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Software Engineer in Natural Language Processing (NLP) and Machine Learning (ML)
Are you interested in building amazing Generative AI experiences that will touch the lives of billions of people by utilizing state-of-the-art NLP and machine learning? Do you enjoy collaboration and team work to…
Senior Staff Machine Learning Engineer, Perception, Simulation Realism
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo…
Anthropic Fellows Program, AI Safety & Security
4-month research fellowship building AI safety/security projects with public outputs, mentored by Anthropic researchers using open-source tools and compute budgets.
Machine Learning Engineer, Platform Architecture
At Apple, our Platform Architecture group is responsible for connecting our hardware and software into one unified system. You’ll collaborate with engineers across Apple to design how our technologies work in unison,…
Principal Machine Learning Engineer, Ads & Promos Delivery
Lead AI-driven ranking and relevance systems for DoorDash’s ads marketplace, designing and deploying ML/LLM models to personalize ad delivery in real time across global markets.
Senior Staff Machine Learning Engineer, Ads
Leads AI-driven ads and promotions delivery systems at DoorDash, designing real-time ranking/relevance models using deep learning, LLMs, and sequence modeling to optimize merchant-consumer matching across search/discovery platforms.
Staff Machine Learning Engineer, Causal Inference
A Staff Machine Learning Engineer focuses on causal inference at DoorDash, building production systems for uplift models, counterfactual evaluation, and connecting experiments with ML to drive decisions across new verticals like grocery and retail.
Staff Machine Learning Scientist, Applied Causal Inference
Designs, builds, and productionizes causal ML systems (uplift models, heterogeneous treatment effect, counterfactual evaluation) for DoorDash's New Verticals (grocery, retail, etc.) to influence marketplace decisions like promotions and recommendations.
Principal Machine Learning Engineer, Causal Decisioning
Principal-level technical leader for DoorDash's Causal ML pod in New Verticals (grocery, convenience, retail): sets multi-year causal ML strategy, defines a company-level causal value metric, and builds production causal decisioning systems (treatment effect estimation, counterfactual policy evaluation, surrogate metrics) connecting experiments, observational data, and ML for promotions, ranking,
Machine Learning Intern (Masters) - Summer 2027
A 12-week Summer 2027 machine learning research internship for Masters students at DoorDash. The intern conducts applied ML/AI research (ranking, recommender systems, computer vision, causal inference, ads) to improve discovery, ads, forecasting, fulfillment, and search, using Python or systems languages and ML frameworks like TensorFlow/PyTorch.
Machine Learning Intern (PhD) - Summer 2027
DoorDash is hiring PhD students for a 12-week Summer 2027 machine learning internship in San Francisco, Sunnyvale, NYC, or Seattle. Interns conduct applied ML research (recommender systems, ranking, ads, computer vision, causal inference) to improve DoorDash's discovery, ads, search, forecasting, and fulfillment experiences.
Software Engineer, Machine Learning Platform - Gen AI
Engineer on DoorDash's GenAI Platform team building production ML infrastructure: real-time GPU serving and high-throughput batch inference for open-weight LLMs/VLMs, plus fine-tuning (SFT/DPO/LoRA), LLM Gateway, evals, guardrails and cost attribution. Core stack: Python, distributed systems, GPU inference engines, Kubernetes, AWS/GCP.
Senior Machine Learning Engineer, Drive
Senior ML Engineer on DoorDash's Drive team, owning end-to-end machine learning systems for delivery ETA, merchant prep-time, and order release prediction, plus logistics optimization and AI quality signals built with deep learning, reinforcement learning, and LLMs/VLMs. On-site in San Francisco, Sunnyvale, or Seattle.
Senior Machine Learning Engineer, New Verticals Agentic Foundations
Senior ML engineer on DoorDash's Agentic Foundations team building and improving LLM-powered agents (starting with the Ask grocery assistant) via an eval-driven loop — iterating on prompts, tools, and context, and fine-tuning/deploying small language models to balance quality, latency, and cost, while launching new agent experiences for merchants and dashers.
Senior Software Engineer, Machine Learning
Senior ML engineer on DoorDash's grocery/retail catalog team, designing, training, deploying and monitoring production machine learning models that keep the product knowledge graph accurate and semantically rich. Core stack includes PySpark, Snowflake SQL, PyTorch/scikit-learn-style frameworks, and AI coding tools like Claude Code and Cursor.
Staff Machine Learning Engineer, Fulfillment Planning
Staff ML engineer on DoorDash's Fulfillment Planning team, building large-scale production ML systems for real-time delivery assignment, routing, and fulfillment/ETA estimation across the logistics network. Day-to-day spans Python, deep learning frameworks, optimization, and ML governance, plus mentoring and setting technical direction.
Staff Machine Learning Engineer, Personalization
Staff ML engineer building production personalization and growth models for DoorDash's consumer search across grocery and retail categories, partnering with product teams and mentoring juniors. Core work centers on Python ML (PyTorch/TensorFlow), causal inference, recommendation systems, and AI coding tools in a hybrid SF/Sunnyvale setup.
Staff Software Engineer, Machine Learning
Builds and ships machine-learning models and optimization algorithms (budget pacing, automated bidding) for DoorDash's ads platform and catalog/product knowledge graph, owning the end-to-end ML lifecycle from training through deployment, experimentation, and monitoring. Hybrid role using PyTorch, PySpark, and Snowflake.
Machine Learning Engineer II - Growth & Personalisation
Build and improve machine learning models for Deliveroo's New Verticals (grocery/retail): ranking items on vertical landing pages, blending new-vertical content into the restaurant-first homepage, personalising recommendations, and targeting notifications. Core stack is Python with end-to-end model productionisation; hybrid role based in London (3 days in office).
Machine Learning Engineering Manager - Personalisation
Lead a team of ~12 ML engineers owning ranking, recommendation and personalisation systems across Deliveroo's ordering experience (store page, cart, upsell, checkout, bundling), hybrid 3 days/week in London. Requires production ML at scale plus people management across a team spread over London, Finland and Berlin.