Develop and deploy responsible AI and machine learning fairness solutions across Pinterest’s large-scale, user-facing products, including generative AI, search, and recommendations. The role requires production ML experience, expertise in fairness interventions and modern architectures, and a master’s or PhD in computer science or a related field.

Lead the development and maintenance of scalable data pipelines, warehouse, and transformation layer using modern data stack. Collaborate with data scientists and analysts to ensure clean, reliable data for insights in a high-growth startup.

Build and operate backend infrastructure for machine learning model training, serving, feature management, and marketplace simulation. The role requires 6+ years of software engineering experience, distributed systems expertise, and experience with production ML platforms.

Leads the design and operation of highly available distributed data platforms and pipelines at Snowflake, while providing technical leadership across teams. Requires 12+ years of distributed-systems experience, cloud expertise, and strong database and system-design depth.

Build and operate production machine-learning systems for content safety, from messy customer data through classification, evaluation, and inference. The role requires 5+ years of ML engineering experience, strong Python and MLOps skills, and sound judgment across classical models and LLMs.

Manages alternative-investment data operations, including security-master oversight, workflow controls, document interpretation, and high-volume data validation. The role requires investment-industry knowledge, strong SQL and Databricks/PySpark skills, and the ability to troubleshoot ingestion pipelines and apply AI tooling.

Build analytics data models, pipelines, dashboards, and AI-enabled automation for product and operational decision-making. The role requires 2–3+ years of data engineering or analytics experience, advanced SQL, dbt, cloud data warehouse, Python, and BI expertise.

Senior individual contributor responsible for architecting and scaling production data ingestion systems that integrate complex enterprise sources into reliable datasets. Requires 5+ years of backend engineering experience, strong Python, cloud, Kubernetes, Postgres, and data integration expertise.

Build the tasks, rewards, environments, and data systems used to train and evaluate coding agents. The role requires strong software engineering fundamentals and experience with infrastructure, data, or distributed systems; reinforcement learning experience is a plus.

Investigates and mitigates escalated payments fraud across fiat payment rails, analyzing risk patterns and improving detection and operational processes. Requires 3+ years of payments risk or fraud experience, SQL proficiency, and willingness to work shifts in an in-office Hyderabad role.

Leads architecture and technical governance for an enterprise-scale data platform, driving distributed systems, data modeling, cloud infrastructure, and operational best practices. Requires 7+ years of engineering experience and a bachelor’s degree.

Trains and fine-tunes large-scale diffusion transformer models for image and video generation, conducts rigorous ablation studies, and optimizes distributed training. Requires hands-on diffusion-model experience, strong PyTorch and transformer expertise, and understanding of generative-model evaluation.

Build and operate AI-powered, customer-facing workflows for Datadog Notebooks, combining reliable backend systems with LLM capabilities. The role requires 6+ years of engineering experience, Go or Python expertise, and experience delivering production AI products.

Leads the platform, evaluation, governance, economics, and internal enablement required to operate AI systems reliably in production. Requires hands-on ML/AI, data platform, or AI operations experience, strong LLM fluency, and the judgment to guide investment and build-versus-buy decisions.

Own applied multimodal ML research from clinical problem definition through production, developing and rigorously evaluating computer vision, NLP, and deep learning systems for radiology. Requires strong Python and PyTorch expertise, 4+ years of relevant experience, and an MS, PhD, or equivalent practical experience.

Researcher developing internal evaluations and research signals for AI post-training, including usability, correctness, auditing, agentic systems, and nuanced model behaviors. Requires evaluation experience, strong research judgment, Python, and familiarity with deep learning frameworks.

Leads data strategy and operations for frontier AI research, including vendor partnerships, data pipelines, evaluation frameworks, and quality standards. Requires at least 3 years of operations, consulting, product, or program management experience and familiarity with AI training or LLMs.

Entry-level data scientist developing machine learning models and analytical methods to detect fraud, assess risk, and uncover patterns in large transactional datasets. Requires a master’s degree, strong Python and SQL skills, and knowledge of supervised and unsupervised learning.

Own the shared AI foundation powering Aleph’s financial planning products, including model routing, context and tool systems, evaluations, and observability. The role requires Staff-level experience shipping production LLM and agentic systems, strong technical judgment, and a pragmatic builder’s mindset.

Own the credibility of a military simulation’s entity catalog by defining data standards, quantitative performance models, AI-assisted production workflows, and continuous validation. The role requires strong analytical judgment, documentation, organization, and the ability to defend modeling decisions to customers and subject-matter experts.

The Director of Analytics & Reporting will build and lead a hands-on, centralized analytics function for value-based cardiology contracts, owning metric definitions, semantic data models, payer reporting, and executive dashboards. The role requires 8+ years of healthcare analytics experience and deep expertise in claims, clinical, and value-based care data.

Research Scientist responsible for measuring and improving how frontier models learn from tasks, designing post-training experiments, validating data quality, and creating datasets and evaluation systems. Requires production reinforcement-learning experience at a frontier lab and end-to-end LLM post-training experience.

Own growth and product analytics for activation, retention, expansion, and monetization, using experiments, SQL, AI automation, and product analytics tools. The role partners cross-functionally to turn insights into pricing improvements, product changes, and shipped growth initiatives.

Analyzes, validates, and reports on operational data while supporting UK and European clients with data-related issues. The role requires strong SQL, BI, database, reconciliation, and communication skills, with at least two years of relevant experience.

Build and teach reliable AI agent systems through customer workshops, technical content, guidance, and reference implementations. The role requires strong Python and agent-development experience plus a background delivering customer-facing technical training.

Own the architecture, delivery, evaluation, and production operations of AI capabilities embedded in procurement and finance workflows. The role requires 10+ years in applied AI or machine learning, deep LLM and agent expertise, and experience delivering measurable production outcomes.

Analyzes transaction enrichment performance, investigates data-quality anomalies, and builds dashboards and monitoring to improve product accuracy and reliability. Requires 3–5 years of analytical experience, strong SQL and Python, and experience with BI and automated alerting.

The first dedicated Trust & Safety data scientist will define ecosystem metrics, run experiments, evaluate safety models, and shape the roadmap with Product, Engineering, and Legal. Requires 6–8 years of data science experience, Trust & Safety or adjacent domain expertise, and strong SQL and Python skills.

Build and operate biomedical retrieval, ranking, and concept-mapping systems that ground LLM applications for rare disease research. The role requires at least five years of production software or data-systems experience, including two years delivering LLM-powered applications, plus strong retrieval and Kubernetes skills.

Build and operate agentic AI systems for rare disease research, including typed workflows, evaluation, observability, and production deployment. The role requires a bachelor’s degree or equivalent experience, 5+ years building production systems, and 2+ years shipping LLM-powered applications.

Build AI agent harnesses, models, and product capabilities that enable agents to perform complex work across digital environments. The role combines applied AI research and software engineering, requiring Python proficiency, strong product judgment, and experience with agent tooling, reinforcement learning, or browser technologies.

Build and validate production quantitative risk models for derivatives clearing, including volatility, correlation, stress testing, margin, and automated liquidation. The role requires 5–7 years of quantitative risk experience, expert Python skills, and an advanced quantitative degree or equivalent experience.

Build and deploy secure enterprise AI agents, integrations, and automated workflows that improve internal productivity and business operations. The role requires at least five years of enterprise, software, automation, or IT systems engineering experience, plus hands-on workflow and LLM application development.

Research Scientist focused on evaluating frontier language and multimodal models, diagnosing failure modes, and building rigorous benchmarks. The role requires advanced training in AI or a related field, post-training expertise, and published machine learning research.

Research novel post-training methods for large language models, focusing on preference optimization, data curation, evaluation, alignment, and robustness across text and multimodal systems. Requires advanced academic training and experience with deep learning, reinforcement learning, and post-training techniques.

Analytics Engineer supporting Go-to-Market teams by building scalable data models, metrics, pipelines, visualizations, and self-service products. The role requires 10+ years of data experience, deep SQL expertise, Python proficiency, and strong business judgment.

Lead advanced analytics for host acquisition at Airbnb, driving data analysis, metric definition, experimentation, and strategic insights to support growth initiatives.

Leads Finance Analytics strategy, team development, scalable data products, and AI-powered workflows that improve financial decision-making and operational efficiency. Requires 8+ years in analytics or data engineering, people management experience, strong SQL/Python skills, cloud data-platform expertise, and Finance domain experience.

Build and deploy production machine-learning models and data systems that classify and enrich Internet telemetry for internal platforms and customer-facing products. The role requires 5+ years of applied ML, data science, or software engineering experience, plus strong Python or Go skills.

Leads development and integration of advanced maritime autonomy for USVs, UUVs, and cooperating UAVs, including motion planning, localization, safety, and multi-agent coordination. Requires staff-level technical leadership, substantial robotics experience, C++ and Python proficiency, and eligibility for a SECRET clearance.

Senior individual contributor who architects and builds end-to-end people data systems, predictive models, and AI-agent workflows. Requires 8+ years of experience across data engineering and data science, with expertise in Python, SQL, machine learning, sensitive HR data, and agentic AI.

Leads technical direction and develops maritime autonomy capabilities for unmanned surface and underwater vehicles, including motion planning, localization, safe behaviors, and heterogeneous multi-agent collaboration. Requires deep robotics and unmanned-systems experience, strong C++/Python skills, and senior technical leadership.

Leads a hands-on GTM analytics team supporting Marketing, Sales, and Customer Operations through trusted reporting, forecasting, experimentation, and self-service automation. Requires 6+ years of analytics experience, at least 1 year of team management, strong SQL, GTM expertise, and advanced analytical judgment.

Research and engineer AI systems, optimizing and evaluating machine-learning models and on-device performance across desktop and mobile products. The role requires software development experience, systems and networking knowledge, and expertise with modern ML frameworks, privacy, and security.

Build and operate scalable data infrastructure, including partner data sharing, identity graph foundations, and governed batch and real-time platforms. The role requires 5+ years of data, distributed systems, infrastructure, or backend engineering experience and strong cloud and data-platform expertise.

Analyzes talent acquisition data, builds recruiting dashboards, and leads cross-functional process and system improvements. The role requires 5+ years in recruiting or business analysis, hands-on AI use, and experience with ATS, HRIS, and reporting tools.

Build data models, analyses, forecasts, automated dashboards, and AI-augmented analytics products for Finance and go-to-market operations. The role requires 2–4 years of analytical or analytics engineering experience, strong SQL and Python skills, and a quantitative degree.

Analyzes workforce data, builds dashboards, performs statistical and predictive analysis, and applies NLP and generative AI to employee feedback. Requires a bachelor's degree and 3–5 years of analytics experience, with strong SQL, Tableau, Snowflake, and HR-platform expertise.

Build and integrate AI/LLM capabilities for a customer and partner portal, including RAG, agents, retrieval systems, and evaluation pipelines. The role requires 3+ years of AI/ML engineering experience, strong Python skills, and production experience serving and evaluating LLMs.

Build and operate scalable enterprise data pipelines, models, and platform infrastructure across the full data lifecycle. The role requires 5+ years of experience, strong SQL and Python, and deep expertise in Snowflake, dbt, and Airflow.