Build and own production AI agent systems spanning orchestration, backend services, integrations, knowledge infrastructure, trust and safety, and evaluation. The role requires 5+ years of backend engineering experience, hands-on LLM or agent experience, and strong ownership in an ambiguous product environment.

Build and operate production machine learning systems for recommendations, search, advertising, content understanding, and LLM-powered experiences at internet scale. The role requires 3–5+ years of production ML experience, strong programming and software engineering fundamentals, and expertise with modern ML frameworks and scalable pipelines.

Design, build, and deploy production ML systems for recommendations, search, ranking, and advertising at internet scale. Own the full ML lifecycle from modeling to monitoring with strong cross-functional collaboration.

Build and own quantitative risk models, stress testing, default-risk frameworks, and real-time monitoring for a regulated derivatives exchange. The role requires hands-on derivatives risk experience, strong Python skills, exchange-mechanics expertise, and working knowledge of CFTC requirements.

Build and deploy algorithmic systems for high-impact healthcare problems, choosing among machine learning, optimization, heuristics, and hybrid approaches. The role requires 4+ years of relevant industry experience, strong applied problem-solving and evaluation skills, and fluency in modern ML tooling.

Builds and operates reliable, scalable data pipelines and infrastructure for Auth0’s data platform. The role requires 5+ years of software development experience, strong SQL and Python skills, and hands-on experience with cloud data systems and modern data-stack tools.

Leads product data science for Reddit’s Consumer area, using experimentation, causal analysis, metrics, and research to guide strategy and growth. The role requires an advanced quantitative degree, substantial industry experience, strong SQL and programming skills, and effective cross-functional communication.

The Senior Data Scientist will develop statistical and machine learning solutions that improve advertiser experience, campaign performance, and Reddit’s ads platform. The role requires an advanced quantitative degree, substantial applied data science experience, and expertise in experimentation, causal inference, large-scale data processing, and ML tooling.

Leads frontier-scale pretraining research for multimodal image, video, and audio foundation models, shaping architectures, objectives, data strategies, and distributed systems. The role requires prior ownership of production-grade foundation-model pretraining, deep Python and PyTorch expertise, and strong experience with visual generative models.

Owns end-to-end post-training for frontier multimodal generative models, spanning reward modeling, preference optimization, distillation, safety tuning, evaluation, and deployment. The role requires prior experience shipping post-training improvements and strong PyTorch expertise.

Advances vision-language models and integrates multimodal capabilities with FLUX diffusion and flow pipelines. The role requires demonstrated VLM pretraining or substantial architectural advancement, strong research or production results, and multi-node distributed training experience.

Conduct research on long-horizon, multi-agent AI behavior by designing agent environments, analyzing large-scale data, and running experiments. The role requires strong research judgment, rapid execution, independence, and familiarity with current AI developments.

Build, optimize, and evaluate long-running and multi-agent AI systems, along with tools for monitoring and analyzing their real-world behavior. The role requires software engineering experience with coding agents, strong independence, and familiarity with current AI developments.

Build scalable software and tools for frontier model training, research experimentation, and production machine learning systems. The role requires strong Python and distributed-training expertise, experience with ML frameworks and infrastructure, and the ability to optimize and debug large language model systems.

The Senior Data Scientist develops statistical and machine learning models from insurance and cybersecurity datasets to improve underwriting, pricing, risk evaluation, and workflow automation. The role requires a quantitative bachelor's degree, 5+ years of insurance experience, advanced SQL, and Python or R expertise.

Leads the technical vision, architecture, and roadmap for a company-wide machine learning platform supporting model training, deployment, serving, monitoring, and generative AI. The role requires expert Python and Java skills, large-scale MLOps experience, cloud and Kubernetes expertise, and organization-wide technical leadership.

Leads the technical vision, architecture, and engineering standards for a company-wide ML platform supporting model development, deployment, serving, and monitoring. The role requires principal-level expertise in Python and Java, scalable MLOps, cloud infrastructure, security, and technical leadership across teams.

Build production machine learning systems for model customization, post-training, evaluation, and AWS-native API integration. The role requires 7+ years of relevant engineering experience and expertise in deep learning, transformers, LLM fine-tuning, and production ML infrastructure.

The Data Scientist partners across Product, Sales, and Engineering to analyze usage, improve business decisions, build data pipelines, and deliver actionable dashboards. The role requires 5+ years of data science or product analytics experience, strong SQL and Python skills, and experience with BI tools and cloud infrastructure.

Build and deploy production machine-learning models for fraud detection, identity verification, and financial risk products. The role suits new PhD graduates or early-career researchers with strong quantitative foundations, Python experience, and interest in owning the full ML lifecycle.

Builds and owns fraud detection and financial-risk models end to end, from data acquisition and feature engineering through production deployment and monitoring. The role requires strong practical machine learning and statistics expertise, production coding experience, and either 4+ years with a relevant master’s degree or 2+ years with a relevant PhD.

Build and operate large-scale machine learning infrastructure and models for Reddit’s recommendation and personalization systems. The role requires 5+ years of ML engineering experience, expertise in deep learning and distributed systems, and proficiency with Python and modern ML frameworks.

Designs AI-native teaching methods and establishes rigorous measurement of skill gain, retention, and transfer. The role requires deep learning-science knowledge, strong experimental and statistical skills, human-subjects research experience, and technical fluency with Python or R.

Leads the technical direction of large-scale ML infrastructure for embedding, recommendation, and personalization systems. The role requires 8+ years of ML engineering experience, expertise in deep learning and distributed training, and strong leadership across research, infrastructure, and production deployment.

Build and operate the agentic systems powering an AI tutoring product, including learner modeling, long-horizon planning, tool use, verification, and evaluation. The role requires 3+ years of software engineering experience, production LLM experience, and strong Python or TypeScript/Node skills.

Leads Alpaca’s data department across platform engineering, analytics engineering, and data science, owning strategy, architecture, execution, and operational reliability. The role requires extensive data engineering and people-management experience, modern data-stack expertise, and familiarity with financial services data.

Staff Data Analyst leads analytics strategy for telehealth platform, driving executive decisions on patient outcomes, compliance, and operations using advanced SQL, Python/R, and BI tools. Requires 8+ years experience, bachelor's degree, and healthcare domain knowledge.

Manages end-to-end human data and evaluation projects for AI systems, partnering with engineering teams to improve training signals, model behavior, and data integrity. Requires cross-functional collaboration, dataset analysis, and experience with annotation or AI/ML data workflows.

The Credit Risk Associate develops and optimizes credit strategies across limits, payment speed, collections, and decisioning workflows. The role requires credit risk or quantitative strategy experience, SQL or Python proficiency, demonstrated AI fluency, and strong cross-functional judgment.

Build and operate petabyte-scale data infrastructure powering Discord’s insights and products. The role requires 5+ years of software engineering experience, strong programming skills, and experience with large-scale pipelines, streaming, orchestration, or data warehousing.

Builds data pipelines, distributed training infrastructure, simulation environments, and evaluation systems for multimodal world models and reinforcement-learning agents. The role partners with research scientists to scale experiments and turn prototypes into reliable observability and security products.

Build and optimize custom AI models for real-time anomaly detection across high-throughput security data. The role combines applied mathematics, model training, GPU and systems optimization, production deployment, interpretability, and ongoing model operations.

Leads the technical direction of a data semantics team while designing and scaling semantic infrastructure across observability platforms. The role requires Staff-level architectural ownership, cross-team influence, hands-on distributed-systems experience, and mentorship.

Builds and deploys machine-learning models and statistical algorithms for scalable, user-facing observability features based on streaming data. The role requires experience with high-scale datasets, production pipelines, and communicating technical concepts clearly.

Build and optimize large language model training and post-training pipelines, improving model quality, distributed performance, evaluation, and production readiness. The role requires deep PyTorch and transformer experience, strong distributed-systems and software-engineering skills, and expertise in modern LLM optimization techniques.

Builds scalable data models, standardized revenue metrics, automated pipelines, and reliable dashboards for global business analytics. Requires at least five years of analytics-related experience, strong SQL, modern data-tool expertise, and careful data validation.

Develop and deploy ML-first behavior prediction and planning systems for autonomous vehicles, forecasting the motion and interactions of road users. Requires a bachelor's degree, deep learning lifecycle expertise, and at least three years of production software experience with C++ or Python.

Optimizes distributed machine learning training and high-throughput offline inference across large accelerator clusters. The role focuses on profiling, scaling efficiency, cluster goodput, GPU performance, and cost-effective processing of autonomy data.

Build scalable data pipelines, infrastructure, and quantitative models that support experimentation, forecasting, and business decision-making. The role requires 4+ years of production data engineering experience, strong Python and SQL skills, distributed computing expertise, and a quantitative degree.

Leads forecasting initiatives by building interpretable, production-ready statistical and machine learning models for growth, revenue, compute, and profitability. Requires an advanced quantitative degree, 7+ years of applied data science experience, and strong expertise in time-series forecasting.

Own operational analytics for a computer vision review pipeline, using SQL, Python, experimentation, and statistical modeling to identify turnaround-time and cost drivers. The role partners across Operations, Finance, and Analytics Engineering to improve process visibility and efficiency.

Own financial data integration pipelines and scalable data models supporting accounting, billing, revenue, and financial reporting. The role requires 8+ years of data or software engineering experience, strong cloud warehouse and data infrastructure expertise, and the ability to lead cross-functional initiatives.

Senior Data Engineer responsible for designing and deploying scalable data infrastructure, orchestration models, and analytics tooling to enable data-driven decisions, ML products, and enterprise reporting at Vanta. Requires 4+ years data experience, software engineering mindset, modern data stack proficiency, and passion for secure, compliant data systems.

Senior Analytics Engineer responsible for designing complex data models, building scalable SQL pipelines, enabling AI tooling, and improving data infrastructure to support self-serve analytics, dashboards, and data science at Vanta. Requires 4+ years data experience, software engineering mindset, and expertise with modern analytics tools like dbt.

Build and maintain tooling, evaluation systems, quality gates, and infrastructure for MongoDB's agent skills and AI platform. Requires 2+ years building production software, developer tools, CLIs, test infrastructure, or CI/CD, with strong fundamentals in API design, testing, and reasoning about nondeterministic AI systems.

Own analytics for major institutional trading counterparties, analyzing order-level behavior, relationship economics, health, and platform-wide liquidity effects. The role requires 7+ years of relevant experience, expert SQL, strong market-structure knowledge, and the ability to support commercial partner reviews.

Leads sales and go-to-market analytics, building scalable data products and translating complex business questions into actionable recommendations. Requires 6+ years of analytics experience, strong SQL and Python skills, and the ability to influence senior cross-functional stakeholders.

The Senior Engineer will build, deploy, and support scalable Workato-based integrations across GTM business systems, particularly Quote-to-Cash workflows. The role requires 5+ years of enterprise integration experience, strong API and scripting skills, and expertise in monitoring, security, and CI/CD practices.

Builds and operates the systems, tooling, and deployment workflows that deliver Voyage embedding and reranking models across cloud marketplaces, third-party inference providers, and self-managed environments. The role requires backend or infrastructure experience, cloud and Kubernetes expertise, and familiarity with ML model serving.

Leads an embedded analytics organization supporting growth, product, markets, finance, risk, and institutional functions. The role requires 10+ years in analytics or data science, 4+ years managing teams, expert SQL, strong statistical judgment, and executive-level stakeholder partnership.