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Location: San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Anthropic Platform Org’s mission is to help builders build. Our vision is to be the premier platform for businesses to transform themselves and their products with AI. This org is responsible for our APIs, self-serve developer experience, multi-cloud integrations, and agentic infrastructure. We serve a wide array of users from startups to large scale enterprises. The platform team is comprised of three key areas: Enterprise fabric – where we are building multi-cloud integrations at extreme scale across our entire stack to meet businesses wherever they are and in the most demanding of requirements. Frontier capabilities – where we are building developer experiences and features that enable users to get the most out of the model and build at the very frontier of intelligence. Agentic platform – where we are inventing the next generation of agentic infrastructure for production-grade use and building new products to enable businesses to solve problems with agents. Responsibilities: Customer Understanding & Advocacy Deeply engage with enterprise developers and technical leaders to understand their integration needs and pain points Run regular feedback sessions and technical reviews with key enterprise customers Build strong relationships with enterprise development teams to understand their workflows and challenges Transform customer insights into actionable product requirements and priorities Product Strategy & Vision Define and execute the enterprise API strategy, balancing security requirements with developer experience Develop a clear roadmap for enterprise API features including authentication, rate limiting, and compliance capabilities Identify and prioritize key enterprise integration patterns that drive organizational value Enterprise API Development Partner with engineering to build enterprise-grade API features, security controls, and deployment tools Design and implement enterprise integration frameworks and SDKs for common enterprise systems Drive development of industry-specific API features and compliance capabilities Cross-functional Leadership Partner with sales and customer success to understand enterprise requirements and support technical evaluations Work closely with security and compliance teams to meet enterprise standards Collaborate with platform teams on API architecture and scalability Engage with marketing to develop enterprise API positioning and technical materials Minimum Qualifications You may be a good fit if you: Have built or shipped products with a hyperscaler as a partner — you know how to align goals and deliver impact across that boundary. Have owned a revenue number, a margin target, or a channel P&L — not just a product roadmap. Operate with high autonomy in ambiguous, fast-moving environments. Are an excellent written communicator and able to drive clarity out of complexity. Excel at cross-company stakeholder management and can build trusted relationships at every layer of an organization. Preferred Qualifications Strong candidates may also have: Have 10+ years of experience in high-scale, high-reliability developer-facing software. Have 5+ years of product management experience. Experience as a founder, GM, or early-stage operator where you owned commercial outcomes, not just product outputs. Direct experience as a PM at AWS, GCP, or Azure — or at an ISV that ships through one of their marketplaces. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $305,000 — $460,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Remote - United States Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning. We are hiring Machine Learning Engineers across our Consumer Engineering organization, giving you the opportunity to work on a wide range of high-impact problems across the Consumer ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you. What You’ll Work On We are looking for a Staff Machine Learning Engineer to help drive the next generation of Reddit’s ML ecosystem across recommendations, search, messaging, and foundational AI systems. You will lead high-impact initiatives from ideation to production, shaping both technical strategy and product direction across multiple ML domains. This is a highly cross-functional role partnering with Product, Data Science, and Engineering to deliver meaningful user and business impact. This role sits at the intersection of: Relevance & recommendation systems (content, search, notifications) AI-powered discovery & LLM-driven experiences Content and user understanding & large-scale representation learning Large-scale ML infrastructure and pipelines What You’ll Do Lead end-to-end ML initiatives from ideation through production and iteration, shaping technical direction and translating product goals into scalable solutions Architect, build and deploy large-scale ML systems across recommendation, search, and content/user understanding, including retrieval/ranking models, representation learnings embeddings optimizations, and LLM or GenAI-powered capabilities Drive measurable impact on user engagement, discovery, and long-term value Collaborate with cross-functional teams to align product and technical roadmaps and unlock key future ML capabilities Stay at the forefront of AI research, evaluating and introducing new AI/ML paradigms to keep Reddit’s ML ecosystem at the cutting edge Contribute to the development of best practices, guidelines, and ethical AI principles for responsible LLM development and deployment Mentor and guide senior and mid-level ML engineers, fostering a culture of excellence, innovation, and knowledge sharing Set technical vision and drive technical discussions, present findings to leadership, and contribute to long-term ML planning and decision-making Required Qualifications 7+ years of experience building, deploying, and operating machine learning systems in production Deep understanding of machine learning methods, spanning classical approaches and modern deep learning (e.g., Transformers, GNN, etc) Expert at developing and productionizing models using TensorFlow, PyTorch, or Hugging Face Transformers Experience building production-quality code incorporating testing, evaluation, and monitoring using object-oriented programming, including experience in Python and Golang Experience designing and scaling ML systems, including data pipelines, feature engineering, model training/serving, and production monitoring Excellent communication and collaboration skills, with the ability to discuss complex technical topics with diverse teams and translating product needs into scalable ML solutions Track record of driving measurable impact through applied machine learning in real-world products Preferred Qualifications Subject matter expertise in one of the following domains: Recommender systems Search systems (lexical and semantic retrieval and ranking) Content understanding (NLU/NLP/LLM, topic/taxonomy modeling, interest graphs or clustering, and multimodal understanding) Familiarity with distributed systems and large-scale data processing frameworks (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.) Experience working with real-time systems and low-latency production environments Experience with LLM/GenAI techniques, including but not limited to LLM evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems and productionizing LLM-powered products at scale Strong experimentation rigor, with experience formulating clear hypotheses, designing actionable learning plans and building offline/online correlations Advanced degree in Computer Science, Machine Learning, or related quantitative field Potential Teams Home Experience ML Understanding Feed Relevance Answer Experience Search and Answers Relevance Search Experience Benefits Comprehensive Healthcare Benefits and Income Replacement Programs 401k with Employer Match Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support Family Planning Support Gender-Affirming Care Mental Health & Coaching Benefits Flexible Vacation & Paid Volunteer Time Off Generous Paid Parental Leave #LI-Remote Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $230,000 — $322,000 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Location: New York City, NY | Seattle, WA; San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As part of our growing Data Science and Analytics team, you will play an instrumental role in our company’s mission of building safe and beneficial artificial intelligence by driving data-informed decision making across our organization. You bring experience from high-bar teams and are eager to help shape the norms and best practices of a growing data science team as Anthropic continues to scale. In this unique company, technology, and moment in history, your work will be critical to informing our strategy as we deploy safe, frontier AI at scale to the world. You’ll be the senior data science leader embedded in our Growth team and a strategic thought partner to its product and marketing leads. The Growth team’s job is to keep Anthropic on the exponential by getting more people and companies using and paying for Claude. You’ll help set direction across acquisition, activation, retention, and monetization: bringing a point of view on where to invest, how to grow revenue, and how to deliver more value for our users. As a tech lead manager, you’ll also manage a small team of Product Data Scientists, setting their agenda and raising the bar for how data shapes growth decisions. Responsibilities: Act as a strategic thought partner to Growth product and marketing leads, helping shape growth strategy, roadmap priorities, and the major bets the team makes Set the data science agenda for Growth, deciding where the Product Data Science team can have the most impact and what it should deprioritize Manage and develop a small team of Product Data Scientists, coaching them to move from answering questions to shaping decisions Frame the most important and ambiguous questions facing Growth, from where the next users and companies will come from to what makes them stay and pay, size the opportunities, and make clear recommendations, including when they challenge the current direction Define how Growth measures success, establishing the core metrics, guardrails, and measurement frameworks that tie short-term wins to long-term value Set the standard for experimentation and causal inference across Growth, including holdouts and quasi-experimental methods where A/B tests aren’t practical, and personally lead the highest-stakes analyses Guide how Growth measures the return on its programs, including marketing incrementality, LTV, CAC, and payback, and turn the results into budget and channel recommendations Guide the team’s work on targeting and personalization, including how we decide which users get which message, offer, or experience and how we evaluate those decisions Turn complex analyses into clear narratives and recommendations that drive decisions with senior leadership and cross-functional partners Establish foundational data practices and shape the analytics infrastructure Growth needs to support rapid iteration and decision-making as our products grow You may be a good fit if you: Have extensive experience in data science, including leading analytics for a growth or product area at significant scale Have 5+ years managing data science teams, including setting team direction and developing senior data scientists Have been a trusted partner to senior product, growth, or marketing leaders, with clear examples of changing a roadmap or high-stakes decision Bring strong product sense and business judgment across the growth funnel, including the ability to frame the right question and take a position with incomplete information Have deep expertise in experimental design, causal inference, and statistical modeling at high scale, with enough fluency in Python and SQL to stay hands-on and guide others’ technical work Communicate clearly in writing and in presentations, including to executive audiences Have a bias for action and thrive in ambiguous, fast-moving environments where you must create clarity and drive progress Care about the company’s mission of building helpful, honest, and harmless AI Strong candidates may also have: Experience measuring marketing incrementality, including holdouts, geo experiments, or marketing mix modeling Experience with targeting, personalization, or uplift models in production Background at consumption-based, multi-product companies serving both consumers and enterprises Experience with AI/ML products or large language models, including using coding agents in your own analytical workflow The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $285,000 — $380,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Brazil About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . *This is a remote role and can be performed anywhere in Brazil/Colombia* The Role We are looking for a Research Engineer to help deliver frontier-quality datasets, RL environments, and evaluations that improve state-of-the-art models for a frontier AI lab client. You will work directly with the client's researchers and engineers, turning inbound requests and post-training goals into concrete technical proposals and data/environment specifications, and then owning the technical execution: building the quality and verification systems that ensure what we deliver meets extremely high standards for correctness, realism, diversity, difficulty, and measurable model lift. Most of this work is bespoke and custom, built for one client's evolving needs.You'll typically stay attached to a single frontier lab client so you can build real context and a working relationship with their team, with flexibility to support other accounts when needed. Because bespoke work is judged on both turnaround time and quality, both matter equally here. This role is designed for candidates with experience building and improving deep learning systems, especially where strong results depend on data quality, data curation, denoising, synthetic data generation, and rigorous evaluation. You'll operate in one or more of the following capability areas: Coding and software engineering agents (repositories, unit tests, debugging, tool use, code reviews, long-horizon workflows) RL environments and verifier-based training (tasks, rewards/verifiers, trajectories, evaluation harnesses) Multimodal data and reasoning (text + images + documents + tables/charts; optional audio/video) STEM reasoning (math, physics, chemistry, bio, engineering – solution verification and error analysis) Modern embodied AI / VLM-driven agents (vision-language(-action) models, embodied task suites, tool/sensor/action abstractions, long-horizon interaction data) What You'll Do 1) Own data and environment quality from an AI researcher perspective Respond to inbound requests from the client and translate ambiguous, evolving research goals into a technical proposal and clear data requirements: target skills, failure modes, difficulty calibration, coverage, and success metrics. Provide the technical feasibility assessment, assumptions, acceptance criteria, and evaluation requirements needed to scope the contract or statement of work. Define what “good” looks like by creating detailed rubrics, counterexamples, and boundary cases (what to include vs. exclude). Perform deep, detail-oriented audits of produced data: spot subtle errors, reward hacking opportunities, leakage, ambiguity, inconsistent assumptions, and distribution shifts. Drive iterative improvements using evidence: group failures (for example, by semantic similarity) to find the underlying gap, then turn that into concrete instructions for the production team — better few-shot examples, explicit counterexamples, clearer guidance on what's causing rejections. 2) Design and build datasets and RL environments for your capability area(s) Contribute to or lead the design of: Task suites (single-step and long-horizon workflows) Ground-truth signals (verifiers, unit tests, structured checks, reward functions, automatic validators) Environment interfaces (APIs, tool schemas, state abstractions, database schemas, simulator-like dynamics) Depending on your mapped capability area(s), you may focus on: Coding / SWE agents: data reflecting real development work (codebase navigation, bug localization, patching, tests, code reviews, CI-like constraints, refactors, security fixes). Multimodality: tasks that test true multimodal reasoning (chart reading, document QA, UI understanding, diagram-based STEM reasoning, OCR-aware tasks). STEM: tasks with verifiable solutions (symbolic checks, reference solvers, numerical validation, step consistency, unit sanity). Modern embodied AI / VLM-driven agents: interaction data and environments for vision-language(-action) models. 3) Build robust validation, denoising, and synthetic data systems Build project-specific verification systems that combine deterministic checks, model-based evaluators calibrated against gold sets, and targeted human review. Implement automated validation and filtering to achieve frontier-grade signal-to-noise: deduplication, decontamination, leakage checks, consistency checks, difficulty and diversity controls. Develop synthetic data generation and augmentation pipelines where appropriate: programmatic task generators, controlled perturbations, scenario templating, simulator-/tool-driven rollouts. Create documentation and data cards: dataset intent, known limitations, recommended use, and evaluation linkage. 4) Use evaluations and training runs to prove impact Design and run evals that reflect the client's intended usage. Produce analysis that connects data to outcomes: pre/post comparisons, error breakdowns, ablations that identify which data attributes drive lift. When needed, run in-house fine-tuning or RL-style experiments (or partner with research) to demonstrate that the data/environment improves model behavior in measurable ways. 5) Collaborate effectively with large production teams without being ops-heavy Give technical direction to the distributed expert network producing the data, by providing clear specs, examples, edge cases, and fast feedback loops based on audits and quantitative signals. You own technical translation, acceptance criteria, evaluator and verifier design, quality diagnosis, and the technical release recommendation. The Strategic Project Lead owns production execution, staffing, throughput, project cost, and recovery. You are expected to be highly engaged in reviewing and improving outputs from large annotation/creation efforts, but not primarily responsible for hiring, staffing, or people operations — that sits with the SPL. Communicate directly with the client on technical findings, quality risks, and recovery options. Align changes to scope, schedule, or external commitments with the account and delivery owners. Who We're Looking For 4–5 years of experience building or improving deep learning systems where data quality mattered materially (training, post-training, evals, or agentic systems). Strong intuition for the “data ingredients” that drive model improvements: what to collect, what to filter, what to synthesize, and how to measure. Ability to communicate clearly with researchers and engineers: turning research objectives into concrete specs, and turning messy outputs into actionable insights. Comfortable being the direct technical point of contact for a client, including explaining setbacks or trade-offs when things don't go as planned. Demonstrated ability to be extremely detail-oriented in diagnosing subtle data quality issues and failure modes. Solid programming ability with a bias for shipping: Python proficiency required; comfort with SQL/structured data workflows strongly preferred; for coding-focused work, proficiency in a major language (e.g., C++, Java, Go, Rust, JS/TS) is a plus. Comfort designing quality systems: rubrics, validation scripts, gold sets, sampling strategies, statistical checks, slice-based evaluation, human-in-the-loop review loops grounded in measurable criteria. Direct experience with a frontier AI lab is not required, and is uncommon in the LATAM market — what matters most is hands-on engineering depth and the ability to operate with ambiguity. Strong pluses RL or post-training experience (any of: RLHF/RLAIF, verifier training, reward modeling, RL fine-tuning, environment design). Experience with agentic evaluation (tool use, multi-step workflows, long-horizon tasks, trajectory analysis). Multimodal expertise (document understanding, charts, diagrams, OCR, UI/vision grounding; audio/video optional). STEM depth (math/physics/engineering) with an eye for verifiability and rigorous correctness. Modern embodied AI / VLM-driven agent experience (vision-language(-action) models, interaction datasets, embodied evals, long-horizon grounding, tool/sensor/action interfaces). Systems thinking: ability to “simulate” an application's API/data schema and design tasks that realistically reflect real-world constraints and workflows. Why Turing Work directly with a frontier AI lab, at the cutting edge of post-training and RL environment design, embedded in a real research relationship rather than a rotating set of anonymous tasks. Real impact (path to AGI): your datasets and environments will directly influence the trajectory toward Artificial General Intelligence and, ultimately, Superintelligence. High autonomy and fast iteration, with a Strategic Project Lead handling scaling and resourcing so you can stay focused on the technical approach and quality bar. Talent-dense team, where you'll find rapid iteration and an exceptional learning curve. Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace  and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here .

Location: Hong Kong, Hong Kong SAR; Singapore, Singapore Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me, Do the Right Thing, and Get Things Done. These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About the Team We sit on the front lines of OKX's security and compliance mission. Our charter is to build the flexible, scalable, and intelligent AI systems that detect and prevent identity fraud, account takeover, and large-scale organized abuse — in real time and at the scale of a global financial platform. We own the core identity-risk capabilities that decide, millions of times a day, whether an account can be trusted: identity trust signals, behavioral risk modeling, relationship and cluster intelligence, and face, liveness and document verification. We work shoulder-to-shoulder with Product, Risk, Compliance, and Engineering to turn the hardest adversarial problems in crypto into production-grade defenses that protect good users and the open financial system. About the Role We are looking for a Senior AI Engineer to design, build, and own key identity-risk and trust models at OKX. You will build models that combine identity verification results, device and geo data, and user behavior into trust and risk signals, and use graph and clustering methods to uncover organized, industrialized fraud. This is an end-to-end, research-to-production role: you will own algorithms in your domain and ship models into real-money, high-risk, large-scale production environments. You will be a hands-on technical contributor who works closely with Product, Risk, and Compliance, and who helps raise the technical bar of the team. Your domains span: Identity trust & risk modeling — fusing verification scores, device, geo, and behavioral data into identity-quality and trust signals. Cluster & relationship intelligence — graph and clustering methods to identify account farms, mass registration, and coordinated attacks. Behavioral risk modeling — behavioral features and sequence models for account takeover and abnormal-session detection. Biometric & multimodal signals — face embeddings, liveness/anti-spoofing, DeepFake and injection defense, document forgery and AIGC detection, used as inputs to identity trust and the risk layer. AI agents — applying agentic AI to scale investigation, detection, and operational defense. What You'll Be Doing Build identity trust & risk models: Design and ship coarse-to-fine risk models that fuse face/liveness/document verification scores, device, IP and geo signals, and behavioral data, for high-concurrency real-time decisioning. Uncover organized fraud with graph & clustering: Build entity graphs across accounts, devices, faces, documents and templates, and apply community detection, clustering, and GNN methods to detect fraud rings and large-scale abuse. Develop behavioral features & sequence models: Engineer real-time and offline behavioral features, and build sequence models to detect account takeover, bot/script behavior, and abnormal sessions. Leverage biometric & multimodal signals: Turn biometric features (face embeddings, face quality, liveness and anti-spoofing results) and document-forgery and DeepFake signals into reliable identity-trust inputs for risk decisions, including biometric similarity for cross-account linkage and duplicate-identity detection. Work with the face, liveness, and document teams, or build models yourself. Drive execution & collaboration: Deliver measurable results while managing ambiguity; partner with backend, product, infrastructure, risk, and compliance teams to integrate models into the production decision chain. Own metric definitions, the balance between false positives and missed fraud, pass rate, monitoring, and drift handling. Advance applied R&D: Experiment with graph learning, multimodal fusion, and AI agents; stay current with academic and industry advances and translate them into practical defenses. Raise the technical bar: Contribute to design reviews, share applied-AI best practices, and mentor junior engineers. What We Look For 5+ years of hands-on experience building risk-control, fraud-detection, or identity-trust models, including significant experience deploying ML systems into production. Graph & clustering expertise: Experience applying graph mining, community detection, clustering, or GNN methods to fraud or abuse detection. Behavioral modeling: Solid experience with behavioral feature engineering and sequence modeling, including real-time feature pipelines. Deep AI/ML expertise: Strong proficiency with PyTorch and/or TensorFlow, and solid experience with production ML systems. Strong technical & coding skills: Strong coding ability (e.g., Python, SQL) and the system-level thinking to design end-to-end solutions with high availability and low latency. Adversarial mindset: Understanding of how fraudsters adapt, and how to evaluate and iterate defenses against evolving attacks. Collaboration: Strong communication skills, with experience working across engineering, product, and risk teams. Education: Bachelor's degree or higher in Computer Science, Electrical Engineering, or a related field. Preferred Qualifications Experience in identity verification, KYC/KYB, AML, face-payment or payment risk control, or biometric security. Hands-on experience with face recognition, liveness/anti-spoofing, OCR, document parsing, fake-ID detection, or media forensics. Experience with graph databases or graph computing (e.g., Neo4j, GraphX) and real-time graph features. Knowledge of data and AI/ML infrastructure (e.g., Spark, Flink, Kafka, Airflow, Snowflake). Familiarity with MLOps best practices: monitoring, retraining, and continuous improvement of production models. Experience with LLMs and AI agents. Experience working in fast-paced technology companies or security-critical environments. Research publications, patents, or open-source contributions in relevant AI fields. Perks & Benefits Competitive total compensation package L&D programs and Education subsidy for employees' growth and development Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependants More that we love to tell you along the process! Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .

Location: Washington, DC About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Federal Partners Account Executive at Anthropic, you'll drive revenue by selling our safe, frontier AI solutions directly to Systems Integrators (SI) and Independent Software Vendors (ISV) in the public sector space. You'll focus on selling directly to partners to ensure Anthropic's AI capabilities are delivered within their own solutions and service offerings. Working closely with GTM, product, and marketing teams, you'll help these partners understand and implement our technology while driving significant revenue growth. Responsibilities Win new business and drive revenue for Anthropic by directly selling to Systems Integrators and ISVs in the public sector space, owning the full sales cycle from prospecting through close Identify net-new revenue by selling to SIs with prime contracts, helping them integrate AI into their technology stack and consulting practices to differentiate their offerings, accelerate delivery, and win more competitive bids Navigate complex technical sales conversations with partners' engineering and product teams Work with partners' technical teams to ensure successful implementation, adoption and deployment of Anthropic's AI capabilities into their solutions Coordinate with cloud providers (AWS, GCP) to align technical and commercial aspects of deals Build deep relationships with key decision makers within partner organizations Provide market intelligence and partner feedback to product teams to influence our roadmap and feature development Create and maintain sales playbooks specific to SI and ISV sales motions Track and forecast sales pipeline specific to the partner segment You may be a good fit if you have 7+ years of enterprise sales experience selling directly to Systems Integrators and ISVs Security clearances preferred Strong track record of closing complex technical sales to partner organizations Deep understanding of SI and ISV business models, buying processes, and technology evaluation criteria Experience navigating technical requirements and security standards specific to public sector implementations Proven ability to exceed revenue targets in partner-focused sales roles Strong technical acumen and ability to engage with partners' engineering teams Experience coordinating with cloud providers in complex deal scenarios Excellent communication skills and ability to present to both technical and business audiences Strategic thinking combined with hands-on sales execution capabilities Understanding of public sector procurement processes and how partners operate within them A passion for safe and ethical AI development, with the ability to articulate its technical value to partner organizations Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $380,000 — $450,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: UK Workplace: Remote About Inworld Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, realtime workloads. Hundreds of millions of users interact with Inworld powered apps every day and we serve over 10 trillion LLM tokens per month. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more. Our work spans model research, realtime inference, large-scale serving infrastructure, and the APIs developers use to bring these capabilities into production. We’ve raised more than $125M from Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, Stanford, and others. Our technology has powered experiences from companies including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat. Inworld has also been recognized by CB Insights as one of the 100 most promising AI companies globally and named one of LinkedIn’s Top 10 Startups in the USA. WHO WE'RE LOOKING FOR A year ago, reliably working agentic systems barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood. EXPERIENCE WE FIND USEFUL You don't need all of this. But you need enough to make a case. - Foundation models: training, new architectures, RL, reward modeling, scaling - Evaluation: benchmarks, eval loops, quality measurement, LLM-as-judge, failure analysis - Frontier topics: multimodal models, agents, tool use, test-time compute, world models - Published research at ICML, ICLR, NeurIPS, EMNLP, ACL, or AAAI - PhD in ML/NLP — or equivalent practical experience you can point to - Public work: non-trivial AI side projects, interdisciplinary experiments, open-source contributions - Full-stack research ownership: you frame the question, run the experiments, write the paper, ship the result If you learned through building, competitions, or collaborations outside academia — that counts. We care about evidence, not credentials. WHO THRIVES HERE - Pathfinders: You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go. - Full-Cycle Researchers: You believe research isn't finished until it’s shipped. You have a bias for impact over purely academic output. - First-Principles Engineers: You don't just ship code; you obsess over the why. You’re the first to question an approach if you think there’s a better way to solve the core problem. - Mission Owners: You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make. WHAT WORKING HERE IS LIKE We hand you unclear problems and expect you to make them clear. We value researchers who say "I don't know yet" — and then design the experiment that finds out. We treat evaluation as a first-class research product, not a box to check before launch. Impact comes before publications though we support sharing work that moves the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater. We don't need a cover letter. A link to something you've built tells us more. The base salary range for this full-time position is £140,000 – £200,000. In addition to base pay, total compensation includes equity and benefits. Within the range, individual pay is determined by work location, level, and additional factors, including competencies, experience, and business needs. The base pay range is subject to change and may be modified in the future. Candidates must already have the legal right to work in the United Kingdom, as visa sponsorship is not available for this role. For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S. visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements. Inworld Jobs Privacy https://inworld.ai/jobs-privacy

Location: Serbia Workplace: Remote About Inworld Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, realtime workloads. Hundreds of millions of users interact with Inworld powered apps every day and we serve over 10 trillion LLM tokens per month. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more. Our work spans model research, realtime inference, large-scale serving infrastructure, and the APIs developers use to bring these capabilities into production. We’ve raised more than $125M from Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, Stanford, and others. Our technology has powered experiences from companies including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat. Inworld has also been recognized by CB Insights as one of the 100 most promising AI companies globally and named one of LinkedIn’s Top 10 Startups in the USA. WHO WE'RE LOOKING FOR A year ago, reliably working agentic systems barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood. EXPERIENCE WE FIND USEFUL You don't need all of this. But you need enough to make a case. - Foundation models: training, new architectures, RL, reward modeling, scaling - Evaluation: benchmarks, eval loops, quality measurement, LLM-as-judge, failure analysis - Frontier topics: multimodal models, agents, tool use, test-time compute, world models - Published research at ICML, ICLR, NeurIPS, EMNLP, ACL, or AAAI - PhD in ML/NLP — or equivalent practical experience you can point to - Public work: non-trivial AI side projects, interdisciplinary experiments, open-source contributions - Full-stack research ownership: you frame the question, run the experiments, write the paper, ship the result If you learned through building, competitions, or collaborations outside academia — that counts. We care about evidence, not credentials. WHO THRIVES HERE - Pathfinders: You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go. - Full-Cycle Researchers: You believe research isn't finished until it’s shipped. You have a bias for impact over purely academic output. - First-Principles Engineers: You don't just ship code; you obsess over the why. You’re the first to question an approach if you think there’s a better way to solve the core problem. - Mission Owners: You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make. WHAT WORKING HERE IS LIKE We hand you unclear problems and expect you to make them clear. We value researchers who say "I don't know yet" — and then design the experiment that finds out. We treat evaluation as a first-class research product, not a box to check before launch. Impact comes before publications though we support sharing work that moves the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater. We don't need a cover letter. A link to something you've built tells us more. Professional fluency in English (written and spoken) is required, as you will be collaborating daily with our US-based leadership and engineering teams. Inworld Jobs Privacy https://inworld.ai/jobs-privacy

Location: Germany Workplace: Remote About Inworld Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, realtime workloads. Hundreds of millions of users interact with Inworld powered apps every day and we serve over 10 trillion LLM tokens per month. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more. Our work spans model research, realtime inference, large-scale serving infrastructure, and the APIs developers use to bring these capabilities into production. We’ve raised more than $125M from Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, Stanford, and others. Our technology has powered experiences from companies including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat. Inworld has also been recognized by CB Insights as one of the 100 most promising AI companies globally and named one of LinkedIn’s Top 10 Startups in the USA. Who We're Looking For A year ago, reliably working agentic systems barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood. Experience We Find Useful You don't need all of this. But you need enough to make a case. - Foundation models: training, new architectures, RL, reward modeling, scaling - Evaluation: benchmarks, eval loops, quality measurement, LLM-as-judge, failure analysis - Frontier topics: multimodal models, agents, tool use, test-time compute, world models - Published research at ICML, ICLR, NeurIPS, EMNLP, ACL, or AAAI - PhD in ML/NLP — or equivalent practical experience you can point to - Public work: non-trivial AI side projects, interdisciplinary experiments, open-source contributions - Full-stack research ownership: you frame the question, run the experiments, write the paper, ship the result If you learned through building, competitions, or collaborations outside academia — that counts. We care about evidence, not credentials. Who Thrives Here - Pathfinders: You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go. - Full-Cycle Researchers: You believe research isn't finished until it’s shipped. You have a bias for impact over purely academic output. - First-Principles Engineers: You don't just ship code; you obsess over the why. You’re the first to question an approach if you think there’s a better way to solve the core problem. - Mission Owners: You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make. What Working Here Is Like We hand you unclear problems and expect you to make them clear. We value researchers who say "I don't know yet" — and then design the experiment that finds out. We treat evaluation as a first-class research product, not a box to check before launch. Impact comes before publications though we support sharing work that moves the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater. We don't need a cover letter. A link to something you've built tells us more. Professional fluency in English (written and spoken) is required, as you will be collaborating daily with our US-based leadership and engineering teams. For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S. visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements. Inworld Jobs Privacy https://inworld.ai/jobs-privacy

Location: Remote Workplace: Remote Our Team Dandelion Health unlocks a layer of unexplored clinical depth that has been previously inaccessible at scale. By combining all the raw multimodal data from community health systems with validated AI models, we deliver regulatory-grade scientific insights and products that give teams the evidence to design better trials, enroll the right patients, and generate AI-powered insights that drive confident decisions across the development and commercial lifecycle. Your Role As a Strategic Partnerships Manager - Life Sciences, you will oversee Dandelion Health’s most important strategic life science accounts and ensure the successful implementation of partnerships. You will translate customer business needs into deliverables, quarterbacking execution across data science, engineering, and growth teams. Your goal is not only to deliver on the initial scope of work but also to identify opportunities for upselling and expand projects into long-term, multi-million-dollar partnerships. You will own client communications, internal project plans, and engagement management end-to-end. By building strong executive and operational relationships with partners, you will ensure alignment on priorities, anticipate challenges, and deliver measurable outcomes. Internally, you will bring the voice of the customer into planning conversations and drive cross-functional alignment to meet customer goals. You thrive in client-facing environments, can navigate technical and non-technical conversations, and are motivated to build lasting partnerships that drive both customer success and Dandelion’s growth. You will report directly to the Chief Commercial Officer. Responsibilities - Deliver and Expand Partnerships: Ensure successful execution of initial projects and proactively identify opportunities for upsell, cross-sell, and long-term expansion into multi-million-dollar partnerships. - Translate Business Needs into Deliverables: Partner with customer executives to understand business objectives and convert them into impactful deliverables that create clear value. - Quarterback Engagements: - Lead end-to-end execution of strategic accounts, coordinating data science, engineering, and growth resources to deliver on time and at high quality. - Set clear priorities, track progress against deliverables, and escalate or resolve issues to keep engagements on track. - Act as the central point of accountability, ensuring all internal stakeholders are aligned and that clients receive a seamless, integrated experience. - Own Client Communications: Serve as the primary point of contact for strategic accounts, managing executive updates, project milestones, and issue resolution. - Support Complex Deals: Provide leverage for the growth team in structuring deliverables, implementation plans, and timelines for large, complex partnerships. - Drive Alignment: Ensure data integrity across tools (e.g., Salesforce, Jira) and maintain clarity for all stakeholders on account status, progress, and opportunities. - Inform Product Roadmap: Surface partner needs, feedback, and market insights to influence product strategy, ensuring Dandelion’s roadmap and features align with customer priorities and emerging opportunities. Qualifications Required: - 4+ years of consulting, strategic account management, or client-facing experience, ideally in life sciences, healthcare, or health tech. - Experience supporting customers on data analytics or RWE/RWD platforms (or similar healthcare data products). - Strong background in project management with proven ability to lead cross-functional engagements from start to finish. - Prior analytical experience, with the ability to bridge conversations between technical and non-technical stakeholders. - Exceptional communication skills, with experience engaging senior executives (VP and above) and translating complex work into business impact. - Demonstrated ability to upsell, cross-sell, and expand customer relationships into larger, revenue-generating partnerships. - Highly organized and goal-oriented, with strong problem-solving skills and the ability to anticipate and proactively resolve challenges. - Comfortable working in a fast-paced, early-stage environment where flexibility and ownership are critical. - Willingness to travel as needed for client meetings and industry events. Preferred: - 3+ years in life sciences or healthcare consulting, with strong emphasis on client engagement and project delivery. - Familiarity with real-world evidence use cases in pharma (medical affairs, outcomes research, HEOR, medical affairs, value & access, epidemiology, RWD/RWE). - Experience working with data scientists, healthcare analytics projects, and data products Team Benefits - Remote work and flexible hours. Availability needed for meetings, which we try to keep to a healthy minimum - Complete wellness benefits including healthcare, dental, vision, PTO, sick days and more. Ask for details - Professional development days to build your skills - Collegial work environment - Academic bent towards inquiry and problem solving but start-up speed and flexibility - Great balance of focus time to work on projects but easy to access team members to discuss issues and work collaboratively - Dandelion is a mission-driven company that is focused on improving patient care

Location: International About HumanSignal Real-world data is the competitive edge in AI. HumanSignal is a human data partner for companies building AI models and products. Our customers ship better AI, faster, because we partner with their researchers from real-world data creation to annotation to delivery. We design and create datasets from scratch, recruit and manage the domain experts who evaluate model output, and run everything through our own platform, Label Studio, the open-source standard for data labeling and evaluation, used by over 1 million practitioners worldwide. We specialize in the operationally complex: real-world data collection, multimodal pipelines, and multi-step workflows. Advanced ML and AI teams use our enterprise platform to run their own data factories, and our services team to extend their reach where in-house capacity runs out. If you want to do work that materially shapes how the next generation of AI products gets built, we'd love to talk. AI Data Collector — Turn the World Into Your Workplace! About the Opportunity We’re building a global community of detail-oriented contributors who help improve the quality of datasets used to develop advanced technologies such as artificial intelligence and computer vision systems. As a Data Annotation Contributor, you’ll help review and refine labeled data to ensure accuracy and consistency. We are preparing for several upcoming initiatives and are inviting qualified contributors to join our growing community. By joining our contributor network, you’ll be among the first to hear about annotation projects that match your skills and location. What You’ll Do Depending on the project, contributors may be asked to review and correct labeled data within images or videos. Tasks may include: Reviewing and correcting bounding boxes around objects or people Adjusting or refining segmentation or masking areas within images Identifying and masking personally identifiable information (PII) when required Ensuring annotations follow detailed project guidelines and quality standards Flagging unclear or incorrect labels for review Submitting completed annotation tasks through designated tools or platforms Each project will include clear instructions, examples, and support from our team. How Our Community Works Once you join our contributor community, you will: Receive notifications about upcoming or ongoing data annotation projects Review project details and decide whether you’d like to participate Complete annotation tasks that match your skills and availability Gain access to future opportunities as new projects are launched Participation is flexible, allowing contributors to select the projects they want to work on. What We’re Looking For We’re looking for contributors who are: Highly detail-oriented and focused on accuracy Comfortable following structured guidelines and quality standards Able to work independently and manage tasks responsibly Strong communicators when questions or clarifications arise Comfortable using online tools for reviewing or editing data Previous experience with data annotation, image labeling, or quality review is helpful but not required. Training materials may be provided depending on the project. Compensation Compensation will vary depending on the specific project and the country or region where the work is performed. Pay rates will be communicated prior to the start of each project and are designed to align with competitive rates for similar work in your location. Why Join Our Contributor Community Flexible opportunities to participate in data annotation projects The ability to contribute to the development of emerging technologies Access to a growing pipeline of global annotation initiatives Clear instructions and support from experienced project teams If you enjoy detail-oriented work and want to contribute to improving real-world datasets used in advanced technologies, we encourage you to apply and become part of our annotation contributor community. ( Must reside in one of these countries , India, Pakistan, Bangladesh, Sri Lanka, Nepal, Philippines, Vietnam, Indonesia, Thailand, Malaysia, Kenya, Nigeria, Ghana, Uganda, Tanzania, Rwanda, Egypt, Mexico, Colombia, Peru, Argentina, Brazil, Bolivia, Guatemala) This is an independent contractor engagement and does not constitute employment with HumanSignal. Contractors are responsible for their own tax obligations in their jurisdiction.

Location: United States About HumanSignal Real-world data is the competitive edge in AI. HumanSignal is a human data partner for companies building AI models and products. Our customers ship better AI, faster, because we partner with their researchers from real-world data creation to annotation to delivery. We design and create datasets from scratch, recruit and manage the domain experts who evaluate model output, and run everything through our own platform, Label Studio, the open-source standard for data labeling and evaluation, used by over 1 million practitioners worldwide. We specialize in the operationally complex: real-world data collection, multimodal pipelines, and multi-step workflows. Advanced ML and AI teams use our enterprise platform to run their own data factories, and our services team to extend their reach where in-house capacity runs out. If you want to do work that materially shapes how the next generation of AI products gets built, we'd love to talk. (US BASED) AI Data Collector — Turn the World Into Your Workplace! Do you love scavenger hunts? Enjoy exploring the world around you? Want to get paid competitively while doing something fun, flexible, and impactful? We’re looking for curious, detail-oriented individuals to join us as AI Data Collectors . In this role, the world becomes your workspace. You’ll help shape the future of AI by capturing high-quality images based on project guidelines—no two assignments are exactly the same. What You’ll Do As an AI Data Collector, you will: Capture assigned images in real-world environments , following specific project guidelines. Photograph objects, scenes, or activities across a wide range of settings, backgrounds, lighting conditions, and angles . Travel locally to collect data in homes, offices, stores, parks, streets, or other everyday locations . Follow detailed instructions to ensure image quality, variation, and accuracy. Document your process when needed and upload collected data through provided tools. Work independently, manage your time, and meet project deadlines. Support the development and improvement of next-generation AI technologies. Who You Are You’ll thrive in this role if you: Love exploring new places and noticing details others might miss Are reliable, self-motivated, and comfortable working solo Enjoy task-based, flexible work that changes from project to project Have a smartphone or camera with solid image quality Can follow instructions carefully and consistently Why You’ll Love This Role Competitive pay Flexible schedule — work when and where it fits your life Perfect for people who enjoy movement, creativity, and variety A chance to directly influence cutting-edge AI systems No prior experience needed — just enthusiasm and a keen eye! If you’re ready for work that feels like a real-world scavenger hunt with real rewards, we’d love to have you work with us. Note: all data collections must be completed safely and lawfully. Never complete data collection in a way that would risk injury to you or others. Important: This opportunity is a 1099 contractor assignment and does not constitute employment with HumanSignal. Up to $20 /hour

Location: United Kingdom About HumanSignal Real-world data is the competitive edge in AI. HumanSignal is a human data partner for companies building AI models and products. Our customers ship better AI, faster, because we partner with their researchers from real-world data creation to annotation to delivery. We design and create datasets from scratch, recruit and manage the domain experts who evaluate model output, and run everything through our own platform, Label Studio, the open-source standard for data labeling and evaluation, used by over 1 million practitioners worldwide. We specialize in the operationally complex: real-world data collection, multimodal pipelines, and multi-step workflows. Advanced ML and AI teams use our enterprise platform to run their own data factories, and our services team to extend their reach where in-house capacity runs out. If you want to do work that materially shapes how the next generation of AI products gets built, we'd love to talk. ( United Kingdom BASED) AI Data Collector — Turn the World Into Your Workplace! Do you love scavenger hunts? Enjoy exploring the world around you? Want to get paid competitively while doing something fun, flexible, and impactful? We’re looking for curious, detail-oriented individuals to join us as AI Data Collectors . In this role, the world becomes your workspace. You’ll help shape the future of AI by capturing high-quality images based on project guidelines—no two assignments are exactly the same. What You’ll Do As an AI Data Collector, you will: Capture assigned images in real-world environments , following specific project guidelines. Photograph objects, scenes, or activities across a wide range of settings, backgrounds, lighting conditions, and angles . Travel locally to collect data in homes, offices, stores, parks, streets, or other everyday locations . Follow detailed instructions to ensure image quality, variation, and accuracy. Document your process when needed and upload collected data through provided tools. Work independently, manage your time, and meet project deadlines. Support the development and improvement of next-generation AI technologies. Who You Are You’ll thrive in this role if you: Love exploring new places and noticing details others might miss Are reliable, self-motivated, and comfortable working solo Enjoy task-based, flexible work that changes from project to project Have a smartphone or camera with solid image quality Can follow instructions carefully and consistently Why You’ll Love This Role Competitive pay Flexible schedule — work when and where it fits your life Perfect for people who enjoy movement, creativity, and variety A chance to directly influence cutting-edge AI systems No prior experience needed — just enthusiasm and a keen eye! If you’re ready for work that feels like a real-world scavenger hunt with real rewards, we’d love to have you work with us. Note: all data collections must be completed safely and lawfully. Never complete data collection in a way that would risk injury to you or others. Important: This opportunity is a 1099 contractor assignment and does not constitute employment with HumanSignal. Up to $13.300 /hour

Location: Thailand About HumanSignal Real-world data is the competitive edge in AI. HumanSignal is a human data partner for companies building AI models and products. Our customers ship better AI, faster, because we partner with their researchers from real-world data creation to annotation to delivery. We design and create datasets from scratch, recruit and manage the domain experts who evaluate model output, and run everything through our own platform, Label Studio, the open-source standard for data labeling and evaluation, used by over 1 million practitioners worldwide. We specialize in the operationally complex: real-world data collection, multimodal pipelines, and multi-step workflows. Advanced ML and AI teams use our enterprise platform to run their own data factories, and our services team to extend their reach where in-house capacity runs out. If you want to do work that materially shapes how the next generation of AI products gets built, we'd love to talk. ( Thailand BASED) AI Data Collector — Turn the World Into Your Workplace! Do you love scavenger hunts? Enjoy exploring the world around you? Want to get paid competitively while doing something fun, flexible, and impactful? We’re looking for curious, detail-oriented individuals to join us as AI Data Collectors . In this role, the world becomes your workspace. You’ll help shape the future of AI by capturing high-quality images based on project guidelines—no two assignments are exactly the same. What You’ll Do As an AI Data Collector, you will: Capture assigned images in real-world environments , following specific project guidelines. Photograph objects, scenes, or activities across a wide range of settings, backgrounds, lighting conditions, and angles . Travel locally to collect data in homes, offices, stores, parks, streets, or other everyday locations . Follow detailed instructions to ensure image quality, variation, and accuracy. Document your process when needed and upload collected data through provided tools. Work independently, manage your time, and meet project deadlines. Support the development and improvement of next-generation AI technologies. Who You Are You’ll thrive in this role if you: Love exploring new places and noticing details others might miss Are reliable, self-motivated, and comfortable working solo Enjoy task-based, flexible work that changes from project to project Have a smartphone or camera with solid image quality Can follow instructions carefully and consistently Why You’ll Love This Role Competitive pay Flexible schedule — work when and where it fits your life Perfect for people who enjoy movement, creativity, and variety A chance to directly influence cutting-edge AI systems No prior experience needed — just enthusiasm and a keen eye! If you’re ready for work that feels like a real-world scavenger hunt with real rewards, we’d love to have you work with us. Note: all data collections must be completed safely and lawfully. Never complete data collection in a way that would risk injury to you or others. Important: This opportunity is a 1099 contractor assignment and does not constitute employment with HumanSignal. Up to $6.00 /hour

Location: South Africa About HumanSignal Real-world data is the competitive edge in AI. HumanSignal is a human data partner for companies building AI models and products. Our customers ship better AI, faster, because we partner with their researchers from real-world data creation to annotation to delivery. We design and create datasets from scratch, recruit and manage the domain experts who evaluate model output, and run everything through our own platform, Label Studio, the open-source standard for data labeling and evaluation, used by over 1 million practitioners worldwide. We specialize in the operationally complex: real-world data collection, multimodal pipelines, and multi-step workflows. Advanced ML and AI teams use our enterprise platform to run their own data factories, and our services team to extend their reach where in-house capacity runs out. If you want to do work that materially shapes how the next generation of AI products gets built, we'd love to talk. ( South Africa BASED) AI Data Collector — Turn the World Into Your Workplace! Do you love scavenger hunts? Enjoy exploring the world around you? Want to get paid competitively while doing something fun, flexible, and impactful? We’re looking for curious, detail-oriented individuals to join us as AI Data Collectors . In this role, the world becomes your workspace. You’ll help shape the future of AI by capturing high-quality images based on project guidelines—no two assignments are exactly the same. What You’ll Do As an AI Data Collector, you will: Capture assigned images in real-world environments , following specific project guidelines. Photograph objects, scenes, or activities across a wide range of settings, backgrounds, lighting conditions, and angles . Travel locally to collect data in homes, offices, stores, parks, streets, or other everyday locations . Follow detailed instructions to ensure image quality, variation, and accuracy. Document your process when needed and upload collected data through provided tools. Work independently, manage your time, and meet project deadlines. Support the development and improvement of next-generation AI technologies. Who You Are You’ll thrive in this role if you: Love exploring new places and noticing details others might miss Are reliable, self-motivated, and comfortable working solo Enjoy task-based, flexible work that changes from project to project Have a smartphone or camera with solid image quality Can follow instructions carefully and consistently Why You’ll Love This Role Competitive pay Flexible schedule — work when and where it fits your life Perfect for people who enjoy movement, creativity, and variety A chance to directly influence cutting-edge AI systems No prior experience needed — just enthusiasm and a keen eye! If you’re ready for work that feels like a real-world scavenger hunt with real rewards, we’d love to have you work with us. Note: all data collections must be completed safely and lawfully. Never complete data collection in a way that would risk injury to you or others. Important: This opportunity is a 1099 contractor assignment and does not constitute employment with HumanSignal. Up to $6.00 /hour

Location: Romania About HumanSignal Real-world data is the competitive edge in AI. HumanSignal is a human data partner for companies building AI models and products. Our customers ship better AI, faster, because we partner with their researchers from real-world data creation to annotation to delivery. We design and create datasets from scratch, recruit and manage the domain experts who evaluate model output, and run everything through our own platform, Label Studio, the open-source standard for data labeling and evaluation, used by over 1 million practitioners worldwide. We specialize in the operationally complex: real-world data collection, multimodal pipelines, and multi-step workflows. Advanced ML and AI teams use our enterprise platform to run their own data factories, and our services team to extend their reach where in-house capacity runs out. If you want to do work that materially shapes how the next generation of AI products gets built, we'd love to talk. ( Romania BASED) AI Data Collector — Turn the World Into Your Workplace! Do you love scavenger hunts? Enjoy exploring the world around you? Want to get paid competitively while doing something fun, flexible, and impactful? We’re looking for curious, detail-oriented individuals to join us as AI Data Collectors . In this role, the world becomes your workspace. You’ll help shape the future of AI by capturing high-quality images based on project guidelines—no two assignments are exactly the same. What You’ll Do As an AI Data Collector, you will: Capture assigned images in real-world environments , following specific project guidelines. Photograph objects, scenes, or activities across a wide range of settings, backgrounds, lighting conditions, and angles . Travel locally to collect data in homes, offices, stores, parks, streets, or other everyday locations . Follow detailed instructions to ensure image quality, variation, and accuracy. Document your process when needed and upload collected data through provided tools. Work independently, manage your time, and meet project deadlines. Support the development and improvement of next-generation AI technologies. Who You Are You’ll thrive in this role if you: Love exploring new places and noticing details others might miss Are reliable, self-motivated, and comfortable working solo Enjoy task-based, flexible work that changes from project to project Have a smartphone or camera with solid image quality Can follow instructions carefully and consistently Why You’ll Love This Role Competitive pay Flexible schedule — work when and where it fits your life Perfect for people who enjoy movement, creativity, and variety A chance to directly influence cutting-edge AI systems No prior experience needed — just enthusiasm and a keen eye! If you’re ready for work that feels like a real-world scavenger hunt with real rewards, we’d love to have you work with us. Note: all data collections must be completed safely and lawfully. Never complete data collection in a way that would risk injury to you or others. Important: This opportunity is a 1099 contractor assignment and does not constitute employment with HumanSignal. Up to $7.70 /hour

Location: Poland About HumanSignal Real-world data is the competitive edge in AI. HumanSignal is a human data partner for companies building AI models and products. Our customers ship better AI, faster, because we partner with their researchers from real-world data creation to annotation to delivery. We design and create datasets from scratch, recruit and manage the domain experts who evaluate model output, and run everything through our own platform, Label Studio, the open-source standard for data labeling and evaluation, used by over 1 million practitioners worldwide. We specialize in the operationally complex: real-world data collection, multimodal pipelines, and multi-step workflows. Advanced ML and AI teams use our enterprise platform to run their own data factories, and our services team to extend their reach where in-house capacity runs out. If you want to do work that materially shapes how the next generation of AI products gets built, we'd love to talk. ( Poland BASED) AI Data Collector — Turn the World Into Your Workplace! Do you love scavenger hunts? Enjoy exploring the world around you? Want to get paid competitively while doing something fun, flexible, and impactful? We’re looking for curious, detail-oriented individuals to join us as AI Data Collectors . In this role, the world becomes your workspace. You’ll help shape the future of AI by capturing high-quality images based on project guidelines—no two assignments are exactly the same. What You’ll Do As an AI Data Collector, you will: Capture assigned images in real-world environments , following specific project guidelines. Photograph objects, scenes, or activities across a wide range of settings, backgrounds, lighting conditions, and angles . Travel locally to collect data in homes, offices, stores, parks, streets, or other everyday locations . Follow detailed instructions to ensure image quality, variation, and accuracy. Document your process when needed and upload collected data through provided tools. Work independently, manage your time, and meet project deadlines. Support the development and improvement of next-generation AI technologies. Who You Are You’ll thrive in this role if you: Love exploring new places and noticing details others might miss Are reliable, self-motivated, and comfortable working solo Enjoy task-based, flexible work that changes from project to project Have a smartphone or camera with solid image quality Can follow instructions carefully and consistently Why You’ll Love This Role Competitive pay Flexible schedule — work when and where it fits your life Perfect for people who enjoy movement, creativity, and variety A chance to directly influence cutting-edge AI systems No prior experience needed — just enthusiasm and a keen eye! If you’re ready for work that feels like a real-world scavenger hunt with real rewards, we’d love to have you work with us. Note: all data collections must be completed safely and lawfully. Never complete data collection in a way that would risk injury to you or others. Important: This opportunity is a 1099 contractor assignment and does not constitute employment with HumanSignal. Up to $8.80 /hour

Location: Netherlands About HumanSignal Real-world data is the competitive edge in AI. HumanSignal is a human data partner for companies building AI models and products. Our customers ship better AI, faster, because we partner with their researchers from real-world data creation to annotation to delivery. We design and create datasets from scratch, recruit and manage the domain experts who evaluate model output, and run everything through our own platform, Label Studio, the open-source standard for data labeling and evaluation, used by over 1 million practitioners worldwide. We specialize in the operationally complex: real-world data collection, multimodal pipelines, and multi-step workflows. Advanced ML and AI teams use our enterprise platform to run their own data factories, and our services team to extend their reach where in-house capacity runs out. If you want to do work that materially shapes how the next generation of AI products gets built, we'd love to talk. ( Netherlands BASED) AI Data Collector — Turn the World Into Your Workplace! Do you love scavenger hunts? Enjoy exploring the world around you? Want to get paid competitively while doing something fun, flexible, and impactful? We’re looking for curious, detail-oriented individuals to join us as AI Data Collectors . In this role, the world becomes your workspace. You’ll help shape the future of AI by capturing high-quality images based on project guidelines—no two assignments are exactly the same. What You’ll Do As an AI Data Collector, you will: Capture assigned images in real-world environments , following specific project guidelines. Photograph objects, scenes, or activities across a wide range of settings, backgrounds, lighting conditions, and angles . Travel locally to collect data in homes, offices, stores, parks, streets, or other everyday locations . Follow detailed instructions to ensure image quality, variation, and accuracy. Document your process when needed and upload collected data through provided tools. Work independently, manage your time, and meet project deadlines. Support the development and improvement of next-generation AI technologies. Who You Are You’ll thrive in this role if you: Love exploring new places and noticing details others might miss Are reliable, self-motivated, and comfortable working solo Enjoy task-based, flexible work that changes from project to project Have a smartphone or camera with solid image quality Can follow instructions carefully and consistently Why You’ll Love This Role Competitive pay Flexible schedule — work when and where it fits your life Perfect for people who enjoy movement, creativity, and variety A chance to directly influence cutting-edge AI systems No prior experience needed — just enthusiasm and a keen eye! If you’re ready for work that feels like a real-world scavenger hunt with real rewards, we’d love to have you work with us. Note: all data collections must be completed safely and lawfully. Never complete data collection in a way that would risk injury to you or others. Important: This opportunity is a 1099 contractor assignment and does not constitute employment with HumanSignal. Up to $14.30 /hour