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Location: New York 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 As a Staff Software Engineer on the Core Infrastructure team at Harvey, you'll play a critical role in designing and building new infrastructure systems while equally scaling and strengthening our existing infrastructure. Our infrastructure is the foundation that powers every user interaction with Harvey — processing billions of prompt tokens and millions of daily requests across our global legal AI platform. You'll work in an environment balanced between innovation — building new systems — and operational excellence, ensuring that Harvey remains resilient and efficient as it scales products, regions, customers, and usage. Your contributions will directly impact the reliability, scalability, and security of our platform as we serve the world's leading law firms and professional service providers. This role is based in New York City, New York. We use an in-person work model and offer relocation assistance to new employees. WHAT YOU’LL DO - Design and build scalable, fault-tolerant infrastructure systems that power Harvey's AI platform across multiple cloud regions - Own and evolve our multi-cloud infrastructure (Azure, GCP), including Kubernetes orchestration, networking, and container management - Lead technical initiatives around observability, incident response, and operational excellence — building systems that enable rapid detection and resolution of issues - Architect and optimize our distributed systems for reliability, including load balancing, quota management, and failover mechanisms - Partner with Product Engineering and Security teams to ensure our infrastructure is an accelerant, not a constraint - Drive infrastructure-as-code practices using tools like Terraform and Pulumi to enable reproducible, auditable deployments - Mentor engineers and raise the technical bar across the organization through code reviews, design reviews, and technical leadership REPRESENTATIVE PROJECTS - Design and implement a next-generation model proxy architecture that routes millions of daily inference requests while maintaining model API compatibility and enabling seamless model integration - Build distributed rate limiting and quota management systems using Redis-backed algorithms to handle bursty traffic patterns without degrading user experience - Architect multi-region deployment strategies that meet strict data residency requirements for global enterprise customers - Develop comprehensive observability infrastructure with granular SLA monitoring, burn rate alerts, and detailed token attribution for cost tracking - Lead the evolution of our CI/CD pipelines to improve developer velocity while maintaining production stability WHAT YOU HAVE - 10+ years of experience in Infrastructure Engineering or Platform Engineering in a production environment - Long track record building and scaling complex, large-scale distributed systems - Deep proficiency with cloud infrastructure platforms (Azure preferred; GCP or AWS experience transfers well) - Strong fluency in Infrastructure as Code (IaC) tools — Terraform, Pulumi, or CloudFormation - Solid understanding of Kubernetes, container orchestration, networking, and cloud security at scale - Experience with observability tools (Datadog, Sentry) and incident response practices (PagerDuty, Incident.io http://Incident.io) - Strong programming skills in Python, Go, or similar languages - Excellent problem-solving skills, a "spidey sense" of where things could go wrong, and a commitment to operational excellence NICE TO HAVE - Experience building infrastructure for AI/ML workloads or high-throughput inference systems - Background with distributed rate limiting, load balancing, or quota management systems - Experience operating multi-tenant platforms with strict security and compliance requirements - Track record of leading complex cross-functional projects and delivering measurable impact COMPENSATION RANGE $201,000 - $264,000 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-AN2 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: San Francisco 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 As a Staff Software Engineer on the Core Infrastructure team at Harvey, you'll play a critical role in designing and building new infrastructure systems while equally scaling and strengthening our existing infrastructure. Our infrastructure is the foundation that powers every user interaction with Harvey — processing billions of prompt tokens and millions of daily requests across our global legal AI platform. You'll work in an environment balanced between innovation — building new systems — and operational excellence, ensuring that Harvey remains resilient and efficient as it scales products, regions, customers, and usage. Your contributions will directly impact the reliability, scalability, and security of our platform as we serve the world's leading law firms and professional service providers. This role is based in San Francisco, CA. We use an in-person work model and offer relocation assistance to new employees. WHAT YOU’LL DO - Design and build scalable, fault-tolerant infrastructure systems that power Harvey's AI platform across multiple cloud regions - Own and evolve our multi-cloud infrastructure (Azure, GCP), including Kubernetes orchestration, networking, and container management - Lead technical initiatives around observability, incident response, and operational excellence — building systems that enable rapid detection and resolution of issues - Architect and optimize our distributed systems for reliability, including load balancing, quota management, and failover mechanisms - Partner with Product Engineering and Security teams to ensure our infrastructure is an accelerant, not a constraint - Drive infrastructure-as-code practices using tools like Terraform and Pulumi to enable reproducible, auditable deployments - Mentor engineers and raise the technical bar across the organization through code reviews, design reviews, and technical leadership REPRESENTATIVE PROJECTS - Design and implement a next-generation model proxy architecture that routes millions of daily inference requests while maintaining model API compatibility and enabling seamless model integration - Build distributed rate limiting and quota management systems using Redis-backed algorithms to handle bursty traffic patterns without degrading user experience - Architect multi-region deployment strategies that meet strict data residency requirements for global enterprise customers - Develop comprehensive observability infrastructure with granular SLA monitoring, burn rate alerts, and detailed token attribution for cost tracking - Lead the evolution of our CI/CD pipelines to improve developer velocity while maintaining production stability WHAT YOU HAVE - 10+ years of experience in Infrastructure Engineering or Platform Engineering in a production environment - Long track record building and scaling complex, large-scale distributed systems - Deep proficiency with cloud infrastructure platforms (Azure preferred; GCP or AWS experience transfers well) - Strong fluency in Infrastructure as Code (IaC) tools — Terraform, Pulumi, or CloudFormation - Solid understanding of Kubernetes, container orchestration, networking, and cloud security at scale - Experience with observability tools (Datadog, Sentry) and incident response practices (PagerDuty, Incident.io http://Incident.io) - Strong programming skills in Python, Go, or similar languages - Excellent problem-solving skills, a "spidey sense" of where things could go wrong, and a commitment to operational excellence NICE TO HAVE - Experience building infrastructure for AI/ML workloads or high-throughput inference systems - Background with distributed rate limiting, load balancing, or quota management systems - Experience operating multi-tenant platforms with strict security and compliance requirements - Track record of leading complex cross-functional projects and delivering measurable impact COMPENSATION RANGE $236,000 - $290,000 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-AN2 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: USA Company Intro At Toloka AI we create data that powers leading GenAI models and innovations. We work with frontier labs, big tech, renowned AI startups, enterprises and non-profit research organizations worldwide. We use a combination of Experts + Crowd + Tech Platform to teach AI models to reason and evaluate their efficacy and safety. We have experts in more than 50 different domains—from doctors and lawyers to physicists and engineers—and boast one of the most diverse global crowds, representing over 100 countries and speaking 40+ languages . We are a well-funded startup with an enviable portfolio of clients including Anthropic , Amazon , Microsoft , Poolside , Recraft ,  and Shopify . Recently, we secured strategic investment led by Bezos Expeditions and Nebius Group with participation from Mikhail Parakhin , CTO of Shopify and board advisor to leading GenAI companies, who now serves as our Chairman of the Board. Our remote-first team is globally distributed around the world: USA , UK , the Netherlands , Serbia , and more. About the Role Technical consultants play a key role in our company, ensuring top-level delivery of our product, its correct configuration, and the deployment of tailored AI data solutions that meet our customers’ needs and deliver an exceptional experience working with us. As part of this role, you will not only design and implement data labeling pipelines but also act as a trusted technical advisor for our customers - helping them understand their data needs, discover new opportunities, and build scalable AI solutions. We are looking for a person with more than 3 years of solid technical background, who feels comfortable working in technical environments, solving data-related tasks using Python and AI, and communicating directly with customers. You should be a confident communicator able to engage with both technical and executive stakeholders and collaborate closely with our commercial team. Responsibilities 1. Client Ownership & Communication Act as the primary technical point of contact for customers across technical and executive stakeholders. Lead discovery conversations to deeply understand client goals, problems and quality criteria. Translate client needs into clear, actionable solution designs and delivery plans. Advise customers on best practices in data collection, data quality, evaluation, and model training workflows. Set expectations proactively, communicate progress regularly, and manage risks and trade-offs transparently. Identify expansion opportunities and additional ways Toloka can create value through data and AI solutions. 2. Solution Design & Delivery Design end-to-end data solutions using Toloka’s platform, selecting appropriate components, workflows, and quality controls. Configure data labeling components and quality controls, develop user interfaces and AI-driven tooling (e.g. agentic systems, RAGs, synthetic data generation), and integrate them into end-to-end automated pipelines for AI training and evaluation. Run experiments and pilots to validate quality, throughput, and cost assumptions. Lead technical execution during delivery, coordinating internal teams and external stakeholders as needed. Ensure solutions meet agreed quality, performance, and scalability requirements. 3. End-to-End Ownership & Project Management Own delivery outcomes holistically - including technical performance, quality, timelines, and financial efficiency. Monitor key KPIs (e.g. throughput, quality metrics, Gross Margin, Contribution Margin) and act on deviations. Prioritize work based on customer impact and business value. Analyze data to identify failure modes, inefficiencies, and opportunities for improvement. Continuously optimize solutions through iteration, automation, and adoption of new technologies. Troubleshoot delivery, process, or technical issues in collaboration with support, infrastructure, and product teams. Drive solutions toward stable operation with minimal ongoing maintenance. Requirements Core Experience Experience as a Solution Engineer, Technical Solutions Engineer, Data Scientist, Data/Systems Analyst, or Technical Project Manager. Proven experience owning projects end-to-end, including scoping, delivery, and stakeholder management. Direct experience working with external customers on technical projects (requirements gathering, delivery, iteration). Technical Skills Strong Python skills for data manipulation (e.g. NumPy, pandas), natural language processing (e.g. NLTK, spaCy), and building lightweight web services or tools (e.g. FastAPI, Flask). Solid understanding of ML concepts and data workflows; familiarity with LLMs and prompt engineering is a strong plus. Experience designing multi-stage pipelines and complex systems. Understanding of software development fundamentals: version control, testing, MVPs, iterative development etc.. Bachelor’s or Master’s degree in Data Science, ML/AI, Software Engineering, or a related quantitative field such as Physics or Applied Mathematics, with strong analytical foundations. Ability to reason about trade-offs between quality, speed, cost, and scalability. Communication & Ownership Excellent English communication skills (B2+), with the ability to explain complex technical concepts to non-technical audiences. Confidence working with data engineers, ML engineers, and researchers from leading tech companies. Strong ownership mindset: comfortable being accountable for outcomes, not just tasks. Ability to manage multiple projects in fast-paced, ambiguous environments. Nice to have Experience with crowdsourcing, expert workflows, or large-scale data labeling. Experience working on ML training, evaluation, or agentic systems. Familiarity with quality frameworks, audits, or data validation pipelines. What we can offer Full-time independent contractor engagement (B2B) through the Ontop contractor platform , working via your own company or business entity; Flexible, fully remote schedule ( 40 hours per week ); Work at the leading edge of AI development, alongside a dedicated and dynamic team of experts; Projects with customers that are AI industry leaders and well-known household names; Friendly community. [Important Notice] Scam Alert Regarding Fake Job Postings It has come to our attention that an individual or group is fraudulently impersonating Toloka to post fake jobs and solicit personal information from applicants.Please be aware: Official Communication: Our recruiting team will only contact you from an official " toloka.ai " email address. We will NEVER use Gmail, Yahoo, Tolokainc, toloka.inc,  or other personal or seemingly business email accounts. Our Process: We will never ask for your bank account details, credit card number, or any fees as part of the application or interview process. Official Listings: All legitimate job openings are posted on our official careers page: https://toloka.ai/careers#job-list What to do: If you see a suspicious job posting or have been contacted by someone you suspect is a scammer, please do not provide any personal information. Instead, report the incident to us directly at security@toloka.ai and report the profile/post to LinkedIn.We are taking this matter very seriously and are working with the appropriate parties to resolve it. Thank you for your vigilance! To learn how we collect, use, disclose, and store personal data, check out our Privacy Notice .

Location: Philippines; South Africa; Mexico; Colombia; Argentina; Honduras About Huzzle At Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms in industries such as SaaS, MarTech, FinTech, and AI. Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team. Role Type: Full-time Engagement: Independent Contractor About the Company Our client is a fast-growing automation-focused company helping small and medium-sized businesses streamline operations using cutting-edge AI solutions. They specialize in deploying practical, results-driven automation systems powered by LLMs and workflow tools, while also building scalable internal infrastructure for long-term efficiency. Job Summary We’re hiring an AI Engineer to design, build, and deploy AI-powered automation workflows for real-world business use cases. This is a hands-on, execution-focused role where you’ll rapidly implement solutions using tools like n8n, Go High Level, and LLM APIs—while also contributing to the development of more scalable, in-house AI systems over time. If you’re looking for a remote AI engineering job that blends prompt engineering, automation, and system design, this role offers strong growth potential and meaningful impact. Key Responsibilities Build and deploy AI automation workflows using tools like n8n, Zapier, and Go High Level Integrate and optimize LLM APIs (OpenAI, Claude, etc.) for business use cases Quickly deliver functional automation systems for client requirements Design and improve internal AI infrastructure to reduce reliance on third-party tools Debug, test, and refine workflows for performance and reliability Collaborate with an operations/project manager to gather requirements and iterate on solutions Continuously explore new AI tools and frameworks to improve system capabilities Requirements Proven experience working with LLMs and AI APIs (e.g., OpenAI, Claude) Strong understanding of automation tools such as n8n, Zapier, Go High Level, or similar platforms Ability to balance rapid implementation with long-term system scalability Solid problem-solving skills with experience debugging workflows and integrations Experience connecting APIs, webhooks, and third-party tools Clear and professional English communication skills Bonus: Experience with Python, backend systems, or building custom AI pipelines (e.g., RAG systems) Benefits 💰 Competitive salary based on experience and location 🌎 Fully remote role with flexible work environment 🚀 Work on cutting-edge AI automation projects with real business impact 📈 Strong growth opportunity into senior AI / systems roles 🧠 Exposure to LLMs, prompt engineering, and scalable AI system design 🤝 Direct collaboration with a fast-moving, high-performance team

Location: Ukraine; Poland; Spain; Romania; Portugal About Us At SPD Technology, we bring together a team of like-minded people who are driven by the desire to bring value through their work, united in their commitment to high performance and delivering custom, cutting-edge tech solutions that drive clients’ growth. We empower our people with a culture of excellence and enable them with the opportunity to uphold their accountability to contribute on each level. We value humanity and collaboration, encourage professional and personal growth, and foster a supportive and flexible work environment where everyone’s contribution is welcomed. And now we are looking for a Senior Engineering Manager to join us as part of our team. About the role PitchBook — a platform for investment professionals. Our software provides access to data and the analytical tools to get answers fast and discover promising opportunities. Uncovers actionable insights and trends hidden within the financial data of more than three million companies. Users all over the world include large corporations, start-ups, venture capital and private equity firms, investment banks, and many others. As a member of the Product and Engineering team at PitchBook, you will be part of a group of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation. As a Senior Engineering Manager in the Technology & Engineering division, you will be responsible for managing and growing several self-organized engineering teams, driving delivery excellence, and representing development direction at a strategic level. You will collaborate closely with engineering leads, product managers, and senior stakeholders to ensure alignment, performance, and team success. Tech Stack: Java, Python, TS/JS/React, GCP, Vertex AI, AWS, Bedrock etc Team setup: 2-5 teams Work Environment: ​​flexible As a qualified expert You will Manage and grow multiple engineering teams and their leaders within a business unit or product area. Cultivate technical excellence and a culture of continuous learning across teams. Participate in and supervise discussions on key technical decisions, delivery expectations, and people allocation. Represent the development direction at the strategic (VP) level, including plans, results, metrics, and capabilities. Drive AI tool adoption to improve team efficiency and delivery speed. Encourage learning through AI-assisted development and automation. Coach teams on best practices for software delivery, estimation, stakeholder communication, and continuous improvement. Ensure clear goals, priorities, and resource allocation while maintaining technical excellence and innovation. Foster a culture of trust, transparency, collaboration, and constructive feedback. Maintain high morale and motivation, especially during challenging circumstances. Balance business, team, and individual needs through effective communication and decision-making. Recognize team achievements and help teams learn from challenges or failures. Manage staffing, including hiring new team members aligned with company values and culture. Monitor and assess team performance, conduct performance reviews, and ensure fair compensation processes. Support the adoption of DevOps practices and modern engineering methodologies. We’re looking for you if you have Mature understanding of the manager’s role, with a strong product- and results-oriented mindset, demonstrating strong ownership and focus on delivering outcomes. 7+ years of hands-on experience in software development, primarily with the Java stack. 3+ years of experience managing one or more engineering teams (25+ individuals) in a modern software development environment. Strong understanding of modern software development processes, frameworks, and their practical trade-offs. Knowledge of contemporary software engineering technologies and their applications to real-world problems. Understanding of AI tools, prompting, and workflow automation in software engineering. Ability to assess AI outputs and apply them to improve efficiency and quality. Familiarity with DevOps culture and practices. Strong interpersonal skills combining empathy, business acumen, and the ability to set expectations and provide feedback. Open-mindedness, willingness to learn, and courage to make progress-driving decisions. Excellent written and verbal communication skills in English. Bonus points Experience leading the development of complex, distributed software systems requiring deep domain or technical expertise. Experience with Agile or other value-stream-based framework transformations. Proven success in building high-performing software development teams from the ground up. Experience managing teams using metrics related to motivation, performance, and time. What’s in it for You Reveal great tech solutions Join the team of experts who create custom, cutting-edge tech solutions for world-renowned businesses, fueling clients growth. Unleash your potential, tackle new challenges, and be part of a team that values your skills and contributions. Focus on long-term impact and building tailored, long-lasting partnerships with our clients. Experience an agile and flexible working environment Work fully remote around the globe, or in a hybrid work model from our office hubs which are equipped with everything needed for comfortable work. Enjoy a flexible working schedule and create work and rest balance for yourself. Empower yourself with a stable workload and a stable income, focusing on lasting cooperation and high-performance culture. Embrace the opportunity for personal and professional growth Take advantage of performance review and career path. Elevate your skills with mentorship program, personal development plan, and individual learnings through the corporate library, public speaking support, and more. Feel cared about Be among like-minded people and feel supported with collaboration, open communication and mutual respect. Join company-wide tech and cultural events, and contribute to meaningful CSR initiatives that resonate with your values. Interview steps Interview with the recruiter Manager screening Tech Interview HR Interview Interview with Managing Director Product Interview (Client) Interview with VP, Technology & Engineering (Client)

Location: South Africa; Philippines; Pakistan; Argentina; Mexico; Colombia About Huzzle At Huzzle, we connect exceptional talent with top opportunities at leading companies across the UK, US, Canada, Europe & Australia. Unlike an outsourcing agency, we place you directly with a client where you're hired in-house to work as a valued member of their team. Please note that by applying & completing our interview process, you will be added to our community. This means you’ll be considered for this and all other possible roles that may match your skills. These potential opportunities will be sent your way as an exclusive Huzzle candidate. Job Type: Full-time Location: Remote Start Date : Immediate About the Company Our client is an innovative AI-driven company focused on building and deploying “AI employees” that automate business workflows and enhance operational efficiency. They specialize in integrating cutting-edge automation tools and large language models (LLMs) to streamline client operations across multiple industries. Job Summary We are seeking a highly skilled Technical Project Manager with hands-on experience in workflow automation and AI/LLM integrations. This role is ideal for someone who can bridge technical execution and business strategy—leading projects that involve tools like n8n, Zapier, and AI platforms such as OpenAI, Gemini, and Claude. You will manage end-to-end delivery of automation and AI-driven initiatives, working closely with developers, stakeholders, and cross-functional teams to ensure projects are delivered on time, within scope, and aligned with business objectives. Key Responsibilities Lead and manage technical projects focused on automation and AI implementation Design and oversee workflows using tools like n8n, Zapier, Make (Integromat), or similar platforms Coordinate the integration of LLM APIs (e.g., OpenAI, Gemini, Claude) into business processes Collaborate with engineering, product, and operations teams to define project scope and deliverables Translate business requirements into technical specifications and actionable tasks Monitor project timelines, budgets, and performance metrics Identify risks, troubleshoot issues, and ensure smooth project execution Optimize workflows and processes for scalability and efficiency Maintain clear communication with stakeholders and provide regular updates Requirements 3+ years of experience as a Technical Project Manager or similar role Proven experience with automation tools (n8n, Zapier, Make, etc.) Hands-on experience working with LLMs and AI tools (OpenAI, Gemini, Claude, or similar) Strong understanding of APIs, integrations, and system architecture Experience managing remote technical teams and cross-functional stakeholders Familiarity with Agile, Scrum, or other project management methodologies Excellent problem-solving, communication, and organizational skills Ability to balance technical depth with business impact Background in SaaS, AI startups, or automation-focused environments Experience with prompt engineering and AI workflow design Basic coding knowledge (Python, JavaScript, or similar) Experience with CRM systems and data pipelines Benefits 💻 Fully Remote: Work from anywhere with international teams 🚀 Career Growth: Join companies in SaaS, MarTech, and B2B services 🤝 Peer Community: Connect with high-performing sales professionals in our network 🧭 Ongoing Support: Receive guidance from Huzzle before and after placement 💰 Tailored Compensation: Salaries vary by client and candidate preference — we’ll match you with options that fit your goals

Location: China (Remote); Taiwan (Remote) Workplace: Remote ABOUT THE OPPORTUNITY We are building a rigorous, verifiable evaluation suite of Terminal-Bench tasks designed to test the limits of large language models on multilingual software challenges. Our goal is to measure multilingual robustness across prompt language effects, non-English data processing, and complex locale/encoding edge cases in terminal workflows. We are seeking experienced native-speaking software engineers to design, build, and validate these benchmarks. You will create high-signal, high-quality tasks that genuinely test a model's ability to handle multilingual environments without relying on English translation crutches. Note this is a remote, freelance opportunity WHAT YOU’LL DELIVER - Task Engineering: Evaluating Coding Agents. - Asset Creation: Build realistic task environments using datasets and files in your native language. Crucially, these assets must remain in the target language to genuinely measure multilingual handling. - Prompting & Translation: finding failure points where AI does not work, in your native language - Implementation & Verification: Support the development of robust solutions (reference implementations) and write highly reliable, deterministic verifier scripts (using rubric-based judging only when strictly necessary). - Calibration & Execution: Analyze execution logs and calibrate task difficulty (Easy to Very Hard) using standard Terminal-Bench run configurations against various model tiers (Haiku, Sonnet, Opus). - Quality Assurance: Participate in a rigorous, 4-layer human quality control process (creation, human review, calibration review, and audit) alongside automated LLM-based checks to ensure fairness, grammatical accuracy, and benchmark integrity. QUALIFICATIONS - Experience: 1+ years of industry experience in software engineering. - Background: Proven track record at leading technology companies and/or graduation from top-tier engineering universities. - Language: Native or near-native fluency, with a deep understanding of its grammar, register, and phrasing rules. High English proficiency. - Technical Stack: Strong proficiency in Python, standard shell scripting, and data processing. - Workflow: Extensive experience with Terminal/CLI-based development workflows and a working familiarity with coding agents. - Domain Expertise: Deep technical understanding of multilingual text processing pitfalls, including: - Encoding/decoding robustness and Unicode normalization. - Locale-dependent conventions (collation, casing, non-Gregorian dates). - Text I/O, toolchain interoperability, and safe string operations. - (For specific languages) Bidirectional/RTL handling, font fallbacks, and rendering/typography in UI or artifacts. WHY COLLABORATE WITH LILT? - Your schedule, your rules. As an independent contractor, work when you want, as much or as little as you want. No fixed hours, no check-ins, no micromanaging. - Get paid quickly and fairly. We respect your time and your expertise. Competitive rates, prompt payments, no chasing invoices. - Work on projects that actually matter. Contribute to cutting-edge AI and language technology that is shaping how humans and machines communicate. - Be part of something bigger. Join a global community of linguists, subject matter experts, and language professionals who are advancing human knowledge together. - Grow without limits. As a Lilt contractor you get access to diverse, innovative projects that expand your portfolio and sharpen your skills across industries and domains. - Have fun doing what you love. Bring your language skills to life on projects that are as interesting as they are impactful.We are building a rigorous, verifiable evaluation suite of Terminal-Bench tasks designed to test the limits of large language models on multilingual software challenges. Our goal is to measure multilingual robustness across prompt language effects, non-English data processing, and complex locale/encoding edge cases in terminal workflows. WHAT TO CONSIDER BEFORE APPLYING - Not ideal as a full time job or primary income source. Work availability fluctuates with project demand, making this better suited as a supplemental income stream. As a 1099 contractor, you won't receive benefits such as health insurance, paid time off, or retirement contributions, and hours are not guaranteed. - Requires reliable availability and commitment. Once you accept a task, we expect quality work and on-time delivery. Most tasks require a minimum of 2 hours per day or 15-20 hours per week. If your schedule is unpredictable, this may not be the right fit. - Geographic restrictions may apply. We cannot engage contractors in regions subject to international embargo or sanctions. As a 1099 contractor, you are solely responsible for your own tax obligations. We recommend consulting a tax professional before engaging. HOW TO JOIN OUR EXPERT COMMUNITY 1 - Submit your application including an updated copy of your CV in English 2 - Next, complete a GenAI assessment to evaluate your skills 3 - Finalize onboarding and profile set-up in our system, and become eligible for Applied AI projects. AI is changing how the world communicates — and LILT is leading that transformation. LILT's mission is to make the world's information available to everyone, no matter the language they speak. Join our global community who thrive on innovation and excellence. Our collective knowledge, uniqueness, and skills deliver multilingual AI and human-verified services to Enterprises, Governments, and AI Developers around the world. Earn money. Have fun. Advance human knowledge. Work on diverse projects from anywhere, any time you want. Get paid quickly and fairly, and build your professional network in a supportive community—all through a streamlined application process tailored to your expertise. Information collected and processed as part of your application process, including any job applications you choose to submit, is subject to LILT's Privacy Policy at https://lilt.com/legal/privacy. At LILT, we are committed to a fair, inclusive, and transparent hiring process. As part of our recruitment efforts, we may use artificial intelligence (AI) and automated tools to assist in the evaluation of applications, including résumé screening, assessment scoring, and interview analysis. These tools are designed to support human decision-making and help us identify qualified candidates efficiently and objectively. All final hiring decisions are made by people. If you have any concerns, require accommodations, or would like to opt-out of the use of AI in our hiring process, please let us know at recruiting@lilt.com. LILT is an equal opportunity employer. We extend equal opportunity to all individuals without regard to an individual’s race, religion, color, national origin, ancestry, sex, sexual orientation, gender identity, age, physical or mental disability, medical condition, genetic characteristics, veteran or marital status, pregnancy, or any other classification protected by applicable local, state or federal laws. We are committed to the principles of fair employment and the elimination of all discriminatory practices.

Location: London, UK; Oslo, Norway Workplace: Hybrid We're hiring a senior engineer for Agent Foundations, the team responsible for how agents work with structured content at Sanity. We own two products. Content Agent https://www.sanity.io/content-agent runs content operations (bulk edits, audits, translation, publishing) through conversation in Sanity Dashboard, Slack, Linear and a headless API. Sanity Context https://www.sanity.io/context (including Knowledge Bases https://www.sanity.io/docs/ai/sanity-context-knowledge-bases) is an MCP endpoint that gives any agent structured retrieval and semantic search over a team's live content, whether it be Sanity Documents or your own federated content from outside Sanity. We're looking for someone who's built AI systems people can depend on in production. At Sanity.io http://Sanity.io, we build an AI-powered content operating system that lets teams model, create, and automate content the way their business actually runs. SKIMS, Figma, Riot Games, Anthropic, COMPLEX, Nordstrom, and Morningbrew run their content operations on it. Most AI products add a model to a content store. We work on what sits underneath. We build knowledge bases from Sanity datasets https://www.sanity.io/content-lake and external sources, and retrieval that combines GROQ filters with keyword and embedding search. Our agents need to understand schemas, references and validation rules. Telemetry and evals tell us how well the systems work. You'll work across these systems, owning your domain end to end and working closely with product and design to decide what gets built next. WHAT YOU'D BE DOING: - Build retrieval and knowledge bases. Turn sources into documents and chunks. Develop how knowledge bases are created, kept fresh and scoped, and how agents query them using GROQ, keyword and semantic search together. - MCP endpoints and tools give agents their interface to our systems. You'll build these, along with tools and integrations that extend Content Agent. - Work on agent loops. Write the orchestration logic that controls an agent's actions and their order, including when to bring a human in. - Engineer system prompts. Give agent instructions the same engineering attention as the code around them. - Measure and improve reliability, retrieval quality and cost through evals, telemetry and experiments. We measure it in production as well as on test sets. - Ship across the stack. Build interfaces in Dashboard and Studio, APIs and backend services. Work on Blueprints, the infrastructure-as-code path customers use to define their agents and knowledge. - Help shape the products. Sanity Context is new and changing quickly. You'll have considerable latitude to decide what it and Content Agent become. ABOUT YOU: - Location: London, UK or Oslo, Norway (in-office 2–3 days/week) - You're strong in TypeScript and React and comfortable working across frontend, APIs and backend (often in Go). - You've shipped LLM-based systems in production and understand the work it takes to make them behave reliably for every user. - You understand chunking, embeddings, hybrid search and ranking, including where RAG falls short. Experience with search or information retrieval is a strong plus. - You think through a capability's user intent, edge cases, failure modes and cost before deciding on the architecture. That includes what the agent needs to know, which tools it can use and when it should escalate. - You write well and pay attention to how phrasing changes an agent's behavior. You can write precise instructions for a system that interprets language literally. - You're comfortable working with probabilistic systems. You design evals, run experiments and interpret results statistically, using aggregate trends to decide which failures need attention. - You have experience with MCP, tool-use patterns and agent architectures, or you're curious enough to explore them. - You care about the quality of the code and products you ship, down to the writing. You don't need to meet every requirement to apply. We're especially interested in people who've developed engineering skills after starting in fields such as writing, interaction design or liberal arts. Some of the best agent work we've seen comes from people who understand language and how people work, alongside systems architecture. WHAT WE CAN OFFER: - A highly-skilled, inspiring, and supportive team - Positive, flexible, and trust-based work environment that encourages long-term professional and personal growth - A global, multi-culturally diverse group of colleagues and customers - Comprehensive health plans and perks - A healthy work-life balance that accommodates individual and family needs - Competitive stock options program and location-based salary WHO WE ARE: Sanity.io http://Sanity.io is a modern, flexible content operating system that replaces rigid legacy content management systems. One of our big differentiators is treating content as data so that it can be stored in a single source of truth, but seamlessly adapted and personalized for any channel without extra effort. Forward-thinking companies choose Sanity because they can create tailored content authoring experiences, customized workflows, and content models that reflect their business. Sanity recently raised an $85m Series C led by GP Bullhound and is also backed by leading investors like ICONIQ Growth, Threshold Ventures, Heavybit and Shopify, as well as founders of companies like Vercel, WPEngine, Twitter, Mux, Netlify and Heroku. This funding round has put Sanity in a strong position for accelerated growth in the coming years. You can only build a great company with a great culture. Sanity is a 300+ person company with highly committed and ambitious people. We are pioneers, we exist for our customers, we are hel ved, and we love type two fun! Read more about our values here! https://www.sanity.io/blog/our-sanity-values Sanity.io pledges to be an organization that reflects the globally diverse audience that our product serves. We believe that, in addition to hiring the best talent, a diversity of perspectives, ideas, and cultures leads to the creation of better products and services. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, or gender identity.

Location: Georgia Solvd Inc. is a rapidly growing AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence. We work with industry-leading organizations to design, build, and operationalize technology solutions that drive measurable business outcomes. Following the acquisition of Tooploox, a premier AI and product development company, Solvd now offers true end-to-end delivery—from strategic advisory and solution design to custom AI development and enterprise-scale implementation. Our capability centers combine deep technical expertise, proven delivery methodologies, and sector-specific knowledge to address complex business challenges quickly and effectively. We are seeking a dynamic and motivated Senior AI NodeJS Engineer with a strong focus on developing AI Agents. If you have an understanding of AI technologies and thrive on applying diverse tech stacks to build innovative solutions, we want to hear from you. This role involves not only technical expertise but also collaboration with clients to understand and refine project requirements. WHAT YOU WILL DO - Collaborate with cross-functional teams to design and build AI Agentic solutions. - Contribute to defining technical requirements and implementing features across the software lifecycle - from proof of concept through implementation to evaluation and production. - Take ownership of assigned tasks and deliver high-quality, maintainable code. - Manage backend tasks while contributing to frontend development. - Stay informed about trends and advancements in AI and related fields, continuously learning and integrating new knowledge. - Employ a pragmatic, evaluation-driven approach to adopting innovative AI solutions. EXPERIENCE AND SKILLS YOU NEED TO JOIN US - Experience in full-stack development using mainly NodeJS (with TypeScript). - At least 1 year of experience in AI Engineering role. - Versatile in technology use, comfortable working across backend and frontend tasks. - Track record in staying current with AI and Agentic technologies, including best practices and architecture. - Openness to client collaboration, fostering clear communication and effective partnership. - Strong commitment to learning new technologies and swiftly adapting to new products and APIs. - Understanding of Retrieval-Augmented Generation (RAG) and its applications. - Familiarity with Multi-Agents concept, tools usage and MCP Servers. - Hands-on experience with LLM APIs/SDKs (e.g., OpenAI, Anthropic). - Knowledge of LLM orchestration and frameworks like Langchain or LlamaIndex, with practical implementation experience. - Understanding of prompt design principles and an ability to create effective prompts. - Experience configuring services on cloud platforms (e.g. AWS, Azure, GCP). - Basic experience with CI/CD pipelines and DevOps best practices. - Competence in REST API usage and efficient database integration. - Fluency in English language. IT WOULD BE GREAT IF YOU ALSO HAVE - Basic knowledge of machine learning principles. - Understanding Python source code. - Experience with React. - Experience with model fine-tuning and distillation. - Familiarity with LLM evaluation. - Experience with Model Context Protocol (MCP). - Experience with graph databases. - Familiarity with other programming languages and frameworks. - Familiarity with Voice Agents concepts and related frameworks e.g. Pipecat. When you join Solvd, you'll… - Shape real-world AI-driven projects across key industries, working with clients from startup innovation to enterprise transformation. - Be part of a global team with equal opportunities for collaboration across continents and cultures. - Thrive in an inclusive environment that prioritizes continuous learning, innovation, and ethical AI standards. Ready to make an impact? If you're excited to build things that matter, champion responsible AI, and grow with some of the industry’s sharpest minds. Apply today and let’s innovate together. Solvd is an equal opportunity employer.

Location: Remote Team: Revenue Operations Reports to: Chief Revenue Officer Location: Remote Type: Full-time The Role You'll be Product Owner across three surfaces : CRM — platform, data model, permissions, lifecycle automation. Partner Product — the cabinet, dashboards, payout logic, and tooling our IBs, affiliates, and KOLs live in. Marketing Enablement — lifecycle stack, AI agents, and the internal tools BD/AM run on. You own the roadmap, backlog, specs, and outcomes with a simple goal in view - to grow revenue. We want a disruptor. Someone who sees a 14-step nurture sequence and asks why an agent isn't running it. Someone comfortable in a product review with engineers and a funnel economics conversation with the CEO. What You'll Do 🛠 CRM Lead the new CRM rollout and adoption across BD, Partnerships, AM, Marketing, Compliance, Support. Own the data model, permissions, and the pipe from platform → warehouse → CRM → activation. Partner Product Own the IB/affiliate/KOL product experience end-to-end. Translate partner and BD feedback into a prioritised backlog; ship with engineering. Build the partner journeys, onboarding, activation, tiering, qualification that turn signups into revenue. Revenue org Enablement & AI Ship AI auto-funnels: agents that score, personalise, route, draft, and hand off. Embed AI into daily BD/AM work: prospect intelligence, meeting prep, auto-logged notes, next-best-action, call QA. Support Acquisition and Retention teams with setting up funnels across email, in-app, SMS, push. Always Test, measure, kill what doesn't work. Report ROI clearly. Iterate. What We're Looking For 🪄 Must-haves Product ownership experience with a track record. Experience in CRM integration/management (Salesforce, HubSpot, Zoho, Zendesk, Customer.io, Braze, or similar). Experience in shipping funnels that actually convert. Hands-on with AI in a revenue context : LLM APIs, agents, prompt engineering, AI-powered outbound. Strong with Dev, Data, Marketing, Sales. Translates well between them. Analytical. Reads cohorts and retention curves, not just reports. Bonus points for Owning a partner/IB/affiliate product before. Shipped AI agents on top of a CRM (scoring, outreach, research, QA). Tools: n8n, Make, Zapier Agents, Clay, Apollo, Smartlead, HeyReach, Retell, Bland. Fintech, crypto, brokerage, iGaming, or other regulated, affiliate-heavy verticals. RAG, vector DBs, internal knowledge agents. A portfolio that shows what you've built , not just where you've worked.

Location: Morocco We are looking to hire passionate Senior AI Engineers to help turn data into intelligent, production-ready solutions. You will work across the full AI stack: traditional machine-learning models, large language models (LLMs), computer-vision pipelines, and analytics / forecasting workflows. If you enjoy exploring data, building state-of-the-art models, and shipping reliable AI services, we would love to meet you. Responsibilities Model Development – Design, train, fine-tune, and evaluate models spanning classical ML, deep learning (CNNs, transformers), and generative AI (LLMs, diffusion). Data Exploration & Analytics – Conduct exploratory data analysis, statistical testing, and time-series / forecasting to inform features, prompts, and business KPIs. End-to-End Pipelines – Build reproducible workflows for data ingestion, feature engineering / prompt stores, training, CI/CD, and automated monitoring. LLM & Agentic AI Engineering – Craft prompts, retrieval-augmented generation (RAG) pipelines, and autonomous/assistive agents; fine-tune LLMs on domain-specific datasets to boost accuracy and align outputs with product requirements. AI Automation & Integration – Expose AI components as micro-services and event-driven workflows; integrate with orchestration tools (Airflow, Prefect) and business APIs to automate decision pipelines. Continuous Learning – Track advances in LLMs, vision, and analytics; share insights and best practices with the wider engineering team. Mentor junior engineers and contribute to technical direction and engineering best practices. Requirements BSc in Computer Science, Mathematics, or related field. 5+ years of professional experience working on AI/ML projects. Good command of English and Arabic (written and spoken). Proficient in Python and core libraries (PyTorch / TensorFlow, scikit-learn, pandas, NumPy). Solid understanding of machine-learning algorithms, deep-learning fundamentals, and basic statistics. Experience with data wrangling and visualization (Matplotlib / Plotly) and exploratory analysis. Familiarity with at least one of: OpenCV, Hugging Face Transformers, LangChain, MLflow, or similar. Good grasp of software-engineering best practices: Git, code reviews, testing, CI. Preferred Qualifications Knowledge of C++ or C# for performance-critical modules. Experience deploying models via Docker, Kubernetes, or cloud AI services. Exposure to vector databases and RAG workflows. Skill in BI / dashboard tools (Power BI, Tableau, Streamlit) or time-series frameworks (Prophet, statsmodels). Familiarity with MLOps / LLMOps tooling (DVC, MLflow Tracking, Weights & Biases, BentoML). Experience with image processing techniques (e.g., OpenCV, image segmentation, feature extraction) Experience with Spark (PySpark) and distributed data processing, including usage of platforms such as Databricks, AWS EMR, or GCP Dataproc. Strong SQL skills and experience working with large-scale datasets, including partitioning and performance tuning. Familiarity with modern data lake architectures and scalable data storage concepts.

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: At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious Generative AI Specialist to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Own: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. Labeling elements of a piece of content rather than the content as a whole. Assigning predefined categories or labels to items. Evaluating the perceived quality and/or appropriateness of content Generating labels to advance understanding of a concept, trend etc. Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. Ordering or ranking items based on a set of preferences or criteria. Creating prompts or questions that will be used to generate responses from a language model or other AI system. Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). Generating responses to prompts or questions using a language model or other AI system. Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. Producing concise summaries of longer pieces of text or data. Converting spoken language or audio content into written text. Converting text or spoken language from one language to another. Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. You’ll Thrive in This Role If You Have: A Bachelor’s degree or higher in a humanities specialization is required. Advanced degrees are strongly preferred (Master’s or PhD) Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for this position is $15 p/hour, 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 - Canada 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: At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious Generative AI Specialist to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Own: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. Labeling elements of a piece of content rather than the content as a whole. Assigning predefined categories or labels to items. Evaluating the perceived quality and/or appropriateness of content Generating labels to advance understanding of a concept, trend etc. Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. Ordering or ranking items based on a set of preferences or criteria. Creating prompts or questions that will be used to generate responses from a language model or other AI system. Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). Generating responses to prompts or questions using a language model or other AI system. Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. Producing concise summaries of longer pieces of text or data. Converting spoken language or audio content into written text. Converting text or spoken language from one language to another. Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. You’ll Thrive in This Role If You Have: A Bachelor’s degree or higher in a humanities specialization is required. Advanced degrees are strongly preferred (Master’s or PhD) Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for this position is $21 CAD p/hour, 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 .

Задачи: — Участие в разработке и деплое ML/LLM решений. — Применение Prompt Engineering и методов Fine-tuning/PEFT. — Построение RAG пайплайнов и работа с векторными базами данных. — Оптимизация производительности LLM и оценка их качества. — Разработка с использованием мультимодальных моделей. Требования: — Уверенное владение Python. — Опыт деплоя ML/LLM решений с использованием Docker, Kubernetes, облачных платформ AWS, GCP, Azure. — Опыт работы с Prompt Engineering (few-shot, chain-of-thought, ReAct). — Знание Fine-tuning / PEFT (LoRA, QLoRA, adapters). — Опыт построения RAG пайплайнов (chunking → embedding → retrieval → генерация). — Умение работать с векторными базами данных (Qdrant, Pinecone, Milvus, FAISS). — Опыт RLHF или работы с синтетическими данными (предпочтения, генерация и фильтрация). — Знание фреймворков LangChain, LlamaIndex, Hugging Face. — Опыт оценки LLM (BLEU, ROUGE, MMLU, кастомные эвалы). — Опыт оптимизации инференса (vLLM, TensorRT, ONNX). — Опыт работы с мультимодальными моделями (LLaVA, GPT-4V, Qwen-VL). — Грейд Middle/Middle+. Условия: — Полная занятость. — Удалённый формат работы. — Интересные проекты в области ИИ.

Location: San Francisco; Palo Alto Workplace: Hybrid Perplexity serves tens of millions of users daily with reliable, high-quality answers grounded in an LLM-first search engine and specialized data sources. The Answer Quality team ensures that our prompts, tools, search systems, datasets, and models work together to create the best possible experience for our users. As our product and agent capabilities evolve, we need evaluation systems that are fast, reliable, production-faithful, and actionable. In this role, you will build and improve the technical foundations that support Answer Quality across Perplexity. This includes our shared evaluation infrastructure and the platform used to replay and analyze agent traces. You will work closely with data scientists, engineers, and product teams to identify quality problems, measure their impact, and turn evaluation findings into product improvements. RESPONSIBILITIES - Build shared evaluation infrastructure that helps teams run reliable evals, analyze results, and make product and model decisions - Develop the platform for replaying and analyzing agent traces to reproduce production behavior and diagnose failures - Build and operate scalable systems for processing, storing, and monitoring interaction, trace, and evaluation data - Partner with data scientists, engineers, and product teams to turn answer-quality problems into evaluations, analyses, and product improvements - Operate in a small, high-impact team where your work directly shapes how Perplexity measures and improves Answer Quality QUALIFICATIONS - 4+ years of software, data, or machine learning engineering experience shipping and operating production systems - Strong proficiency in Python and SQL, with solid fundamentals in system design, data modeling, and distributed systems - Experience building big-data systems, including distributed compute, large-scale storage, and high-volume pipelines - Demonstrated ownership of ambiguous technical projects from initial design through production operation - Ability to work effectively with data scientists, engineers, and product partners PREFERRED QUALIFICATIONS - Experience building evaluation, experimentation, observability, or machine learning infrastructure - Familiarity with LLM and agent systems, including tool use, execution traces, replay, and simulation - Experience building on top of large-scale data processing platforms such as Databricks, Snowflake, or ClickHouse

Location: San Francisco; Palo Alto Workplace: Hybrid Perplexity serves tens of millions of users daily with reliable, high-quality answers grounded in an LLM-first search engine and specialized data sources. The Answer Quality team ensures that our prompts, tools, search systems, datasets, and models work together to create the best possible experience for our users. As our product and agent capabilities evolve, we need evaluation systems that are fast, reliable, production-faithful, and actionable. In this role, you will build and improve the technical foundations that support Answer Quality across Perplexity. This includes our shared evaluation infrastructure and the platform used to replay and analyze agent traces. You will work closely with data scientists, engineers, and product teams to identify quality problems, measure their impact, and turn evaluation findings into product improvements. RESPONSIBILITIES - Build shared evaluation infrastructure that helps teams run reliable evals, analyze results, and make product and model decisions - Develop the platform for replaying and analyzing agent traces to reproduce production behavior and diagnose failures - Build and operate scalable systems for processing, storing, and monitoring interaction, trace, and evaluation data - Partner with data scientists, engineers, and product teams to turn answer-quality problems into evaluations, analyses, and product improvements - Operate in a small, high-impact team where your work directly shapes how Perplexity measures and improves Answer Quality QUALIFICATIONS - 4+ years of software, data, or machine learning engineering experience shipping and operating production systems - Strong proficiency in Python and SQL, with solid fundamentals in system design, data modeling, and distributed systems - Experience building big-data systems, including distributed compute, large-scale storage, and high-volume pipelines - Demonstrated ownership of ambiguous technical projects from initial design through production operation - Ability to work effectively with data scientists, engineers, and product partners PREFERRED QUALIFICATIONS - Experience building evaluation, experimentation, observability, or machine learning infrastructure - Familiarity with LLM and agent systems, including tool use, execution traces, replay, and simulation - Experience building on top of large-scale data processing platforms such as Databricks, Snowflake, or ClickHouse

Location: Sydney Workplace: Hybrid ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Sierra was co-founded by Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/ who first met while working together at Google over 20 years ago. Bret currently serves as Chairman of the Board of Open AI. Previously, he was co-CEO of Salesforce and CTO of Facebook. Clay spent 18 years at Google, where he most recently led Google Labs. WHAT YOU’LL DO - Design and deliver production-grade AI agents https://sierra.ai/blog/meet-the-ai-agent-engineer: You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth. These aren't prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce. - Drive the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way. - Partner with large enterprises and cutting-edge startups: You’ll work directly with leaders at some of the world’s largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You'll also partner with the most cutting-edge startups, embedding AI agents across their entire business stack to drive innovation and efficiency. - Build the future of the platform: Your direct work with customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra's product. EXAMPLE PROJECTS These are some examples of projects that engineers on our team have worked on recently: - Design and build AI agents for large telecommunications and media companies that consistently outperform human agents in managing subscription churn - Develop and refine AI agents capable of navigating complex customer interactions, like troubleshooting a broken device and personalizing product recommendations - Create generalizable AI agent frameworks tailored for industry-specific use cases. See some examples in our financial services blog https://sierra.ai/blog/five-ways-to-use-ai-agents-financial-services! - Facilitate design partnerships for new product initiatives, such as new agent architectures, self-service capabilities, and generative agent development - Experiment with the latest voice models and figure out how to integrate them at scale to enterprise-grade customers WHAT YOU'LL BRING - Experience building and scaling end-to-end production systems - Strong technical problem-solving skills, especially in fast-changing, ambiguous environments - A builder and tinkerer’s mindset with high agency - you find creative ways to overcome obstacles and ship - Comfort working directly with customers to understand their needs and solve real-world problems - Excellent communication skills - clear, direct, and persuasive across technical and non-technical audiences EVEN BETTER... - Experience building or deploying AI/LLM systems in production - Have been a founder or founding engineer - you know what it means to balance craft, ownership, and speed - Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering - Prior experience with React, TypeScript, and/or Go - Previous roles where you interfaced with customers or led technical projects with external stakeholders OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits - Lunch, as well as delicious snacks and coffee to keep you energized when working onsite - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region and employment type, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. 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Location: Japan; Remote; Singapore About the role We are seeking a hands-on Security Engineer who thrives in a startup environment. You'll work alongside product owners and engineers with the objective to secure the products in Startale's ecosystem. Products include a next-generation decentralized exchange with a fully on-chain order book (Strium), a user-facing application (StartaleApp) and a stablecoin (USDSC). This is a hands-on, technical role . You'll be the person who actively tests our systems, hunts for vulnerabilities, models threats against our products, and works with engineers to close the gaps — not the person who writes policies and generates reports. You'll report to the Security Lead and collaborate daily with Backend, Frontend, DevOps, and Blockchain engineering teams. Why this role Startale's products handle user funds and on-chain transactions so security work has tangible impact. Owning the security posture of a project at scale and complexity such as Strium is an opportunity for professional growth. You will have direct influence over how product security is built across the organization. Focus is on driving product security and not on maintaining compliance documentation. Our team is backed by and partnering with leading Japanese enterprises so you will have a chance to work in a stable and well-funded company but with the autonomy and speed of a small team. Key responsibilities Security Assessments & Penetration Testing : Conduct hands-on security testing of our applications, APIs, and infrastructure. Simulate real attack scenarios against our products. Find the vulnerabilities before external attackers or whitehat researchers do. Work with engineers to fix issues pragmatically. Threat Modeling : Build threat models for new services and features — especially Strium's trading engine, order book, and transaction flows. Identify attack surfaces, model adversary behavior, and define what needs to be hardened before launch. Vulnerability Triage & Remediation : Own the end-to-end lifecycle of findings — from discovery through severity assessment, developer-facing write-ups, remediation guidance, and verification of fixes. Coordinate with engineers so issues actually get closed. Vulnerability Disclosure & Bug Bounty : Manage incoming whitehat reports, validate findings by reproducing them, assess severity, communicate with researchers. AI Tools Security Support : Assess technical risks related to AI tools used within teams (such as data exfiltration, prompt injection, training-on-input), maintain security baselines for AI coding tools and review AI-powered internal tools. Qualifications Must-have 5+ years of hands-on experience with a focus on application security, penetration testing, or product security. Demonstrated ability to find vulnerabilities — through manual testing, architecture and/or code review, or creative attack simulation. You should be able to describe specific bugs you've found and how you found them. Practical experience with exchange or trading platform security — from a DEX (preferred) or DeFi protocol. You should understand order book mechanics, transaction flows, wallet security, and the threat landscape specific to trading infrastructure. Scripting and automation ability — you write tools and automate to scale security across the stack, not just audit and write reports. Experience triaging vulnerabilities and writing clear, actionable remediation guidance for developers. Strong written communication in English — you'll write tickets, assessment reports and researcher responses. Strong plus Experience with cloud infrastructure security — least-privilege enforcement, network security, secrets management. Experience with container security — network policies, RBAC, pod security standards, image scanning, Dockerfile hardening, base image management. Ability to read and review code in at least one of: TypeScript/JavaScript, Solidity, Rust. Understanding of software supply chain security, including dependency risks, build integrity, and methods for tracking what components are included in shipped software. Experience managing or participating in a bug bounty program (e.g. Immunefi, HackerOne). Domain plus Experience securing AI/LLM tooling in engineering teams — prompt injection risks, data leakage prevention, tool configuration hardening Japanese language ability (not required, but useful for company context) Location / Timezone Strong preference for Tokyo-based or Singapore-based candidates - Startale office locations. Remote-friendly for exceptional candidates — must have 3+ hours overlap with Tokyo business hours (JST, UTC+9). Target start date As soon as available; realistic target start of Q3 2026. Target companies Decentralized exchanges, DeFi protocols, blockchain security firms, L1/L2 chain security teams, or fintech companies with trading infrastructure. We're also open to strong AppSec engineers from cloud-native startups who have genuine interest in web3. Ideal candidate You're a hands-on security engineer who finds real vulnerabilities, not just runs scanners. You've secured a trading platform or exchange and understand the threats specific to financial infrastructure — order book manipulation, transaction signing, wallet compromise, front-running. You can take a system, map the attack surface, and come back with findings that matter. You write clear reports that engineers act on, and you know the difference between a theoretical risk and a real one. You're comfortable working independently in a fast-moving team where there's no playbook — you write the playbook.