Quantitative Researcher responsible for analyzing execution data, developing market impact and trading cost models, and optimizing execution strategies across equities, futures and other asset classes to minimize transaction costs. Requires 3+ years in electronic execution at a quant trading firm, strong quantitative skills, and Python proficiency.

Data Scientist building measurement systems, risk models, and experiments to detect and mitigate AI-native abuse, fraud, and adversarial behavior on Replit's platform while minimizing impact on legitimate users. Requires 5+ years in data science or fraud/risk, strong SQL/Python, and experience with imperfect labels and high-stakes decisions.

Senior R&D Software Engineer building the governed context layer (Agents Schema and Context Builder) for trustworthy AI agents. Research, prototype, and ship production full-stack features across backend, frontend, SRE, and QA in a fast-moving startup-like AI team.

Build and operate scalable ML training frameworks, distributed infrastructure, and model lifecycle tools to power foundational models, reinforcement learning, and other ML use cases across Zoox's autonomous driving teams. Requires 2+ years ML infrastructure experience with PyTorch, DeepSpeed, JAX, Ray and AWS.

Build, evaluate, and productionize ML/AI models (including LLMs and NLP) that solve ambiguous healthcare, product, and operational problems at Sprinter Health. Requires strong experimentation, error analysis, stakeholder collaboration with clinicians, and focus on real-world impact, bias, and evaluation.

Build and maintain canonical data models, metric definitions, and dbt transformations to create a trusted, reusable data layer for internal teams and payer customers in a healthcare startup. Requires expert SQL, dbt experience, metric reconciliation, and a product-oriented approach to data quality and documentation.

Build and lead the first ML engineering function at Sprinter Health. Design and implement production ML platforms for training, serving, features, monitoring, retraining and governance; productionize models from prototype to reliable systems in a healthcare startup environment.

Part-time student role analyzing highway data for autonomous vehicles. Responsibilities include building Databricks notebooks for scenario mining and dashboards, conducting exposure analysis on vehicle logs, and writing data reports. Requires strong SQL, PySpark, and Python skills plus current enrollment in a CS/Data Science/Engineering program.

Build and maintain Lyft's ETA prediction system using ML models for ride matching, pricing, and user experience. Requires 3+ years ML experience, production code for high-scale low-latency systems, and tradeoff decisions on accuracy vs performance.

Staff Software Engineer owning architecture and technical direction for scalable data integrations platform handling clinical/financial data with EMRs. Requires 10+ years experience building distributed systems, high-throughput pipelines, and deep infrastructure knowledge (GCP/K8s, databases, networking).

Build and operate high-performance inference systems across kernels, runtimes, serving infrastructure, and heterogeneous clusters while owning customer workloads in production. The role requires exceptional production engineering, customer-facing technical judgment, and the ability to solve ambiguous problems independently.

Lead and mentor a team of Data Validation Specialists in an investment management firm. Oversee data validation projects, drive process improvements, ensure high-quality delivery, and collaborate cross-functionally with Sales, Product, and Engineering teams. Requires 3+ years in data validation or financial operations plus leadership experience.

Build and ship AI-powered customer products by turning ML prototypes into robust, scalable production systems. The role requires staff-level software engineering expertise, 10+ years of product experience, strong programming fundamentals, and collaboration with scientists and product teams.

Build and optimize large-scale training pipelines and low-latency inference services for Fin’s AI models. The role requires strong software engineering experience, hands-on expertise in model training, inference, or GPU programming, and collaboration with ML scientists.

Applies machine learning research and experimentation to identify customer value, evaluate algorithms, and ship product prototypes with engineering teams. Requires 3–5 years of applied ML experience, strong statistical and programming skills, and typically advanced education in ML or a related field.

Partners with product teams to use statistical analysis, data pipelines, and quantitative research to guide product strategy and measure outcomes. The role requires 5+ years of experience, strong SQL and Python skills, product intuition, and growing proficiency with AI-assisted workflows.

Build and deploy AI-powered internal tools and data products for go-to-market teams, from rapid prototyping through production. The role requires applied data science experience, strong SQL and Python or R skills, LLM application expertise, and the ability to measure business impact.

The Data Scientist partners with product teams to define metrics, analyze user and product data, run experiments, build pipelines and dashboards, and deliver insights that shape product strategy. The role requires 5+ years of experience, strong SQL and analytical skills, and proficiency in Python or R.

Build production-grade forecasting, propensity, and LTV models that connect customer behavior and product usage to SaaS revenue outcomes. The role requires advanced Python and SQL, scalable data-pipeline experience, and the ability to communicate insights to finance and executive stakeholders.

Leads and grows a team of ML scientists delivering user-facing machine learning products, while providing technical guidance and collaborating across ML, engineering, product, and design. Requires 5+ years of individual ML, AI, NLP, or data-related contributions and strong applied ML and coding skills.

Build and ship AI-powered customer support products, moving ML prototypes into robust production systems while partnering closely with scientists, product, and design teams. The role requires strong software engineering fundamentals, 5+ years of product experience, and proficiency in a high-level programming language.

The Staff Machine Learning Scientist identifies and frames product opportunities, researches algorithms, evaluates models, and partners with engineers to ship impactful ML products. The role requires 5–8 years of applied ML experience, technical leadership, strong programming, and advanced ML education.

Lead a team of ML engineers building and scaling production ML systems for Fetch's Ad Platform, including ad ranking, targeting, bidding, and optimization. Requires 8+ years technical experience (2+ managing teams), strong ML lifecycle and production systems expertise, and cross-functional partnership skills.

Build and deploy large-scale online ML models and end-to-end pipelines for real-time fraud detection at Sift, working on automated training systems that process over 1T events. Requires 4+ years production ML experience, strong Python/Java/Scala skills, and distributed systems expertise with Spark, Databricks, and GCP.

Build and lead Traba's agentic platform as a founding member of the Agents team. Architect orchestration, evals, model strategy, and integrations for autonomous AI agents in industrial supply chain workflows. Requires 7+ years engineering experience including 2+ years production LLM/agent systems, strong Python/TS skills, and customer immersion.

Intern building AI prototypes using computer vision and LLMs to automate blueprint reading, cost estimation, and permitting in construction. Requires ownership from research to production, growth mindset, and comfort with unglamorous work.

Marketing Insights Analyst responsible for owning marketing performance reporting, ROI analysis, and data-driven recommendations on investment mix, pipeline drivers, and experimentation. Requires 5-8 years B2B SaaS marketing analytics experience, strong SQL, BI tools, and business judgment to advise leadership.

Model and analyze capacity (power, space, cooling, compute) across AI data center fleet. Track consumption, build executive reporting, and run scenario analysis to inform allocation and deal decisions. Requires infrastructure capacity analysis experience and SQL/Python modeling skills.

Build and ship production-grade AI agents, assistants, and reusable skills for security-focused solutions. The role requires hands-on experience with agent frameworks, evaluation, Python, cloud integrations, and containerization, plus a bachelor's or master's degree or equivalent experience.

Senior Data Analyst shaping data models, metrics, and insights for Finance, Product, Growth and Operations teams. Build end-to-end from raw data to customer-facing dashboards and products on a modern stack (BigQuery, dbt, Hex). 6+ years analytics experience required.

Build and manage scalable MLOps infrastructure, automated ML pipelines, model serving, and monitoring for a Large Tabular Model (LTM) at an enterprise AI company. Requires 5+ years MLOps/DevOps experience with Kubernetes, PyTorch/TensorFlow, and cloud infrastructure.

Staff Data Scientist defining company-wide standards for experiment design, causal inference, and statistical analysis to drive trustworthy product decisions in a fast-paced multi-product SaaS environment. Requires 9+ years experience with online experiments, strong applied statistics, and practical causal inference.

Build and deploy the ML-based perception system (3D detection, BEV, tracking, sensor fusion) for L4 autonomous trucks, owning models from architecture through onboard deployment and safety validation. Requires 5+ years in ML perception/robotics, strong Python/C++/PyTorch, and classical perception fundamentals.

Staff Deep Learning Research Engineer designing and training novel neural network architectures from scratch for Generalized Scene Reconstruction tasks including anomaly detection, neural rendering, and 3D reconstruction. Requires PhD/Master's, 6+ years deep learning research experience, expertise in 3D vision or SLAM, and hybrid work in Columbia, MD.

Senior Offline Mapping Engineer owning accuracy and robustness of offline SfM, multi-view stereo, and 3D reconstruction pipelines. Integrates classical geometry with deep learning (learned matching, depth priors) for challenging real-world environments like textureless and reflective scenes. Requires advanced degree, production 3D vision experience, and hybrid work in Columbia, MD.

Build and optimize high-performance ML inference services and APIs that turn frontier research models (FLUX, Stable Diffusion) into production systems serving millions of requests. Requires experience scaling ML serving infrastructure, GPU optimization, and production backend systems.

Build and maintain demand, lead-time, and capacity forecasts for critical data center equipment to keep multi-GW AI compute build pipelines on schedule. Partner with procurement using data-driven models and dashboards to mitigate risks and optimize multi-hundred-million-dollar commitments.

Model and track greyspace capacity (electrical, mechanical, support space) across data center sites to ensure constraints are identified early. Build source-of-truth views, analyze trade-offs, and support design/delivery/operations teams with data center or industrial planning experience.

Build and own the facilities data pipeline for AI data center telemetry, including ingestion from industrial protocols (BACnet, Modbus, OPC UA), data quality tooling, and serving clean APIs/datasets for dashboards, controls, and ML. Requires production data pipeline experience with on-call ownership, industrial protocol integration, and full-stack debugging.

Lead the design, architecture, and implementation of a large-scale facilities telemetry platform for AI data centers, ingesting sensor data from industrial protocols into queryable time-series systems while setting data standards and leading a small team.

Build and own ML/LLM systems for internal operations including forecasting, risk flagging, and document extraction. Ship production agentic systems end-to-end with guardrails and partner with data engineering to integrate predictions into tools.

Model and reconcile IT/hardware capacity needs across data center sites, building automated views for planning and procurement while chasing discrepancies in orders, inventory, and lead times.

Build and productionize agentic LLM-powered triage systems and ML/DL pipelines to automate failure analysis for autonomous robots. Requires Master's/PhD in STEM + 4+ years production ML/NLP experience with PyTorch, RAG, Databricks, and AWS.

Clinical Informatics Specialist embedded in product team to generate, annotate, and evaluate clinical datasets for medication-focused AI models. Serves as pharmacy SME to ensure AI outputs align with real-world clinical practice, safety standards, and regulatory requirements while collaborating with engineers, data scientists, and PMs.

Senior Manager overseeing ML data operations and labeling quality at Coalition. Define guidelines and metrics, drive Label Studio platform requirements, manage vendors, and partner with ML teams to ensure high-quality labeled datasets for models.

Principal Software Engineer building a new Identity Graph platform for real-time identity resolution, fraud, and risk on the Stytch team at Twilio. Own architecture, high-scale distributed systems, complex data pipelines, and synchronous read models while mentoring the team.

Founding member of a new team building foundational evaluation infrastructure and flywheels for Databricks' AI/Genie Agents. Design scalable tooling for benchmarking, regression detection, and quality measurement that drives continuous agent improvement across research, training, and production.

Technical leader for Airbnb’s Unified Data Store client stack, responsible for long-term architecture, distributed data access, reliability, and developer experience. Requires 9+ years of industry experience and deep expertise in large-scale distributed systems.

Applied Scientist building optimization, forecasting, and simulation models to solve complex logistics and clinician-patient matching problems for in-home healthcare delivery. Requires strong operations research foundations, Python/SQL/ML expertise, and experience shipping production decision systems.

AI Research Scientist advancing methodological frontiers in healthcare AI at Sprinter Health. Own a research agenda, develop novel architectures/methods, publish at top venues, collaborate with clinicians, and translate findings into production systems. Requires deep ML expertise, strong research taste, and healthcare validation knowledge.