Build and operate the platform that deploys, serves, observes, and retrains production machine-learning models for real-time fraud and financial-crime risk decisions. Requires 5+ years of ML engineering, backend, or MLOps experience, strong Python skills, and production model-serving expertise.

Staff-level engineer responsible for building AI agents and automation, evaluating developer AI tools, and driving adoption across the engineering organization. Requires 8+ years of software engineering experience plus production experience with LLMs, agentic systems, and applied machine learning.

Build and ship autonomous, agentic software development lifecycle capabilities, including AI agents, orchestration, and safety guardrails. The role requires senior software engineering experience, proficiency in Ruby, Go, or Python, distributed systems knowledge, and experience with AI/ML applications.

Build and operate production AI agents for finance workflows, owning orchestration, evaluation, reliability, and human-in-the-loop safeguards. Requires 8+ years building SaaS products, 2+ years shipping agentic systems, and hands-on Node.js and TypeScript experience.

Staff machine learning engineer leading scalable ranking, search, recommendation, and personalization systems. The role requires 9+ years of applied machine learning experience, strong programming and data engineering skills, and expertise productionizing models and pipelines.

Build production AI capabilities for automated slide and document generation, working across LLM applications, data analysis, and content generation. The role requires 3+ years in machine learning and NLP, advanced Python, and experience with LLM frameworks and production systems.

Build and operate large-scale ranking and retrieval systems that power search relevance, including hybrid lexical/vector search, embeddings, query understanding, and permission-aware retrieval. Requires a bachelor's degree and 5+ years of ML engineering experience in ranking or information retrieval.

Build and operate LLM-powered agents that automate business workflows, integrating systems of record through MCP and validating behavior with structured evaluations. Requires 5+ years of software development experience, strong Python and SQL, and hands-on experience shipping agents to production.

Leads development of speech models, decoders, and low-latency inference systems for next-generation voice agents. Requires 5+ years in speech ML or related audio AI, strong Python and PyTorch experience, and the ability to guide technical direction and mentor engineers.

Leads the production AI platform and internal AI adoption strategy, overseeing pipelines, evaluations, monitoring, reliability, cost controls, governance, and enablement. Requires substantial hands-on experience operating ML/AI systems and strong judgment across technical and executive stakeholders.

Sets the technical direction for production machine learning across a payments platform, building and scaling models for risk, authorization, disputes, and forecasting. Requires 8+ years of ML engineering experience, including production model ownership and strong technical leadership.

Build and operate production machine learning systems for ranking, retrieval, recommendations, personalization, and customer intelligence. The role requires 12+ years of production software and ML experience, strong expertise in intelligent systems, and sound judgment around trustworthy customer-impacting signals.

AI Engineering Intern building generative AI agents and RAG pipelines to automate internal engineering workflows and improve productivity. Requires Python, AI/ML and LLM project experience, Git familiarity, and current enrollment in a technical degree program.

Design and productionize ML, deep learning, and LLM models for personalization, recommendations, and search systems. Requires 7+ years building production ML/AI with business impact and strong cross-functional collaboration skills.

Own and evolve Hugging Face’s open-source voice-agent stack and bring hf-voice from demo to production. The role requires senior experience with Python, distributed real-time systems, developer infrastructure, and production AI or multimodal models.

Build and productionize generative AI applications for U.S. federal customers, advise clients, and influence product direction. The role requires extensive data science and machine learning deployment experience, a graduate quantitative degree or equivalent experience, and U.S. security clearance eligibility.

Build and scale production machine-learning pipelines and evaluation systems powering generative AI music experiences. The role requires hands-on LLM, prompt-engineering, data-pipeline, cloud, and user-facing product experience.

Build the technical foundation for a new business vertical, creating reusable infrastructure and leading early customer engagements from scoping through delivery. The role requires 3+ years of engineering experience, strong Python and SQL skills, backend/data expertise, and comfort operating in ambiguity.

Build and operate low-latency machine learning systems for ad ranking, relevance, and optimization, including feature pipelines, experimentation, evaluation, and production inference. The role requires 6+ years of software engineering experience, strong Python skills, AWS experience, and practical LLM application experience.

Deploy and optimize frontier AI models for fast, reliable, real-time production serving at scale. The role requires production ML serving experience, GPU programming and inference optimization expertise, and the ability to diagnose bottlenecks across the serving stack.

Build and deploy machine learning systems that apply economic theory, econometrics, and causal inference to marketplace problems. The role requires advanced training in economics, strong Python and data skills, and production ML experience for senior-level hires.

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 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 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.

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 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.

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.

Senior machine learning engineer who will build and operate large-scale AI systems for Airbnb’s payments ecosystem, including LLM agents, fraud defenses, and personalization. The role requires 5+ years of applied AI/ML experience, strong Python or Java skills, and production MLOps expertise.

Research Scientist II building and improving fraud risk models and scam detection systems using audio, behavioral, and metadata signals. Requires an advanced degree and 3+ years of applied ML experience with Python and modern ML frameworks.

Build reinforcement-learning environments, evaluations, datasets, and scalable infrastructure for frontier AI capabilities. The role suits a high-agency generalist engineer with experience in agents, evaluations, or RL workflows and strong communication skills.

Senior Staff ML Engineer fine-tunes and optimizes state-of-the-art LLMs for Airbnb's customer support AI products, including AI assistants and autonomous agents. Partners cross-functionally to productionize models at scale. Requires PhD and 10+ years experience with PyTorch.

Leads technical strategy for Reddit’s Ads ML Platform, improving feature development, training-data generation, experimentation, and the path to production ML serving. The role requires 8+ years in infrastructure or distributed systems, production ML platform experience, and strong cross-team technical leadership.

Own the architecture and delivery of production AI systems for patient-provider matching, search relevance, personalization, clinical workflows, and engagement. The role requires extensive software engineering, distributed systems, search or recommendation, ML applications, and foundation-model experience in a regulated healthcare setting.

Build production AI agents and the distributed platform that operates large-scale GPU infrastructure. The role requires 5+ years of backend, distributed systems, or infrastructure experience, with expertise in agent systems, knowledge graphs, retrieval, or semantic search.

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 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.

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 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.

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.

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.

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.

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.

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.

The Senior Algorithm Engineer leads development and production deployment of machine and deep learning algorithms for biosignal and medical-device applications. The role requires 5+ years of industry experience, DSP and statistics expertise, PyTorch proficiency, and familiarity with regulated health or similar domains.

Build and operate production AI agent systems that help Sales and Marketing teams with account planning, deal support, competitive intelligence, and content creation. The role requires 6+ years of experience shipping reliable LLM workflows with retrieval, tool use, permissions, evaluation, and observability.

Principal technical leader defining architecture and multi-year strategy for Pinterest’s Homefeed, Search, and AI Assistant experiences. The role requires 15+ years of large-scale systems or machine-learning experience, deep expertise in discovery and generative AI, and hands-on leadership across engineering and product organizations.

Leads the design, deployment, and optimization of agentic and generative AI systems that automate risk and compliance investigations at scale. Requires 8+ years of machine learning modeling experience, production ML expertise, and advanced technical education.

Build and productionize post-training systems for voice and text agents, including environments, verifiers, synthetic data, evaluations, and model training. The role requires strong Python and end-to-end model development experience, with reinforcement learning and distributed training expertise preferred.