Senior Data Infrastructure Engineer responsible for building and operating reliable, low-latency streaming and batch data systems that support AI products. Requires 5+ years of production data infrastructure experience and expertise with technologies such as Kafka, Flink, ClickHouse, and Terraform.

Leads the migration and evolution of Vanta’s multi-tenant data platform, designing highly reliable ingestion, storage, and query systems at terabyte scale. The role requires staff-level distributed-systems expertise, Kafka and database fluency, and the ability to drive architecture across teams.

Conduct AI safety research across data curation, post-training, evaluations, synthetic data, and red-teaming to improve model reliability on harmful and dual-use requests. The role requires AI safety experience, Python, deep learning frameworks, and scalable technical research skills.

Build and deploy LLM-powered tools, agents, and ecosystem infrastructure with life sciences research institutions. The role requires deep scientific or biomedical research experience, production software development expertise, and the ability to translate partner workflows into scalable AI systems.

Build datasets, evaluations, and scalable data systems that improve frontier AI models on challenging biological and scientific tasks. The role partners with scientists and AI labs and requires at least two years of experience applying biology and AI, plus hands-on LLM experience.

Develops rigorous revenue attribution, forecasting, and financial models while building scalable analytical infrastructure for Finance and executive decision-making. Requires 4+ years of analytical experience, advanced SQL and data modeling, strong quantitative reasoning, and business intelligence expertise.

Build the data systems behind frontier coding models, spanning web crawling, large-scale pipelines, data quality models, and training-ready dataset infrastructure. The role requires strong distributed-systems or data-platform expertise and end-to-end ownership.

Provides technical leadership for Pinterest’s data warehouse foundation and agentic analytics platforms at massive scale. The role designs warehouse architecture, leads cross-functional initiatives, mentors engineers, and requires extensive data platform experience plus hands-on AI tooling expertise.

Leads the architecture and production deployment of real-time computer vision and perception systems, combining classical techniques with deep learning. Requires principal-level technical leadership, 6+ years of industry experience, Python, PyTorch, and real-time optimization expertise.

Leads the re-platforming of Vanta’s compliance data layer from MongoDB to schema-aware PostgreSQL across high-throughput Kafka and S3 pipelines. The role requires staff-level distributed systems expertise, migration leadership, and strong experience with relational and document data modeling.

Own and optimize an enterprise customer-support AI agent by improving prompts, conversational quality, guardrails, intent recognition, and performance. The role requires deep conversational AI experience, strong analytical skills, platform expertise, and strategic collaboration across support teams.

Analyzes and improves enterprise marketing systems, campaign data, automation workflows, and experimentation programs. The role requires 5–10 years of marketing systems experience, hands-on Marketo and Salesforce expertise, strong reporting and stakeholder-consultation skills, and a bachelor's degree or equivalent experience.

Build and scale AWS-based data infrastructure, pipelines, knowledge graphs, and APIs for a CTV performance advertising platform. The role requires production data engineering experience with Spark, Scala, AWS, SQL, and large-scale services, plus a bachelor's degree.

Evaluates AI outputs and maintains benchmark datasets to improve response quality, failure-mode analysis, and release readiness. Requires 3–5 years in data labeling, analysis, QA, or related work, plus experience with AI/ML systems, SQL, and structured qualitative evaluation.

Analyzes complex business and financial data, builds automated reporting tools, and delivers actionable insights to stakeholders across the company. Requires 1–3 years of analytical experience, strong SQL and quantitative skills, and a bachelor's degree in a quantitative field.

Leads the strategy, architecture, and hands-on development of scalable AWS data ingestion and transformation platforms. Requires expert Python and SQL skills, Terraform and cloud-native pipeline experience, and 8+ years in data engineering or backend development, with technical leadership responsibilities.

Own end-to-end development, evaluation, and production deployment of AI models serving high-volume real-time products. The role requires 5+ years of production Python experience, hands-on fine-tuning and ML operations, cloud infrastructure expertise, and strong technical ownership.

The Data Analyst I will produce and automate client-facing healthcare reports, investigate complex business questions, and deliver actionable insights in partnership with client-facing and data engineering teams. The role requires 1–2 years of analytics experience, SQL at scale, and hands-on experience with Snowflake or a comparable warehouse.

The Applied Scientist develops causal machine learning models and rigorous experiments to optimize borrower acquisition across marketing channels. The role requires a master’s degree and experience with Python, statistical modeling, machine learning, causal inference, and experimental design.

Build and optimize the production LLM inference runtime for frontier models on OpenAI’s custom silicon. The role spans scheduling, distributed execution, memory and KV-cache management, performance tooling, and hardware-software co-design.

Build and ship forecasting, promotion-effectiveness, and data-quality models using retail and CPG data. The role requires 3–5 years of data science experience, strong statistical foundations, and fluency in Python and SQL.

Build and deploy AI-powered features for conversation intelligence, developing production ML pipelines and inference services for voice and messaging data. The role requires 2+ years of applied ML experience, Python, an ML framework, NLP familiarity, and cloud infrastructure experience.

Owns the end-to-end design, build, deployment, and optimization of AI workflows inside ORA for Customer Success, spanning call preparation, guidance, grading, and follow-up. Requires 7+ years in applied AI or related solution delivery, strong LLM and data-flow expertise, and the ability to translate business problems into shipped systems.

Develops workforce dashboards, predictive models, and AI-enabled insights across the employee lifecycle. The role requires a quantitative bachelor's degree, 5–8 years of relevant analytics experience, and expertise in SQL, Python or R, visualization, statistical modeling, and HR data platforms.

The Data Scientist will use analysis, experimentation, forecasting, and statistical modeling to shape Spotify’s global audiobooks strategy across catalog, discovery, engagement, growth, and commercial initiatives. The role requires strong SQL and programming skills, business judgment, and cross-functional communication with senior stakeholders.

Build and deploy explainable machine learning, NLP, LLM, and agentic systems that power enterprise go-to-market intelligence products. The role requires 6+ years of production ML experience, strong Python and cloud skills, and end-to-end ownership from modeling through monitoring.

Build and ship locally hosted language-model capabilities for a cybersecurity product, owning training data, fine-tuning, evaluation, security, and constrained-hardware inference. The role requires strong Python, LLM serving and grounding experience, with Rust and cybersecurity knowledge valued.

Leads the operational engine for collecting and annotating real-world and simulated data used by perception and robot-learning teams. The role manages vendors and annotators, quality systems, dataset governance, dashboards, and cross-functional delivery.

Build and own production data pipelines, knowledge graph data models, and structured datasets from messy sources (PDFs, spreadsheets, telemetry) to power internal tools, dashboards, and ML models at a frontier AI compute infrastructure company. Requires experience operating depended-on pipelines, schema modeling, data quality engineering, and unstructured data extraction.

Senior software engineer developing ML-based search relevance and discovery systems, including query understanding, ranking, retrieval, and evaluation pipelines. The role requires 5+ years of search relevance experience and expertise in NLP, LLMs, or related discovery technologies.

Research fellows propose, build, validate, and publish benchmarks or evaluation methodologies for measuring frontier AI performance on economically valuable professional and scientific work. The fellowship requires a specific research pitch, relevant technical or adjacent-field background, and a commitment of at least 20 hours per week.

Leads the research agenda for humanoid robotics, developing foundation-model and reinforcement-learning methods for dexterous manipulation and deploying them on real robotic systems. Requires a PhD, strong robotics research publications, and senior-level technical leadership.

The Research Engineer will apply advances in agents and language models to build and evaluate multi-agent systems for automated code validation and review. The role requires a computer science or equivalent background, research experience, strong programming skills, and product intuition.

Leads Deepgram’s end-to-end TTS research program, setting technical direction, training and evaluating large-scale speech-generation models, and turning breakthroughs into production systems. The role combines hands-on technical leadership with building and developing a high-performing research organization.

Leads multichannel B2B demand generation and ABM campaigns for the mid-market segment, partnering with sales and marketing teams to drive pipeline. Requires 5+ years of experience, strong campaign analytics, and proficiency with Salesforce, marketing automation, and campaign operations tools.

Conduct field research and human factors analysis with pilots, operators, and customers to shape collaborative work requirements, mission autonomy design, training, and readiness assessments. The role requires human-machine teaming expertise, operational research experience, and comfort working in field and test environments.

Conducts applied human-machine teaming experimentation for autonomous systems, testing collaboration robustness, operator performance, and failure limits. Requires a relevant degree, human participants research experience, experimental and multivariate analysis skills, and eligibility for U.S. DoD security clearances.

Designs scalable, traceable operator-autonomy relationships for mission autonomy systems by translating human-machine teaming research into requirements, design patterns, and evaluation methods. The role requires expertise in human factors, cognitive systems, experimentation, multivariate analysis, and multidisciplinary systems engineering.

Develops scientifically rigorous sustainability methodologies that become product capabilities for corporate climate and ESG data. The role combines climate expertise, GHG accounting, standards interpretation, data reasoning, and hands-on collaboration with engineers and product teams.

Owns the full lifecycle of data and ML solutions, from ingestion and feature-ready datasets through production deployment and business-impact measurement. The role combines data engineering, applied machine learning, MLOps, and generative AI to build risk detection capabilities.

Build marketplace search and ranking features while supporting MLOps infrastructure, model deployment, feature stores, and real-time data pipelines. The role requires 5+ years of software engineering or MLOps experience, backend or full-stack expertise, and familiarity with cloud and machine learning tooling.

Conducts frontier AI research for health, developing and evaluating scalable training methods, models, and agents that improve medical reasoning, reliability, and real-world outcomes. Requires exceptional machine learning or biomedical AI research depth, hands-on coding and experimentation, and end-to-end ownership of ambiguous problems.

Senior Data Scientist on Coinbase’s Consumer team, using experimentation, causal analysis, advanced modeling, and product analytics to improve consumer products. The role requires strong SQL and Python skills, statistical rigor, stakeholder influence, and at least five years of relevant experience or a PhD with three years.

The Senior Analytics Engineer will architect and operate marketing data infrastructure, productionize predictive models, and enable attribution, experimentation, and customer activation. The role requires strong Snowflake, dbt, Python, SQL, and Segment expertise, plus experience with marketing data and cross-functional analytics initiatives.

Leads monetization and expansion analytics across a B2B SaaS product suite, including ARPU modeling, cross-sell optimization, predictive model operationalization, and pricing experimentation. Requires 8+ years of analytical experience plus expert SQL/Python and Snowflake/dbt expertise.

Research, prototype, and ship statistical and machine learning features that improve MongoDB’s fleet stability, release safety, resource efficiency, and operational automation. The role requires 5+ years of hands-on ML development, strong Python and systems-design skills, and a master’s degree or equivalent quantitative experience.

Build Vanta’s organizational intelligence layer by shipping prototypes, internal tools, and AI agent workflows that make cross-source data useful to EPD, GTM, and other teams. The role requires recent hands-on LLM product work, independent problem scoping, and strong judgment around AI quality, reliability, cost, and latency.

Own the systems that ingest, standardize, validate, and operationalize data signals for Vanta’s EPD organization. The role suits a hands-on builder who has recently shipped working tools or pipelines, uses AI-assisted development, and helps teammates grow technically.

Researcher focused on scaling reinforcement learning for frontier models, with ownership spanning asynchronous RL algorithms, inference and distributed training systems, and large-scale empirical studies. Requires strong Python and deep learning experience, scalable systems debugging, and rigorous research judgment.

Supports data platform improvements, modeling, analysis, and pipeline maintenance for corporate finance and analytics. The internship suits a quantitative bachelor’s or master’s student with SQL, database, and data visualization knowledge, with Python and cloud warehouse experience valued.