Develop and productionize machine- and deep-learning algorithms for biosignal and EEG data used in medical devices, clinical development, and diagnostics. The role requires 4+ years of industry experience, DSP and statistics expertise, PyTorch proficiency, and familiarity with regulated environments and production ML practices.

Build autonomy and sensor-integration software for autonomous mining vehicles, spanning perception, localization, mapping, planning, control, and field validation. Requires a bachelor’s degree, 2+ years in autonomy or embedded software, C++/Python, robotics middleware, and hands-on multi-sensor fusion experience.

Research Scientist defining and executing research on reliable long-horizon agents in enterprise environments. The role focuses on post-training and reinforcement learning, agent memory, evaluation, verification, and structured representations, combining hands-on experimentation with product delivery and publication.

Build and scale post-training, reinforcement-learning, evaluation, and inference systems for long-horizon agents operating over complex enterprise software. The role requires strong Python and PyTorch or JAX skills, distributed GPU experience, empirical rigor, and the ability to take research results into production.

Build and operate production AI agents that transform enterprise processes, data, and code. The role focuses on tool layers, retrieval, context management, evaluations, monitoring, auditability, and guardrails, requiring strong Python and TypeScript plus experience with production LLM systems and traditional machine learning.

The Media Monitoring Specialist validates coverage, writes editorial summaries, manages search strategies, and produces media analysis and dashboards for clients. The role requires media-content experience, strong analytical and communication skills, English plus another European language, and proficiency with Excel.

Build and operate distributed data applications powering large-scale audience segmentation and real-time personalization. The role requires 2–4 years of software engineering experience, backend development skills, and familiarity with databases, algorithms, and distributed systems.

The role partners with cross-functional teams to translate business needs into data problems, build pipelines, metrics, dashboards, and reports, and deliver actionable recommendations. Candidates need a relevant bachelor’s degree with three years of experience or a master’s degree with two years, plus SQL proficiency.

Build and deploy embedding, sequence, and language-model representations for Reddit Ads, taking ML projects from requirements and experimentation through production. The role requires 5+ years of end-to-end industry ML experience, with expertise in NLP or computer vision and deep-learning frameworks.

Senior Data Analyst embedded with business teams to deliver SQL-driven insights, dashboards, and ad-hoc analyses that drive decisions across member experience, finance, and investments.

Build production agent systems that plan, use tools, recover from failures, and improve over time. The role requires 5+ years of production ML or backend experience, LLM or agent deployment experience, and expertise in evaluation, tracing, observability, and agent architecture.

Own inference-stack cost and performance by optimizing serving, caching, batching, quantization, decoding, routing, and GPU execution. The role requires 5+ years in ML systems, inference infrastructure, or performance engineering, plus strong Python and systems-language skills.

Build and deploy production AI systems, including agentic workflows, RAG applications, and LLM-powered services. The role requires 5+ years of engineering experience, strong Python skills, cloud and containerization experience, and the ability to lead technical initiatives and mentor engineers.

Develop and deploy machine learning models across the full lifecycle to manage financial risk and improve customer experience. The role requires 3+ years in data science or ML, strong Python and SQL skills, statistical expertise, production engineering experience, and cross-functional collaboration.

Develop multimodal perception and authentication systems combining visual, audio, and other sensor signals for real-world AI products. The role requires machine learning expertise, practical research-to-system experience, and proficiency in Python and PyTorch with comfort in C++.

Leads an applied machine learning organization responsible for fraud detection and identity verification models, combining people management with hands-on technical direction. Requires extensive ML leadership, production modeling experience, strong Python skills, and expertise operating in sensitive risk-focused domains.

Leads and manages an applied machine learning team developing production fraud detection and identity verification models. The role combines people leadership with hands-on technical work and requires substantial ML experience, production deployment expertise, and experience in risk-focused domains.

Build and operate large-scale data acquisition pipelines, distributed processing systems, and production Java services across batch and streaming workloads. The role requires 5+ years of backend or data engineering experience, strong distributed-systems expertise, and proficiency with cloud data technologies.

Senior software engineer responsible for building AI agents, developer tooling, and automation that improve planning, coding, testing, code review, CI, and local development workflows. Requires 6–8 years of software engineering experience, hands-on agentic coding tool experience, and proficiency in Python or JavaScript/TypeScript, AWS, and PostgreSQL.

Build and operate scalable monetization data platforms, pipelines, models, and quality systems spanning product, financial, and operational data. The role partners with Product Engineering, Finance, Accounting, Analytics, and GTM teams to deliver reliable, observable data products.

Leads an analytics engineering team that transforms raw data into reliable, actionable insights for product, marketing, and operations. The role requires 7+ years in data or analytics engineering, management experience, and advanced SQL, Databricks, and dbt expertise.

Build and operate production machine-learning systems for search ranking, relevance, extraction quality, and LLM-driven features. The role requires production ML ownership, ranking or relevance expertise, large-scale data experience, Python, and rigorous experimentation skills.

Build evaluation methods, RL environments, agent tooling, and scalable infrastructure that make subjective qualities such as design and taste measurable for frontier AI models. The role requires experience with evaluations, RL environments, ML or post-training, plus strong backend engineering skills.

This staff-level data engineer will architect and operate low-latency market data infrastructure, including feed handling, normalization, distribution, and exchange connectivity. The role requires at least five years of backend engineering experience and strong Java or C++ expertise with high-throughput messaging and market data protocols.

Develop and deploy machine learning systems for Instacart’s advertising ecosystem, spanning data pipelines, model architectures, serving, experimentation, and optimization. The role requires a graduate degree and strong programming, analytical, and collaboration skills, with experience in large-scale ML systems preferred.

Own the end-to-end lifecycle of memory features for AI agents. Fine-tune models, implement research, build evaluations, and ship production systems with Engineering.

Senior Data Scientist who will characterize conversational audio data, build active-learning and human-in-the-loop systems, and develop repeatable model-improvement pipelines. The role requires strong Python and data-pipeline experience, familiarity with speech or NLP models, and the ability to turn ambiguous data problems into measurable gains.

Develop and deploy production machine learning models for real-time inventory and shelf-stocking intelligence at scale. The role requires 5+ years of production ML experience, strong Python and ML framework skills, cloud and data pipeline expertise, and a bachelor's degree or equivalent experience.

Senior Research Engineer tailoring and deploying machine learning models for partner applications across geospatial and environmental domains. The role requires PyTorch expertise, end-to-end ML deployment experience, geospatial tools knowledge, and strong independent execution.

Leads the analytics engineering function, owning data architecture, modeling standards, semantic layers, governance, and roadmap execution while managing and developing the team. The role requires deep SQL and dbt expertise, dimensional modeling experience, cloud data warehouse knowledge, and strong senior-stakeholder communication.

Staff Machine Learning Engineer building and operating production ML systems for causal marketing measurement, optimization, and planning. The role requires deep statistical and machine learning expertise, production programming experience, cross-functional collaboration, and technical mentorship.

Architects scalable data systems and platforms using distributed technologies like Spark, Kafka, and AWS. Mentors engineers and drives innovation on large-scale data projects, requiring 8+ years experience and expertise in data infrastructure.

Own the operational reliability, governance, and lifecycle maintenance of production AI solutions for public-sector and enterprise customers. The role combines software engineering, MLOps, incident management, automation, model monitoring, and senior client communication.

Build and operate quantitative risk models, pricing tools, and real-time monitoring systems for futures trading while supporting live trading and applying AI techniques. The role requires 5+ years of quantitative, risk, or trading-systems experience, advanced Python skills, and strong futures-market knowledge.

The Health Economist leads claims-based ROI and health economics studies for digital MSK care, translating complex data into commercial insights and published research. The role requires a graduate quantitative degree, 3–5 years of applied econometrics and claims database experience, and strong R, SQL, or Python skills.

Leads Discord’s Safety ML team, setting technical direction and overseeing production machine learning systems for content understanding, account integrity, and platform abuse. Requires substantial machine learning and engineering management experience, hands-on technical depth, and experience delivering ML systems at scale.

The Principal AI Engineer architects enterprise-grade AI/ML platforms and GenAI infrastructure, establishing standards for agentic systems, RAG, model serving, observability, security, and multi-cloud deployment. The role requires 8+ years in cloud architecture and platform engineering, including substantial AI/ML infrastructure experience.

Senior individual contributor responsible for defining, operationalizing, and improving performance metrics for enterprise AI agent deployments. The role combines customer-facing advisory work, quantitative analysis, experimentation, and building scalable measurement tools and frameworks.

Conduct speech technology research on text-to-speech, ASR, speech-to-speech, and speech analysis models during a six-month project. The role requires a relevant master's qualification or PhD study, neural-network development experience, and Python skills.

Senior Data Scientist supporting Discord’s experimentation platform by improving experimental rigor, statistical methodology, and causal inference practices. The role requires a quantitative master’s degree, experience with experiments or causal inference, strong cross-functional education skills, and proficiency in Python, SQL, and R.

Develop forecasting and scenario-planning capabilities for autonomous fleet operations, covering staffing, demand, charging, supply, and infrastructure. The role suits a currently enrolled quantitative-discipline student with experience in statistical modeling or machine learning and strong analytical communication skills.

Own product and customer analytics across financial product experiences, turning behavioral data and customer feedback into roadmap recommendations and business decisions. The role requires 4–8 years of analytics experience, advanced SQL, strong analytical judgment, and daily fluency with AI-powered tools.

Leads Clay’s Data Science and Analytics team, managing data scientists and analytics engineers while setting technical standards and measurement frameworks. The role partners with executives and cross-functional leaders to shape product and business strategy through experimentation, analytics, and data storytelling.

The Data Scientist will shape analytics strategy and deliver forecasting, experimentation, optimization, dashboards, models, and decision tools for Real Estate & Workplace operations. The role requires strong applied statistics, causal inference, SQL, Python, stakeholder communication, and comfort working with ambiguous operational data.

Build and ship production AI/ML systems for real-time incident management, including LLM agents, retrieval pipelines, and inference services. The role suits an early-career software engineer with 2+ years of production experience and hands-on experience with modern AI.

Build and operate production AI systems, including LLM agents, retrieval pipelines, and event intelligence, across PagerDuty’s high-scale distributed platform. The role requires 5+ years of software engineering experience, production distributed-systems expertise, and hands-on experience shipping reliable LLM applications.

Owns end-to-end production machine learning systems, including NLP, LLM, agentic, ranking, and recommendation capabilities. Requires 8+ years of industry experience, strong Python and cloud ML expertise, and the ability to deliver explainable AI products with cross-functional and customer impact.

Build and optimize Ray Data, a Python-native data processing engine for large-scale AI workloads. The role focuses on distributed systems performance, scalable data pipelines, production training solutions, and fault tolerance while partnering with AI-focused customers.

Own credit and product analytics for consumer liquidity products, shaping underwriting strategy, portfolio risk policies, and new product launches. The role requires 4–8 years of credit analytics experience, advanced SQL, AI capabilities, and strong quantitative problem-solving skills.

Six-month remote internship for final-year Computer Science students working across AI and data engineering. Residents develop and evaluate machine learning models, build backend and data pipelines, and analyze large datasets while receiving mentorship and a monthly stipend.