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Location: Paris Workplace: Hybrid ABOUT VOODOO Founded in 2013, Voodoo is a tech company that creates mobile games and apps with a mission to entertain the world. Gathering 800 employees, 7 billion downloads, and over 200 million active users, Voodoo is the #3 mobile publisher worldwide in terms of downloads after Google and Meta. Our portfolio includes chart-topping games like Mob Control and Block Jam, alongside popular apps such as BeReal and Wizz. TEAM Our Growth team is a transversal entity aiming to maximize and deliver the potential of any mobile product. It combines user acquisition, creative content production, monetization, and the tech capabilities required to turn applications into global hits. With over 150 experts, we operate at the forefront of mobile marketing and ad tech across various types of games (hypercasual, hybrid, 100% IAP). ROLE - Create mobile video ads that engage millions of people - Become a creative expert in mobile gaming: benchmark what our competitors are doing, experiment with new ideas - Develop a deep understanding of how your creations perform and why - Work within a small creative squad with amazing people from diverse backgrounds and nationalities - Have the opportunity to cover different product scopes (e.g., hyper casual, hybrid, casual) - Contribute to transversal initiatives (e.g., testing new tools) PROFILE - Fully proficient with video editing and content creation - Expert in After Effects - Nice to have: 3D softwares and/or Unity - Creative and have a hacker mindset - Understand how your creations drive marketing performance - Fluent in English, both oral and written - At least 3+ year of experience in a similar role - Hands-on experience with AI creative tools (Scenario, Seedance, Kling, Veo, Runway, etc.) - Deeply familiar with the mobile gaming market, in particular, hyper casual and casual BENEFITS - Competitive salary based on experience - Swile Lunch voucher - Gymlib (100% covered by Voodoo) - Premium healthcare coverage with SideCare, 100% covered for you and your family - Wellness activities in our Paris office

Location: United States Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. PROOF OF WORK   THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients. The Agent Systems team is a 0→1 engineering group building internal AI-powered agents that interact directly with company systems. The mandate is to dramatically increase internal speed of execution through automation, intelligent inference, and workflow orchestration. This team operates at the intersection of AI, backend systems, and applied product engineering. The work is pragmatic and fast-moving — prototypes are expected, but the bar for production reliability remains high. Engineers on this team move fluidly between experimentation and shipping, building systems that reason over user interactions and take meaningful action across internal tools. You’ll work closely with cross-functional partners across product, infrastructure, and internal operations to deploy agent-driven capabilities that compound leverage across the organization.   THE OPPORTUNITY - Build and ship AI-powered agent systems that automate internal workflows and decision paths - Design and implement inference pipelines that reason over user interactions across internal systems - Prototype quickly to validate agent behaviors, then productionize what proves valuable - Architect backend services that integrate with multiple internal APIs and data sources - Define patterns for safe, observable, and controllable agent execution - Collaborate cross-functionally to identify high-leverage automation opportunities - Improve system speed, reliability, and signal quality as usage scales - Contribute to foundational design decisions for a 0→1 agent platform   SKILLS YOU SHOULD HODL - 5+ years of experience building and shipping production software systems - Strong backend engineering fundamentals (APIs, distributed systems, data modeling, reliability) - Experience building fullstack systems, with comfort working across backend and occasional frontend surfaces - Hands-on experience working with AI/ML systems, LLMs, or inference pipelines in production - Ability to prototype rapidly while maintaining a clear path to production-grade architecture - Strong systems thinking — able to reason about orchestration, failure modes, and observability - Comfort operating in ambiguous, 0→1 environments with high ownership   NICE TO HAVES - Experience building or operating agent-based systems or autonomous workflows - Familiarity with prompt engineering, evaluation frameworks, or model performance tuning - Experience integrating with internal enterprise systems (CRM, support tools, analytics platforms, etc.) - Background in building developer platforms or internal tooling - Experience designing guardrails, sandboxing, or safety layers for AI systems Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on X https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

Location: United Kingdom; Brazil; United Arab Emirates; Ireland; Peru; Sweden; Colombia; Argentina; Romania; Cyprus; Switzerland; Portugal; Lithuania; South Africa; Czech Republic; Canada; Hungary; Mexico; Chile; Poland; Spain; Bulgaria Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. PROOF OF WORK   THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients. The Agent Systems team is a 0→1 engineering group building internal AI-powered agents that interact directly with company systems. The mandate is to dramatically increase internal speed of execution through automation, intelligent inference, and workflow orchestration. This team operates at the intersection of AI, backend systems, and applied product engineering. The work is pragmatic and fast-moving — prototypes are expected, but the bar for production reliability remains high. Engineers on this team move fluidly between experimentation and shipping, building systems that reason over user interactions and take meaningful action across internal tools. You’ll work closely with cross-functional partners across product, infrastructure, and internal operations to deploy agent-driven capabilities that compound leverage across the organization.   THE OPPORTUNITY - Build and ship AI-powered agent systems that automate internal workflows and decision paths - Design and implement inference pipelines that reason over user interactions across internal systems - Prototype quickly to validate agent behaviors, then productionize what proves valuable - Architect backend services that integrate with multiple internal APIs and data sources - Define patterns for safe, observable, and controllable agent execution - Collaborate cross-functionally to identify high-leverage automation opportunities - Improve system speed, reliability, and signal quality as usage scales - Contribute to foundational design decisions for a 0→1 agent platform   SKILLS YOU SHOULD HODL - 5+ years of experience building and shipping production software systems - Strong backend engineering fundamentals (APIs, distributed systems, data modeling, reliability) - Experience building fullstack systems, with comfort working across backend and occasional frontend surfaces - Hands-on experience working with AI/ML systems, LLMs, or inference pipelines in production - Ability to prototype rapidly while maintaining a clear path to production-grade architecture - Strong systems thinking — able to reason about orchestration, failure modes, and observability - Comfort operating in ambiguous, 0→1 environments with high ownership   NICE TO HAVES - Experience building or operating agent-based systems or autonomous workflows - Familiarity with prompt engineering, evaluation frameworks, or model performance tuning - Experience integrating with internal enterprise systems (CRM, support tools, analytics platforms, etc.) - Background in building developer platforms or internal tooling - Experience designing guardrails, sandboxing, or safety layers for AI systems       Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on X https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

Location: Paris; Amsterdam; Linz; Munich; London; Berlin Workplace: Remote ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. ABOUT THE JOB Mistral AI is looking for a Domain Expert in crashworthiness simulations to help build AI-accelerated simulation capabilities for industrial engineering. You will work at the intersection of industrial simulation, physics modeling, machine learning, and engineering workflows. Your role is to bring deep solid-mechanics expertise into the design, training, evaluation, and deployment of AI Physics Models for real engineering use cases. This is a hands-on technical role. We are looking for someone who understands industrial structural simulation not only conceptually, but through direct experience with simulation models, solver workflows, data generation, validation, and engineering decision-making. You will work with research, product, and customer-facing teams to ensure that our models are useful against real engineering standards — not only benchmark metrics. Relevant application areas may include automotive crashworthiness, aerospace structures, consumer-electronics drop/reliability, manufacturing, durability/fatigue, and other nonlinear structural mechanics problems. WHAT YOU WILL DO - Work with our research team to define, generate, and iteratively improve simulation datasets for training and evaluating crashworthiness foundation models, balancing coverage of relevant physical scenarios, simulation fidelity, and computational cost. - Design and run high-fidelity simulation campaigns using structural mechanics solvers such as Abaqus, LS-DYNA, Ansys Mechanical, Radioss or equivalent tools. - Define the relevant variation space for training data: geometry, mesh resolution, material behavior, boundary conditions, loading, contact, joints, failure modes, and engineering KPIs. - Build or guide automated pipelines for simulation setup, execution, post-processing, dataset creation, and model evaluation. - Work with research teams to train and evaluate AI models on simulation data, and diagnose failure modes caused by data gaps, poor coverage, numerical artifacts, or model limitations. - Evaluate model outputs against industrial engineering needs, including field-level accuracy, scalar KPIs, deformation modes, load paths, energy absorption, stress/strain fields, failure indicators, uncertainty, and out-of-domain behavior. - Work with industrial customers to understand their simulation workflows and engineering priorities, define use cases and success criteria, and incorporate their feedback into model development and validation. ABOUT YOU - You have deep expertise in crashworthiness, solid mechanics, and structural mechanics, with substantial experience in industrial simulation workflows. - You have a Master’s degree or equivalent technical depth in mechanical engineering, aerospace engineering, civil/structural engineering, computational mechanics, applied physics, or a related field. - You have 4+ years of relevant industrial experience (or PhD +1 years) in domains such as automotive, aerospace, and consumer electronics. - You have hands-on experience with explicit dynamics for crash or impact simulation and understand nonlinear FEM and related topics such as contact, plasticity, structural dynamics, buckling, material modeling, fracture/damage, fatigue, crashworthiness, or durability. - You have direct experience with simulation validation, correlation, model quality, numerical sensitivity, and engineering KPI definition. - You are a strong Python developer who can build and maintain reliable tools for simulation automation, data processing, and model evaluation. You apply sound software engineering practices, including version control with Git, automated testing, code review, and clear documentation. - You have hands-on experience working in Linux and HPC environments, including submitting and monitoring batch jobs, selecting appropriate compute resources, and troubleshooting simulation workflows. You can run simulation campaigns efficiently across a compute cluster. - You are comfortable operating in ambiguous technical environments and turning poorly defined industrial problems into scoped datasets, experiments, metrics, and execution plans. - You communicate clearly with both deep technical experts and non-specialist stakeholders. IT WOULD BE GREAT IF YOU - Have experience applying machine learning, surrogate modeling, reduced-order modeling, optimization, or data-driven methods to simulation problems. - Have contributed to reusable internal tools, open-source code, simulation automation frameworks, or production-quality engineering workflows. - Have experience working directly with industrial customers, product teams, or engineering decision-makers. - Have publications, patents, internal technical leadership, or recognized contributions in engineering, simulation, computational mechanics, or ML-for-physics communities. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: IN - Bangalore, India Scopely is looking for Senior 2D Marketing Artists to join our team based in Bangalore. At Scopely, we care deeply about what we do and want to inspire play every day - whether in our work environments alongside our talented colleagues or through our deep connections with our communities of players. We are a global team of game lovers who are developing, publishing, and innovating the mobile games industry, connecting millions of people around the world daily. We are the in-house creative agency, Flamed, an International multidisciplinary team. We build thousands of creatives every year to support all Scopely games' marketing needs worldwide. What You Will Do We are hiring Senior Marketing Artists with a focus on high-quality visual execution to join our Production Pod in Bangalore. You will be responsible for crafting static visuals (ads, store assets, social media posts) for some of the top mobile games in the world. Produce high-quality marketing assets from briefs and benchmarks, following established pipelines and templates Execute AI-generated visuals, refining them through paintovers, compositing, and final layout Work with 2D tools like Photoshop and Illustrator to assemble polished visuals with clean lighting, retouching, and compositional balance Learn and work with 3D tools like Blender/Maya to create solid baselines for the artwork Participate in performance-based iteration cycles, delivering updated versions based on KPIs and creative performance Work in partnership with Lead Artists to deliver top-notch creatives that reflect brand identity and production benchmarks Ensure all visuals align with brand guidelines and support the maintenance and application of style guides Collaborate with other artists and teams in Barcelona and beyond to ensure visual alignment and timely delivery Maintain precise tracking and accountability through internal workflow tools and reporting platforms Occasionally participate in brainstorms or creative alignment sessions, when requested What We’re Looking For 5+ years of experience in marketing or production art roles, ideally in gaming or entertainment Strong portfolio showcasing execution-heavy marketing art, including AI-generated visuals, and high-quality compositions Strong 2D design fundamentals to create polished visuals with clean compositions, refined retouching, and strong compositional balance Proven skills with AI generation tools (Nano Banana, Flux, Midjourney, ChatGPT, Stable Diffusion, etc.) Excellent knowledge of Adobe Photoshop Understanding of visual fundamentals: layout, color, lighting, and storytelling Self-driven and comfortable working independently within fast-paced production timelines Fluent communication skills in English (spoken and written) Comfortable collaborating with stakeholders across international locations and time zones Bonus Points Experience with UA or ASO asset production 3D production tools knowledge Familiarity with AI art pipelines, prompt writing, and image refinement tools Experience using production tracking systems and collaborative project tools **Please include a portfolio or PDF/links to examples of your work in the application. Applicants need work examples to be considered.** At Scopely, we create games for everyone - and want to ensure that the people behind our games reflect that!  We are committed to creating a diverse, supportive work environment where everyone is treated with respect. We are committed to providing equal employment opportunities and welcome individuals from all backgrounds to join us & embrace the adventure! About Scopely Scopely is a leading video game and global interactive entertainment company, home to many of the world’s most beloved and enduring experiences, including two of the most successful mobile games of all-time “MONOPOLY GO!” and “Pokémon GO,” along with “Stumble Guys,” “Star Trek™ Fleet Command,” “MARVEL Strike Force,” “WWE Champions,” the Scrabble® franchise, “Yahtzee® With Buddies,” and many others. Across mobile, web, PC, and console, Scopely creates, develops, publishes, and live-operates one of the most diversified and award-winning portfolios in the games industry — bringing hundreds of millions of players together through a shared love of play. Founded in 2011, Scopely is powered by its exceptional team — including thousands of world-class gamemakers around the globe, a distinctive tenet-driven culture, and its proprietary technology platform, Playgami. Together, these strengths have fueled Scopely’s position as the #1 mobile games company in the U.S. and #2 globally, generating more than $10 billion in lifetime revenue. Whether building global sensations like “MONOPOLY GO!” from the ground up, or expanding through strategic acquisitions, including the FoxNext, GSN, and Scopely Explore games businesses — Scopely consistently delivers experiences players love today and return to for years to come. Recognized multiple times as one of the "100 Most Influential Companies in the World" by TIME magazine and one of Fast Company's "World's Most Innovative Companies" and “Best Workplaces for Innovators,” Scopely believes that video games can be a force for good — creating meaningful connections, vibrant communities, and making life better through play. Scopely has global operations and partners across four continents in more than a dozen countries worldwide. For more information, visit: https://www.scopely.com/ . Notice to Candidates: Scopely will never request payment or financial information during the application or hiring process. Please apply only through our official website and verify that all Talent Partner communications come from an email address ending in @ scopely.com . Should you have any questions or encounter any fraudulent requests/emails/websites, please immediately contact recruiting@scopely.com. Our job applicant privacy policies are available here: California Privacy Notice and EEA/UK Privacy Notice . Employment at Scopely is based solely on a person's merit and qualifications. Scopely does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law. We also consider qualified applicants with arrest or conviction records, consistent with applicable federal, state and local law.

Location: Chile; Peru; Slovakia; Mexico; Brazil; Spain Crystalia Glass LLC is a U.S.-based manufacturer and provider of premium glass solutions, specializing in custom glass partitions for residential, commercial, and institutional projects. We operate a full-cycle model — from design and manufacturing to sales, delivery, and installation — with production facilities in the United States and Europe. The U.S. market is our core focus. Crystalia Glass is a stable, scaling business, serving B2C, B2B, and B2G clients across multiple states. We combine strong product quality, competitive pricing, high service standards, and operational efficiency to set a benchmark within our industry. We are strengthening our commercial function and are looking for a Sales Manager to take full ownership of sales execution, team performance, and revenue growth in a high-volume, inbound-driven environment. This is a hands-on leadership role requiring strong operational involvement. The Sales Manager will own sales performance end-to-end, including CRM operations, inbound lead management, call quality, analytics, and team development. Employment Type: - Full-time 8.30 am - 5 pm, NY (EST zone). - Remote work. - B2B contract (sole proprietorship status or corporate entity). Responsibilities CRM & Sales Operations: Own and optimise CRM and sales operations, including pipeline structure, lead lifecycle, data hygiene, SLAs, and inbound workflows. Enforce strong CRM discipline across the sales team through training, audits, and corrective actions. Drive performance through structured reporting and dashboards, continuously identifying and improving funnel efficiency. Team Leadership & Development: Lead and develop the sales team - Provide ongoing coaching and mentoring to team members, conducting regular performance reviews and setting goals to ensure they achieve and exceed their targets. Participate in the recruitment and training of new team members, ensuring they are aligned with company values and priorities. Inbound Lead Management: Manage a high-volume inbound lead flow, ensuring fast response times, high-quality lead handling, and balanced workload across Sales Reps. Continuously optimise lead distribution to maximise efficiency, conversion, and team performance. Call Quality & Communication Standards: Own call quality and communication standards, with calls as the primary channel for US-based clients. Regularly review calls, coach on objection handling and structure, analyse deal losses, and develop supporting channels such as SMS and email. Performance & Analytics: Lead the sales function through data and metrics, including conversion rate, close rate, average deal value, speed to lead, and revenue per rep. Design and execute data-backed initiatives to improve conversion and overall sales performance. Proactivity & Continuous Improvement: Proactively identify and solve problems, taking full ownership even with limited resources. Continuously initiate improvements across sales processes, marketing collaboration, tools, and customer engagement with a focus on measurable business impact. Requirements 5–7 years of relevant sales experience, with a strong background in sales execution and revenue growth. At least 2 years of managerial experience, leading and developing sales teams. Proven experience in sales roles, including hands-on ownership of targets, pipelines, and performance. Strong hands-on experience with CRM systems (HubSpot or similar), including daily operational use, reporting, and pipeline control. Hands-on experience managing inbound sales in a high-volume or B2C setting is a must. Experience leading teams of 5+ Sales Reps. Experience with AI tools and structured sales playbooks. Strong analytical mindset with the ability to make data-driven decisions. Experience with call-based sales models. Fluent English (working with US-based clients). High level of involvement in day-to-day sales operations. Nice-to-Have Track record of increasing B2C conversion rates. Cross-functional collaboration experience. CRM optimisation experience. Sales process and pipeline improvement expertise. Benefits Pay: Fixed Salary and bonuses on goals performed. Joining a highly professional and dynamic team. Exciting experience working with prestigious clients in the US market.

Location: San Francisco Bay Area, USA Workplace: Hybrid Why work at Higgsfield AI? Higgsfield AI is the fastest-scaling generative AI company in history, hitting $1B in annual revenue run rate, 30M+ users worldwide, 6M+ generations per day, and powering 390 of Fortune 500 brands. We're building at the absolute frontier of AI-powered video creation and next-generation creative tools. Joining Higgsfield means becoming part of a high-impact team shaping the future of AI-native experiences, at a company that isn't just moving fast, but rewriting what fast looks like. About the role: We are looking for an Investor Relations Manager, Capital Markets & Strategic Research to build and deepen Higgsfield’s relationships across investment banks, equity research, institutional investors, and the broader capital markets ecosystem. This is not a traditional IR role focused on quarterly earnings, filings, or maintaining an investor database. As a private, fast-growing AI company, our goal is to establish Higgsfield as a primary source of insight for the financial community on Creative AI and the transformation of the broader creative economy. You will build relationships with the analysts, bankers, and investors shaping how emerging technology categories are understood, helping ensure they have the data, context, and access needed to understand the size of the market and Higgsfield’s position within it. The goal is not paid placement. It is to build the relationships and credibility that lead analysts to independently recognize Higgsfield as one of the companies defining the Creative AI category. What you'll do: - Build and manage relationships with investment bankers, equity and thematic research analysts, institutional and private-market investors, hedge funds, and other influential members of the capital markets ecosystem. - Establish a systematic engagement program with research teams at leading investment banks. - Develop a regular cadence of analyst briefings, executive conversations, and relationship-building across Wall Street. - Track relevant research covering Creative AI, generative video, the creator economy, advertising, media, AI infrastructure, and adjacent markets. - Make Higgsfield a trusted resource for analysts by providing market intelligence, data, executive access, and informed perspectives on how AI is transforming creative industries. - Educate analysts and bankers on the size and structure of the Creative AI opportunity and why the relevant TAM extends across multiple large existing industries. - Identify upcoming sector reports and research initiatives where Higgsfield can provide insight and contribute to the underlying investment thesis. - Create opportunities for earned inclusion of Higgsfield in thematic and sector research. - Identify opportunities to collaborate on or co-commission credible research examining Creative AI and the transformation of the creative economy, while maintaining a clear distinction between sponsored research and independent analyst coverage. - Partner with Higgsfield leadership, communications, and finance to develop the data, market frameworks, benchmarks, and narratives needed to explain the category. - Track analyst and banking relationships, engagements, relevant reports, upcoming research themes, and resulting outcomes. - Build a deliberate strategy for converting relationships into tangible outcomes rather than treating relationship-building itself as the objective. Requirements: - 3–6+ years of experience in investor relations, investment banking, equity research, capital markets communications, strategic financial communications, or a closely related field. - Strong understanding of how Wall Street research is produced and how relationships with analysts and investment banks are built. - Ability to discuss TAM, industry structure, competitive positioning, and technological disruption with sophisticated financial audiences. - Ability to translate a fast-moving technology story into a credible capital markets thesis without turning it into marketing language. - Highly relationship-driven while remaining focused on measurable outcomes. - Strong written and verbal communication skills with the ability to work closely with senior executives and cross-functional teams. - Comfortable operating in a fast-moving environment where the category, company, and market narrative are evolving quickly. *Nice to have: - Existing relationships across investment banks, equity research analysts, institutional investors, or the broader capital markets community. - Experience covering or working within AI, technology, internet, media, advertising, the creator economy, or high-growth private technology companies. - Experience working with thematic or sector research and understanding how emerging technology categories become incorporated into broader investment theses. - Experience helping position a private, high-growth company with sophisticated financial audiences. Compensation & Benefits - We offer a competitive and thoughtfully structured compensation package designed to align with impact, experience, and long-term growth. - Base Salary: The anticipated salary range for this role is $175,000 - $240,000, depending on experience, skills, scope, and location. - Bonus: This role is Bonus eligible and may participate in the Company's discretionary annual bonus program. - Equity: In addition to cash compensation, employees are eligible to participate in the company’s stock option program and share in Higgsfield’s long-term growth. - Benefits: We offer a comprehensive benefits package designed to support employees professionally and personally, including medical, dental, and vision insurance, a competitive 401(k) retirement plan with company matching, and additional benefits and perks. - The opportunity to work on ambitious AI products alongside a highly experienced, fast-moving, and international team. - Significant ownership, direct impact, and opportunities for professional growth as the company scales. This is a hybrid role based in the San Francisco Bay Area. Team members are expected to work from our San Francisco office three full days per week, with the remaining days worked remotely and are expected to be available during agreed working hours and to maintain sufficient overlap with the relevant team’s time zone. We value in-person collaboration, active communication, responsiveness, and close partnership across teams. Higgsfield AI is an equal opportunity employer. We are committed to building a diverse and inclusive team and do not discriminate on the basis of race, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, disability, veteran status, or any other protected characteristic.

Location: Remote About GiveDirectly What if the most effective way to fight poverty was also the simplest: give people money and trust them to decide what they need? Since 2011, GiveDirectly has proven that idea at scale. We’ve delivered more than $1B in cash directly to 2+ million people living in poverty and crisis across 15 countries, and rigorous research shows the results: healthier kids, stronger businesses, sturdier homes, and more resilient families and local economies. Cash is now widely recognized as one of the most scalable, cost-effective, and dignified forms of aid. Our ambition goes beyond our own programs. We want cash to become the benchmark for aid, much as the index fund became the benchmark for investing, so that every aid dollar is held to one question: is this doing more good than giving the money directly to people living in poverty? We’re growing fast, and this is a rare and important moment to join. We expect to hit $1B in revenue in 2026 with significant growth forecast for 2027. At the same time we are building a new technology stack and operating model designed for a roughly 10x change in scale, and we are actively pursuing partnerships with major funders to move even more money in bigger ways, to people who need it. We are known for our extensive integration of technology into field processes; our quantitative approach to performance measurement; and our commitment to rigorous, independent, experimental evaluation of our impact, with multiple Randomized Control Trials completed and others in progress. How we work Our team spans 20+ countries and 69 languages. Our culture is candid, analytical, and non-hierarchical. We expect high ownership and give people real responsibility early. Our values are central to how we hire, work, and grow, and they are deliberately opinionated: Recipients first. Recipients’ preferences come before those of donors or ourselves. Team next. We optimize for organizational success, not individual success. Be proactively candid. We say what we believe and share information openly. Create positive energy. We aim to be a source of energy for colleagues, not a drain. Think rigorously; act quickly. We reason from first principles, then act rather than debate. Know yourself and grow. We own our imperfections and seek feedback to grow. Accept reality. Propose solutions. We focus on what can change and bring solutions, not just problems. Be productively ambitious. We take risks for step-change impact, not incremental progress. If they describe how you like to work and they energize you, this could be a great fit. Want to learn more? Read and listen: We are one of Time100’s Most Influential Companies of 2026, and our work has been covered by The Economist , NPR , TED , and The Washington Post . We're now preparing to deliver billions of dollars a year to people in extreme poverty, if funding allows. Read our CEO's essay on what that will take. About this role: Are you an experienced engineer at the stage of your career where, above all, you want to do good? This role is about using engineering to support fundraising: delighting our donors; helping our fundraisers; getting donations recorded and safely started on their journey to our recipients; telling donors and the public about what happens to their gifts. A bit of website development. A lot of plumbing. The good news about this position: You will make a difference to people in extreme poverty You will work independently, with few constraints You will work directly with lovely people from across our fundraising teams The trade-offs: There is only one other fundraising engineer and mostly you will be working on your own Our technology is a mixture of boring (Laravel, PHP, plain JS, HTML and CSS) and legacy (Salesforce, Wordpress, wrangling CSV files sent by our partners) We're growing, but this is a role for someone who values depth and impact over a fast title ladder. The maybe good maybe bad news about the role depending on who you are: We are all in on AI where it allows us to get more $ to people in extreme poverty If you want a role where you will be part of a bigger engineering team, working in Python or working on more complex tasks, then please take a look at our other engineering roles . This role is right for you if: You care about our mission You agree with our values You have the right to work in one of the countries we're able to hire from (you can check the current list here ). You're happy working remotely, and taking meetings across East Africa Time and US Eastern Time. You are happy to travel to meet your colleagues in the US, Europe and Africa a few weeks a year You are fluent in English You have 4+ years of engineering experience You're happy working autonomously: defining what needs doing, doing it, getting it tested and launched, fixing the bugs, and hustling to make progress every day. You're comfortable being on-call on peak donation days (Giving Tuesday and the last weeks of the year), including owning an incident: working out what matters, communicating with fundraisers, and debugging on legacy and others' code, sometimes when no other engineers are available. You are happy with our boring and legacy technologies (Laravel, PHP, plain JS, HTML, CSS, Salesforce, Wordpress, SQL, wrangling csv files etc). You don’t have to be experienced in all of them, but you do have to be genuinely happy to use them (many engineers are not…). You are happy and skilled at working directly with non-engineers on messy, poorly defined, rapidly changing, sometimes boring tasks Compensation At GiveDirectly, we strive to pay our employees generously and equitably. We use an accredited third party salary aggregator to calculate what we believe to be competitive pay based on role, location, and cost of living. We also have a no negotiation policy to ensure we are paying staff equitably across roles. Read more about our compensation philosophy here . Unless otherwise noted, the benefits stipend may be used to cover benefits or taken as additional taxable income. United States Base Salary: $181,130 Bonus at Target Performance: 15% (~$27,170, with potential for upside. For reference, with the organization's current performance multiplier, this amount would be ~$31,789 in 2025) Estimated Total Compensation at Target: $208,300+ Annual Benefits Stipend: $21,393 United Kingdom Base Salary: £124,370 Bonus at Target Performance: 15% (~£18,656, with potential for upside. For reference, with the organization's current performance multiplier, this amount would be ~£21,827 in 2025) Estimated Total Compensation at Target: £143,026+ Annual Benefits Stipend: £2,760 Kenya Base Salary: $112,350 Bonus at Target Performance: 15% (~$16,853, with potential for upside. For reference, with the organization's current performance multiplier, this amount would be ~$19,717 in 2025) Estimated Total Compensation at Target: $129,203+ Annual Benefits Stipend: $8,453 This role is fully remote, so if you are not based in the US, UK or Kenya, we will share an estimated salary benchmark for the country you are based in during the hiring process. Why work at GiveDirectly? At GiveDirectly, we work to ensure that you have everything you need to excel in your role and on your team, including: A positive and supportive team with opportunities for advancement A demonstrated commitment to helping all staff develop and grow A competitive salary, including bonus A robust health benefits plan (exact details will vary by country) Unlimited PTO (that we encourage staff to take!) Desk allowance and flexible work location About this specific hiring process Take-home coding assignment Live Coding (60 mins) Systems Design (60 mins) Project Deep Dive + Behavioral (60 mins) *It’s possible that there will be adjustments to this interview process. Any changes will be communicated to you during the process. #LI-REMOTE Working at GiveDirectly GiveDirectly is an Equal Opportunity Employer. All qualified applicants are considered for employment without regard to the person’s race, color, religion, national origin, sex, sexual orientation, age, marital status, veteran status, disability, or any other characteristic protected by applicable law. Flagging for US applicants: We invite you to " Know Your Rights " as an applicant. Commitment to Safeguarding As a global organization working with communities to eliminate extreme poverty, GiveDirectly takes the safeguarding of its recipients, staff, and partners seriously. To that end, GiveDirectly is a member of the Misconduct Disclosure Scheme , and will systematically check with previous employers about any abuse or misconduct related matters involving potential new hires. We may also employ other robust pre-hire screens, including in-depth reference checks, criminal background checks, and sanctions screens. These efforts help us continue to build and maintain trust with the communities we work with, and prevent abuse to our recipients and staff. **GD is committed to observing all local, national and international laws that protect people and basic human rights of all. GD is committed to a policy of “zero tolerance when it comes to preventing,  reporting, or responding to any form of abuse or  exploitation.” and expects anyone who works for GD to uphold the protection and safeguarding of our recipients as a priority.** Reasonable Accommodations We are committed to fostering an inclusive and accessible work environment. If you require any accommodations during the application or interview process, or to perform the essential functions of the role, please email us at careers@givedirectly.org with the email subject “Accommodation Needed”. We will work with you to ensure reasonable accommodations are made to support your needs. Want to put your best foot forward on your GiveDirectly application? Take a look at our Candidate Application Prep Guide !

Location: Remote, Canada; Remote, United Kingdom; Remote, United States GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. About the Role We are looking for a Distinguished Engineer to lead technical direction across GitLab's Core DevOps services, the systems the majority of our users touch every day. Distinguished Engineers are recognized experts across multiple technology domains and represent the most senior level of technical leadership within and across divisions at the company. Core DevOps builds continuous Integration, continuous deployment, planning, and source control experiences. These are among the most mature, highest traffic, and most deeply interconnected systems at GitLab. They carry years of accumulated architectural decisions, they sit in the critical path of our customers' own delivery pipelines, and they are being reshaped by the shift toward AI native development. The job is to raise their quality, converge them onto a coherent go-forward architecture, and retire accumulated risk, all without interrupting the millions of users and Fortune 100 organizations who depend on them. GitLab is pursuing a set of company-wide engineering goals: large gains in developer productivity, measurably higher quality in what we ship, and engineering practices reshaped around AI and agentic workflows. Core DevOps is where much of that strategy has to land, because these are the services our own engineers and our customers depend on daily. In this role you will bring that strategy into Core DevOps in a form that works for long lived production systems, and carry what you learn here back out to the rest of engineering. What You'll Do Set and continuously refine the go forward technical direction for CI, CD, Plan, and source code experiences, aligned against the horizontal architectural initiatives. Work directly with the VP of Engineering as her technical counterpart on planning, technical investment, and where the group's engineering effort should go. Translate GitLab's company-wide productivity, quality, and AI native engineering goals into concrete technical direction for Core DevOps, and turn into iterable roadmaps, partnering broadly across the org. Define what good means in measurable terms for these services, including availability, latency at p95 and p99, pipeline success rate, test reliability, data correctness, and defect escape rate, then hold designs and implementations to it. Maintain a clear and current picture of systemic technical risk across the group, including single points of failure, unowned critical paths, brittle coupling between CI/CD and Plan, scaling limits, and past decisions that now constrain the roadmap. Drive a prioritized plan to retire it. Lead the hardest design decisions hands on, writing code, prototypes, and proofs of concept where a design argument needs evidence behind it. Drive convergence on shared patterns, libraries, and paved paths, reducing how many different ways the same problem gets solved across the group. Design migration paths that let large, long lived systems change underneath users without breaking them, using incremental cutover, dual run, measurable rollback, and deprecation with clear timelines. Adopt the platform capabilities coming from GitLab's AI organization and the company's productivity initiatives into Core DevOps, feed this group's requirements back into them, and help prove what works on systems of this scale and maturity. Serve as the escalation point for complex or contested technical decisions across the group, including those where no single team owns the outcome. Review significant designs and merge requests in the group's critical paths, and use review to teach rather than only to gate. Ensure designs hold across GitLab.com, GitLab Dedicated, and Self-Managed deployments, and respect multi-tenant, compliance, and data governance boundaries in each. Partner with Infrastructure, Security, and SRE so Core DevOps services are observable and debuggable, and so failure modes degrade gracefully instead of cascading. Make architectural constraints and opportunities clear to Product in roadmap terms, so that technical investment and product ambition get planned together instead of traded off late. Write clear, opinionated design documents, architecture narratives, and decision records that let teams across the group make aligned decisions independently. Grow Principal and Staff Engineers across Core DevOps, raise the bar on design rigor and technical writing, and contribute to the technical hiring bar for senior individual contributors. Participate in the Incident Management on-call rotation to help meet availability goals for GitLab.com, and complete Interview Training to participate in hiring as a technical interviewer or panel member. Take part in on-call or operational support where your team’s ownership model requires it. What You'll Bring 10+ years of software engineering experience, including 4+ years in a Staff, Principal, or equivalent senior technical leadership role. Deep expertise in AI and ML systems, including large language models, agentic frameworks, and autonomous workflow design at production scale. Proven track record of leading hands-on technical experimentation, including defining evaluation frameworks, running benchmarks, and translating findings into scalable architecture decisions. Strong background in scalable, multi-tenant distributed systems, including service decomposition, fault tolerance, observability, and operational resilience. Experience designing and implementing human-in-the-loop controls, safety guardrails, and responsible AI practices for production systems. Experience mentoring senior engineers and influencing technical direction across multiple teams or divisions without direct authority. Ability to work effectively in a fully remote, globally distributed organization with excellent written and asynchronous communication skills. The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity . Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. United States Salary Range $250,000 — $349,000 USD How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

Location: United Kingdom; Brazil; Ireland; Romania; Cyprus; Portugal; Lithuania; Czech Republic; Canada; Poland Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients.   We're looking for a Data Analyst, Regulatory Analytics and Reporting to join our team remotely! The #1 goal of this role is to turn complex compliance and regulatory data into clear, actionable insights that protect the business, satisfy regulators, and support senior leadership in making high-stakes decisions. You'll work at the intersection of data engineering, regulatory reporting, and compliance operations in a fast-paced, high-scrutiny environment where accuracy and audit-readiness are non-negotiable. Beyond technical expertise, success in this role depends on being a true business partner who combines data-driven insights with deep knowledge of compliance regulations and frameworks. You'll own end-to-end data management from building and maintaining datasets and pipelines to designing dashboards and insights for compliance and leadership teams. You will also automate compliance processes and workflows to boost efficiency and minimize human error. If you combine exceptional data analysis expertise with solid knowledge of compliance regulations, a keen eye for regulatory risk, and the drive to shape the future of crypto with a top-tier brand - this is your next mission!   THE OPPORTUNITY - Own the design of dashboards, compliance metrics, and regulatory reports, turning data into actionable insights for stakeholders, cross-functional partners, and regional compliance officers - Automate end to end compliance related data solutions, governance controls, and automations to boost efficiency and minimize manual intervention - Dive into large, complex datasets to turn findings into scalable, audit-ready data models that facilitate regulatory reporting and analytics - Translate regulatory and business requests into accurate reports and automated data pipelines using Python, SQL, DBT and Airflow - Lead cross-functional projects with analysts, engineers, and compliance teams to build and maintain high-quality data pipelines and sources - Coordinate client data quality monitoring by identifying issues, flagging remediations, and partnering with responsible teams to ensure timely resolution - Support ad-hoc data requests for audits, exams, risk assessments, and day-to-day business needs - Deliver insights that shape compliance direction through clear, data-driven storytelling   WHAT YOU BRING - 5+ years of experience in data analysis and data management within financial services or a regulated industry, with hands-on experience in compliance and regulatory reporting across frameworks such as AML, KYC, Sanctions, MiCA, or MiFID - Solid understanding of regulatory risk and the ability to operate effectively in high-scrutiny, audit-ready environments - Expert SQL skills including complex joins, CTEs, and analytical functions, paired with proficiency in Python libraries such as pandas, matplotlib, and plotly - Hands-on experience using dbt or similar tooling to model and organize high fidelity data for reporting and decision-making - Experience setting up and managing data pipelines with a strong understanding of data workflow orchestration - Proficiency with BI and data visualization tools such as QuickSight, Power BI, or Superset to build executive-facing dashboards - Strong communicator who can simplify complex data ideas for both technical and non-technical audiences - Alignment with the values outlined in Kraken's Tentaclements document   NICE TO HAVES - Degree in Mathematics, Statistics, Finance, Information Systems, or a related technical field - Passion for continuous learning and approaching problems with a beginner's mindset - Solid understanding of the cryptocurrency space and how financial markets function Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on X https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

Location: Paris Workplace: Hybrid ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE ROLE Cybersecurity is one of the areas where AI could do the most good — and one where the capability must be built with particular care. As a Research Engineer on this track, you'll push our models' capabilities in vulnerability discovery and remediation, security analysis, incident response, and across the offensive-to-defensive spectrum of cybersecurity, and it will be your job to develop that ability deliberately and safely. The work sits at the meeting point of research and engineering: you'll devise new approaches and be the one to implement them. Concretely, that means designing and building RL environments that reproduce realistic security scenarios, pipelines that generate synthetic training instances at scale, and experiments and evaluations that show what our models can actually do. Your results feed directly into the production training runs that shape our frontier models, in close collaboration with Mistral's researchers, engineers, and security specialists. Security specialists and ML engineers are both welcome here — what matters is that you can hold your own in both worlds, and are eager to go deeper on the one you know less. WHAT YOU WILL DO - Design and implement RL environments simulating cybersecurity scenarios. - Build the pipelines and infrastructure that generate synthetic cybersecurity training instances at scale — thousands of scenarios, not one hand-crafted exercise. - Conduct experiments and evaluations of model capabilities on these environments, from quick prototypes to controlled benchmark runs. - Own the infrastructure behind the environments: containers, sandboxes, VMs, cloud deployments, and orchestration (Kubernetes), all managed as code. - Partner with researchers and security specialists across Mistral, distilling their domain expertise into reproducible environments and datasets. - Write clear, efficient code in Python and enforce strong software-design practices: testing, code review, CI/CD. WHAT WE'RE LOOKING FOR - Hands-on expertise in offensive and/or defensive cybersecurity: vulnerability analysis, web/network/cloud security, secure coding practices, and SOC. - Strong software engineering skills: clean, reliable, well-tested code — not just exploit scripts. - Fluency in Python plus comfort reading lower-level languages (C/C++) for vulnerability analysis. - DevOps experience: Docker, Kubernetes, cloud deployments, sandboxed or simulated environments. - A pragmatic research-to-engineering mindset: ship a working first version, then refine and scale it. - Working knowledge of RL techniques and LLM training methodologies, or strong motivation to develop it. - Self-starter, low-ego, collaborative — comfortable working across research and engineering. NICE-TO-HAVES - CTF, cyber-range, or bug-bounty experience — as a player, challenge author, or platform builder. - A research background in cybersecurity, academic or industrial, or in another experimental discipline. - Prior experience building RL environments or large-scale ML training infrastructure. - Relevant open-source contributions and projects. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Limassol, Cyprus Workplace: fully Sumsub is the first AI-powered trust infrastructure for compliance operations at scale. It connects identity and business verification, fraud prevention, transaction monitoring, and risk workflows, helping teams reduce manual work and enter new markets. Trusted by over 4,000 clients across financial services, crypto, mobility, trading, marketplaces, education, and iGaming, including Bybit, Bitpanda, Wirex, Avis, Vodafone, Duolingo, and Kaizen Gaming. Sumsub is recognized as a Great Place To Work® in the US and rated 4.4 out of 5 on Glassdoor. Our 1,000+ people around the world back it up, too: 92% are proud to be Sumsubers, and 90% say their work is interesting and challenging. We are looking for a Product Manager (or a strong Project Manager with a product mindset) to take ownership of the user experience within our main client dashboard. Your goal will be to support, scale, and dedicatedly evolve this direction. What You Will Be Doing: Work on the redesign the main dashboard home page and build end-to-end activation flows (product tours, checklists, contextual hints, gamification) to guide new clients from initial login to full production deployment. Create a self-serve communication system (pop-ups, feature adoption nudges, announcements, promo campaigns) enabling marketing and product teams to reach targeted users at the right time without continuous engineering intervention. Run A/B tests, map user funnels, and continuously measure performance against activation speed, feature adoption, and client retention. Take features across the entire product lifecycle—from early concept and clear milestone definition to cross-functional alignment and final production launch. Act as the central node between Product, Design, Marketing, and Engineering to turn fragmented business requests into a unified system. Collaborate on related projects like the service marketplace (purchasing/activating add-on services) and Web SDK evolution. About You: Proven track record of defining clear milestones, working through technical and design constraints, and pushing features across the finish line to production. Excellent communication skills with a strong ability to align engineering, UI/UX design, marketing, and business leads. Comfortable analyzing onboarding funnels, building hypothesis-led experiments, and optimizing metrics for user activation and adoption. Fluent English (from C1). Prior experience in B2B SaaS platforms, complex dashboards, or developer-focused product ecosystems will be a plus. What We Offer: Remote-first, trust-based culture. Work from the place that works best for you. No mandatory office days, no attendance trackers. In some locations, we provide offices or coworking spaces, but the choice is yours. True flexibility. We do not fix you to a 9-to-5 schedule. You can adjust your working hours when needed, as long as your day stays productive and in sync with the team. Extra time off. Your birthday is a holiday here. Add to that 10 personal days each year, seven sick days without paperwork, and extra time to enjoy Christmas and New Year. Time to rest is part of the deal. Work that matters. Our mission is to build a digital world that is secure, accessible and inclusive for everyone. From fighting fraud to making online services easier and safer to use, your work will have a real impact on how people experience trust online. Compensation. We offer fair and transparent pay, benchmarked to the market. Truly global. We work across continents and time zones, with teammates and customers from all over the world. You will run campaigns that cross borders, cultures, and languages, and see your ideas land worldwide. Growth built in. Clear goals, open feedback and personal development plans. We support your progress with learning opportunities and by covering role-specific events, from design conferences to marketing forums. Celebrating your big moments. We are proud to support you through life’s biggest journeys with dedicated financial bonuses for both marriage and welcoming a new baby to your family. Team offsites. Sometimes just Slack is not enough. That is why we meet in person a few times a year. Trips are fully covered, so you can meet, collaborate, and recharge together. Getting you set up. We make sure you have access to the tools and hardware you need to do your work well. Friendly by design. Our logo is a dog for a reason. We keep things human, open and kind. We welcome individuality, quirks and different perspectives, because that is what makes our work smarter and more fun. The hiring stages: TA Interview -> Interview with Product Experience Lead -> Final Interview. Sounds like a great opportunity for your career development? Then go ahead and apply! We are a global community of innovators, creators, and thinkers, and we believe that diversity fuels our innovation. Sumsub is proud to be an equal opportunity employer, committed to building a diverse and inclusive workforce. We welcome applications from people of all backgrounds, cultures, genders, experiences, abilities and perspectives. Join us in shaping the future inclusively. We believe in fair and transparent compensation. Salaries vary depending on work location and applicable local market conditions. This role is open to candidates in multiple countries, and compensation differs based on the candidate’s confirmed work location. For this reason, a single universal salary range is not included in this job posting. The applicable work location will be confirmed early in the recruitment process, and the relevant compensation information for that location will be shared in writing, in line with local requirements.

Location: San Francisco Workplace: Hybrid WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW Harvey is looking for a Strategic Sourcing Manager to join the Finance team and own sourcing for our engineering technology and software categories. You will report directly to the Head of Procurement, based in the San Francisco HQ office. This role owns the commercial relationship with the vendors that support Harvey's product and engineering organization: cloud infrastructure, data platforms, security and observability tooling, developer platforms, and enterprise SaaS. You will run competitive sourcing events, negotiate pricing and terms that improve as Harvey scales, manage the renewal pipeline, and partner with Engineering, Security, Legal, and FP&A to get deals done without unnecessary friction. Harvey's spend is scaling fast, and our sourcing motion has to scale with it. WHAT YOU'LL DO Category Strategy & Sourcing - Own category strategy and the sourcing pipeline for cloud infrastructure, data platforms, security and observability tooling, developer tools, and enterprise SaaS - Lead end-to-end sourcing events (RFI/RFP, supplier evaluation, selection) for new technology purchases; maintain a competitive supplier landscape for each category - Analyze vendor pricing, usage patterns, and market benchmarks to identify opportunities to improve economics and reduce commercial risk Commercial Negotiation & Contract Structure - Lead commercial negotiations with software and infrastructure vendors, including committed-spend, tiered, usage-based, and enterprise license agreements - Structure agreements that balance commitment, flexibility, and unit economics as Harvey's usage grows; right-size license counts and tiers to actual utilization - Drive redlines on MSAs, order forms, and DPAs in partnership with Legal, Security, and Privacy; own the deal from first proposal through signature in Zip - Support the Head of Procurement and Partnerships on strategic AI provider agreements with usage analysis, benchmark data, and contract administration Stakeholder Partnership - Partner with Engineering and Finance to forecast demand, translate technical requirements into sourcing strategy, and turn Harvey's growth into negotiating leverage - Serve as the commercial point of contact for engineering leadership; engage early in build-vs-buy decisions and vendor evaluations - Coordinate Security, Legal, and Privacy review so that technology purchases move through intake at the speed the business needs Renewals, Supplier Management & Reporting - Own the renewal calendar for technology and software vendors; prepare negotiation briefs, utilization analysis, and benchmark data ahead of each renewal - Manage supplier relationships through execution, utilization monitoring, escalations, and renewal; consolidate overlapping tools and eliminate shelfware; track savings and cost avoidance against target - Build AI-powered sourcing playbooks and tooling for redlining, negotiation prep, and benchmarking that raise throughput and deal quality across the team WHAT YOU HAVE - 4–7 years of strategic sourcing or procurement experience with a focus on technology and software categories - Track record of negotiating enterprise SaaS, cloud infrastructure, or security tooling agreements with vendors such as AWS, Google Cloud, Snowflake, Datadog, GitHub, Okta, or comparable - Understanding of software commercial models: per-seat and usage-based pricing, committed spend, tiers, discounts, and true-ups - Strong analytical skills: unit-cost analysis, TCO modeling, and benchmarking; able to find the real economics underneath a vendor proposal - Working knowledge of commercial and legal contract terms (MSAs, order forms, SOWs, DPAs); comfortable driving redlines in partnership with Legal - Clear, direct communicator with executives and across the negotiating table - Hands-on experience running sourcing in a procure-to-pay platform (Zip preferred) - AI fluency: you actively use AI tools for redlining, negotiation prep, benchmarking, and vendor analysis - Comfortable operating at pace: high deal volume, ambiguity, imperfect information, and a bias toward execution COMPENSATION $160,000 - $220,000 USD DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-TA1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Location: Remote - United States Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: Video is where multimodal models are weakest and hardest to grade. Temporal reasoning, long-form understanding, grounding events in time, and holding audio, video, and text together do not fall out of image benchmarks — and the evaluations for them are still immature. Closing that gap is gated as much by how we design data and evaluation as by architecture. Innodata builds that data and those evaluations for the customers and frontier labs advancing video and multimodal models, and we are hiring a Research Scientist to own the science behind it. You will partner directly with the customers and frontier labs building video understanding, video-language, and video-generation models, as interested in the data behind them as in the models themselves. Video spans two model families judged in completely different ways: models that understand video — answering questions, localizing events, grounding language in time — where the question is whether the answer is correct; and models that generate it, where fidelity, temporal coherence, and physical plausibility matter and no automatic metric is settled. You own the evaluation science for both, and knowing when model-based scoring can stand in for a human versus when it can't. Your conclusions shape what our partners measure and collect next. What You’ll Own: You will define how Innodata designs, structures, and evaluates video data for video and multimodal models, and you will validate those choices experimentally. Concretely, you will: Translate the requirements of video and multimodal models — video understanding, temporal and event localization, action recognition, long-form video, video-language models, video generation, cross-modal reasoning, and multimodal retrieval and grounding — into concrete data specifications: modalities, annotation schemas, sampling, and evaluation criteria. Build evaluation methodology for video understanding — temporal grounding accuracy, long-context and long-horizon reasoning, and dynamic multi-turn, cross-modal, and retrieval-and-grounding evaluation — clear about when model-based scoring is trustworthy and when a human is needed. Build evaluation methodology for video generation — fidelity, temporal coherence, and physical plausibility, including generative video used as a world model — the regime where automatic metrics are weakest and human judgment matters most. Decide how existing and incoming video should be structured, enriched, and sampled to extract the most model value from it, including from messy, domain-specific footage. Run experiments that prove data decisions matter: fine-tune and evaluate models on Innodata data, with ablations tying specific data choices to measurable improvement. Design adversarial and stumping evaluations that surface where video and multimodal systems fail, and turn those failures into better data. Publish. Turn what you learn into benchmarks, methodology, and papers that advance the field and earn the trust of the customers and frontier labs we partner with. Work with annotation teams, subject-matter experts, and the synthetic-data pipeline to turn specifications into operational collection and labeling plans. You’ll Thrive in This Role If You Have: Roughly 5+ years of hands-on industry experience in video understanding or multimodal ML. We weight practical experience over formal credentials; a PhD with a compelling, current research agenda can offset the lower end. A Bachelor's degree in computer science, electrical engineering, or a related technical or quantitative field is required; an advanced degree (MS or PhD) in a relevant field is preferred. Trained and evaluated video or multimodal models yourself, with strong PyTorch fundamentals. Fluency in the formats and tooling video work runs on: ffmpeg and decord pipelines, temporal and COCO-style annotation, WebDataset, Parquet and Arrow, and HuggingFace datasets. Experience fine-tuning large video or vision-language models with the modern toolchain (HuggingFace transformers, PEFT, efficient inference), and with long-form video, streaming, temporal segmentation, or synthetic video generation. A way of thinking in datasets and benchmarks: you have built evaluation sets, calibrated difficulty, and argued about what makes video data good for a given objective. A track record the field recognizes: first-author publications or strong open-source contributions at venues such as CVPR, ICCV, ECCV, NeurIPS, or ICLR. The ability to work directly with the research scientists at the customers and frontier labs we partner with, and to explain data and modeling decisions clearly to both expert and non-expert audiences, backed by a rigorous, reproducible approach to experiments and documentation. Bonus: interest or hands-on experience in responsible-AI evaluation and red-teaming — safety and robustness testing for video and multimodal systems. The expected salary range for this position is $160,000 - $185,000 p/year, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov .

Location: Remote - United States Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: Where models actually differ now is robustness across accents, noise, and code-switching; speaker diarization; the naturalness of generated speech; and latency under streaming. Measuring those honestly, and building the data that trains for them, is gated as much by data and evaluation design as by architecture. Innodata builds that data and those evaluations for the customers and frontier labs advancing speech and audio models, and we are hiring a Research Scientist to own the science behind it. You will partner directly with the customers and frontier labs building ASR, text-to-speech, speech-to-speech and conversational voice, diarization, and audio-language models, as interested in the data behind them as in the models themselves. Your work is judgment: which conditions and languages a benchmark must cover to be honest, what a transcription convention should be for a given objective, and when an automated metric can be trusted versus when a human ear is required. You will also partner closely with our transcription and linguistics lead, whose standards directly shape what the models learn. What You’ll Own: You will define how Innodata designs, structures, and evaluates audio data for speech and audio models, and you will validate those choices experimentally. Concretely, you will: Translate the requirements of speech and audio models — ASR, text-to-speech and speech generation, speech-to-speech and conversational voice, speaker diarization and verification, audio-language models, and streaming systems — into concrete data specifications: modalities, transcription and annotation schemas, sampling, and evaluation criteria. Build evaluation methodology that goes past word error rate — semantic accuracy, robustness to noise and accent, code-switching, diarization error rate (DER), naturalness and intelligibility of generated speech, and streaming latency — and know when automated metrics hold and when they don't. Decide how existing and incoming audio should be structured, enriched, and sampled for coverage that fits the model objective — across languages, accents, and acoustic conditions (studio, real-world, telephonic), speaker demographics, emotional and paralinguistic range, scripted versus spontaneous speech, and single- versus multi-speaker settings, including low-resource and code-switched speech. Partner with the transcription and linguistics lead to turn model objectives into transcription specifications, and to quantify how transcription conventions and quality move ASR and speech-model results. Partner with the audio solutions and engineering team so the audio we collect is built for the model objective: you specify what good data and evaluation require, and they scope programs with customers and capture audio to spec. Run experiments that prove data decisions matter: fine-tune and evaluate models on Innodata data, with ablations tying specific data choices to measurable improvement. Design adversarial and stumping evaluations — noisy, accented, and adversarial audio — that surface where speech systems fail, and turn those failures into better data. Publish. Turn what you learn into benchmarks, methodology, and papers that advance the field and earn the trust of the customers and frontier labs we partner with. Work with annotation teams, subject-matter experts, and the synthetic- and augmented-audio pipeline to turn specifications into operational plans. You’ll Thrive in This Role If You Have: Roughly 5+ years of hands-on industry experience in speech or audio ML. We weight practical experience over formal credentials; a PhD with a compelling, current research agenda can offset the lower end. A Bachelor's degree in computer science, electrical engineering, or a related technical or quantitative field is required; an advanced degree (MS or PhD) in a relevant field is preferred. Trained and evaluated speech or audio models yourself — ASR, TTS, speech-to-speech, speaker, or audio-language models — with strong PyTorch fundamentals. Fluency in the toolchains and metrics speech work runs on: ESPnet, NeMo, SpeechBrain, or Kaldi, HuggingFace, forced alignment, and WER/CER and the metrics that go beyond them. Hands-on experience with multilingual, accented, dialectal, low-resource, or code-switched speech, and with synthetic or augmented audio (TTS pipelines, noise and room-response simulation). A way of thinking in datasets: you have built evaluation sets, reasoned about coverage across conditions, and argued about what makes speech data good for a given objective. A track record the field recognizes: first-author publications or strong open-source contributions at venues such as Interspeech, ICASSP, ASRU, SLT, or NeurIPS. The ability to work directly with the research scientists at the customers and frontier labs we partner with, and to explain data and modeling decisions clearly to both expert and non-expert audiences, backed by a rigorous, reproducible approach to experiments and documentation. Bonus: interest or hands-on experience in responsible-AI evaluation and red-teaming — for example spoofing and voice-cloning robustness, or bias across accents and languages. The expected salary range for this position is $160,000 - $185,000 p/year, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov .

Location: Remote - United States Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: Progress in physical AI is gated as much by data design as by model architecture. The best manipulation and locomotion policies, vision-language-action models, and world models are only as good as the trajectories, demonstrations, and environments they learn from — so the highest-leverage decisions are made long before a model trains: what to capture, what to synthesize, how to represent an action, and how to know whether any of it will transfer to a real robot. Innodata is building the data and evaluation practice behind the next generation of robotics foundation models, in direct partnership with the customers and frontier labs defining that frontier. We are hiring a Research Scientist to own the science of that data. You will partner directly with the customers and frontier labs building robot foundation models, as interested in the data those models learn from as in the models themselves. Your leverage is scientific judgment about data: deciding what is worth capturing in the real world versus generating in simulation, how to weight a training mix across embodiments and sensors, and how to measure whether a policy will hold up outside the lab. Your conclusions will shape what our partners collect next. What You’ll Own: You will define how Innodata designs, structures, and evaluates data for robot foundation models, and you will validate those choices experimentally. Concretely, you will: Translate the requirements of robotics foundation models — vision-language-action models, world models, and manipulation and locomotion policies — into concrete data specifications: modalities, action representations (tokenization, chunking, diffusion and flow-matching action experts), sampling, annotation schemas, and evaluation criteria. Decide what is worth capturing in the real world versus generating in simulation, and curate and weight training mixes across heterogeneous robot datasets that span different embodiments, action spaces, and sensor setups. Guide collection across capture modalities — motion capture, egocentric, exocentric, teleoperation, and multi-sensor — and across synthetic pipelines, so that what we produce maps cleanly to model needs rather than accumulating for its own sake. Build evaluation and benchmarking methodology that predicts real-world transfer — coverage, discriminative power, reliability, and sim-to-real fidelity — including world-model evaluation (rollout quality and action-conditioned prediction) and the domain-randomization and system-identification choices that close the sim-to-real gap. Run the experiments that prove it: fine-tune and evaluate foundation models on Innodata data, with data-quality ablations and scaling studies that demonstrate specific data decisions produce measurable model improvement. Design adversarial and long-horizon evaluations that surface where policies and world models break, and turn those failure modes into better data. Publish. Turn what you learn into benchmarks, methodology, and papers that advance the field and earn the trust of the customers and frontier labs we partner with. Collaborate with the capture lab, annotation teams, and the synthetic-data pipeline to turn specifications into operational collection and labeling plans. You’ll Thrive in This Role If You Have: Roughly 4+ years of hands-on industry experience in robot learning or robotics ML. We weight practical experience over formal credentials; because the field is young, a PhD with a compelling, current research agenda can offset the lower end, and we will also consider very senior candidates with the right background. A Bachelor's degree in computer science, electrical engineering, robotics, or a related technical field is required; an advanced degree (MS or PhD) in a relevant field is preferred. Trained and evaluated robot policies yourself — manipulation or locomotion via imitation learning or reinforcement learning — with strong PyTorch fundamentals. You build and measure models, you don't just call them. A way of thinking in datasets: you have curated, filtered, and weighted robot data across embodiments and sensors, and you have real opinions about what makes it good for a given objective. Fluency in robotics data formats and standards — the LeRobot dataset format, RLDS, and Open X-Embodiment — along with common motion and sensor formats. Hands-on experience with simulation and synthetic data — NVIDIA Isaac Sim, Isaac Lab, and Omniverse, or MuJoCo and comparable engines — including domain randomization, system identification, and sim-to-real transfer. Experience with teleoperation or egocentric data collection, and comfort adapting VLM backbones for control and fine-tuning large VLA models with the modern toolchain (HuggingFace transformers, PEFT). A track record the field recognizes: first-author publications or strong open-source contributions at venues such as CoRL, ICRA, IROS, RSS, or NeurIPS. The ability to work directly with the research scientists at the customers and frontier labs we partner with, and to explain data and modeling decisions clearly to both expert and non-expert audiences, backed by a rigorous, reproducible approach to experiments and documentation. Bonus: interest or hands-on experience in responsible-AI evaluation and red-teaming for embodied systems, for example safety and robustness testing. The expected salary range for this position is $160,000 - $185,000 p/year, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov .

Location: Remote - United States Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: As speech and audio models get better, the human role gets harder, not easier — it moves from producing transcripts to defining what a correct one is, adjudicating the cases models still get wrong, and designing the human-in-the-loop workflows that keep improving them. Innodata runs high-volume segmentation and transcription workflows for the customers and frontier labs building these models, and we are hiring a principal-level linguist to own the linguistic standards and quality behind that work — today, and as the workflows evolve alongside the models over the next two years. This is the applied-expert counterpart to our Speech & Audio Research Scientist. You set the standards the models are trained and measured against, and you understand the big picture: how different transcription and segmentation methods change what a model learns, and how that ripples into the speech and content-understanding systems our partners are building. You know the research and you know the tools — from IPA and acoustic analysis to forced alignment and the ASR engines our partners benchmark against — but your leverage is linguistic judgment and standard-setting at scale, not building models yourself. What You’ll Own: You will own the linguistic foundation of Innodata's segmentation and transcription work across languages, domains, and use cases. Concretely, you will: Define transcription and segmentation standards, style guides, and annotation conventions — verbatim and clean/intelligent verbatim, IPA and phonetic transcription, timestamping and boundary segmentation, speaker labeling and diarization labels, disfluencies and non-speech events, code-switching, and orthographic conventions. Establish and run the quality frameworks behind that work: rubrics, error taxonomies, adjudication processes, inter-annotator agreement, and human QA at scale. Own the quality lifecycle for transcription and segmentation deliverables end to end — pre-processing and normalization of incoming data, quality checks at the point of acceptance, post-processing and pre-delivery validation against spec, and report creation and packaging for delivery — partnering with delivery operations on execution at scale. Design the human-in-the-loop workflows themselves — deciding where human review, correction, and adjudication add the most value as ASR quality rises, so our experts spend their time on what the models still can't do rather than on what they already can. Handle the linguistically hard cases models fail on — accented and dialectal speech, low-resource and multilingual audio, overlapping speech, domain jargon (medical, legal, technical), and noisy acoustic conditions. Partner with the Speech & Audio Research Scientist to turn model objectives into transcription and segmentation specifications, and to work out how different transcription methods — verbatim versus clean, phonetic versus orthographic, and how audio is segmented and labeled — affect the training and evaluation of ASR, TTS, and speech and content-understanding models. Train, calibrate, and mentor expert transcribers and reviewers, and build the onboarding and calibration that keep quality consistent as the work scales. Represent Innodata's transcription and segmentation approach to the customers and frontier labs we partner with, and contribute to the methodology and best-practice documentation that make our work legible to their teams. You’ll Thrive in This Role If You Have: Substantial industry experience (typically 8+ years) in transcription, segmentation, and speech-data quality — enough that you have authored standards, not only followed them. This is a principal-level role, and we weight practical depth heavily. A Bachelor's degree in linguistics, phonetics, or computational linguistics, or a closely related field, is required — with a strong foundation in phonetics, phonology, and sociolinguistics so that IPA, prosody, disfluency, dialect, and register are native concepts. An advanced degree is preferred. A big-picture grasp of how transcription and segmentation choices flow downstream into modeling — how different methods change what speech and content-understanding models learn, and therefore which method fits which modeling objective. You can explain to a model builder why a transcription decision matters. Fluency in phonetic transcription and IPA, plus hands-on experience with acoustic and phonetic analysis of speech — spectrograms, formants, pitch and prosody, and segment boundaries — applied to real, messy speech data at scale (for example in Praat). Deep experience with audio segmentation and its conventions — utterance and turn boundaries, timestamping, and speaker and diarization labeling — across real-world audio. Hands-on fluency with the modern speech stack: Whisper and the commercial ASR engines your partners benchmark against (such as AssemblyAI, Deepgram, Rev, and Speechmatics), forced alignment (for example the Montreal Forced Aligner), and annotation tools such as ELAN. Comfort scripting for speech-data work — Python for batch processing, QA, and metrics such as inter-annotator agreement and WER, plus regular expressions and Praat scripting — enough to work fluently with data and pipelines without needing an engineer for every task. Practical data-management skills across the delivery lifecycle — pre-processing, acceptance-stage quality checks, post-processing, pre-delivery validation, and report creation and packaging — so deliverables leave the door correct, consistent, and well documented. Multilingual capability and hands-on experience with accented, dialectal, and code-switched speech; low-resource languages a strong plus. A point of view on how human-in-the-loop workflows should evolve as models improve — where humans stay in the loop, where they move up to adjudication and standard-setting, and how to measure the difference. Strong written and verbal communication, comfortable working directly with research scientists and interfacing with the customers and frontier labs we partner with. Bonus: responsible-AI considerations for speech, such as bias across accents and dialects and privacy and consent in voice data. The expected salary range for this position is $160,000 - $185,000 p/year, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov .

Location: Boston, MA Workplace: OnSite ABOUT US At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale. We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry. More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale. ABOUT THE TEAM The LangSmith team owns and builds LangChain's core platform for observability, evaluation, and production reliability of AI systems. From tracing and annotation to run rules, evaluations, and beyond, this team owns LangSmith end-to-end. If you want to define what great AI observability looks like at production scale, this is where that work gets done. ABOUT THE ROLE (Onsite in Boston) We’re looking to bring on an experienced frontend engineer to develop and enhance new features on LangSmith, our enterprise platform product for LLM application observability, testing, and debugging.   WHAT YOU WILL DO - Develop new user-facing features using React & Typescript - Build reusable components and front-end libraries for future use - Translate designs and wireframes into high-quality code - Optimize components for maximum performance across a vast array of web-capable devices and browsers - Collaborate with fullstack and backend developers and UX/UI designers, to enhance usability   WHAT YOU WILL BRING - Extensive front-end engineering experience with strong proficiency in React, JavaScript and TypeScript - Hands-on experience with front-end development tools like Babel, Vite, Webpack, NPM, and Yarn - Familiarity with REST APIs and experience working closely with fullstack and backend engineers - Knowledge of modern authorization mechanisms, such as JWTs - A passion for user experience, design and building clean, engaging, and intuitive interfaces - Strong written and oral communication skills, with the ability to explain technical concepts clearly and concisely to both technical and non-technical stakeholders - The DNA to thrive in a start-up, fast-paced environment. Views unstructured environments as an opportunity to figure out the most impactful work and help define the future success of the company - An ownership mind-set. You are self-driven and look for opportunities to make an impact. - Strong computer science fundamentals, ideally with a degree in computer science or related field   Annual salary range: $170,000-$235,000 USD COMPENSATION PHILOSOPHY: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.