Point your AI agent at freehire and let it find you a job. A CLI and an MCP server over the whole job API — no browser.
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.
Build and maintain DoorDash’s iOS app used by millions, focusing on real-time data sync, API integration, and Swift-based features for a 3-sided marketplace.
About the Team Our DD Labs team builds real-time autonomous delivery systems. The Planning & Decision-Making group is investing heavily in deep reinforcement learning to move beyond classical planning, learning…
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.
Leads AI-driven personalization for DoorDash’s consumer shopping journey, designing and deploying ML models to enhance search, discovery, and recommendations across food, grocery, and retail—scaling teams and mentoring engineers to modernize recommendation systems.
Build and maintain DoorDash's global logistics backend, migrating a monolith to microservices while optimizing performance, reliability, and scalability for a 3-sided marketplace.
Builds and maintains DoorDash’s scalable data platform (Spark, Flink, Kafka, Airflow) to enable real-time analytics, data governance, and business insights for logistics/delivery operations.
Build and scale high-performance data pipelines and warehouse models to power analytics and reporting at DoorDash, using Python/Java, Spark, Airflow, Kafka, and Snowflake.
Build and deploy large-scale ML systems to personalize offers and incentives for DoorDash’s DashPass loyalty program, optimizing subscriber acquisition, retention, and churn reduction.
Staff Software Engineer designs and maintains DoorDash’s global backend systems for its 3-sided marketplace, using modern web stacks, microservices, and databases to improve scalability and reliability.
Lead the design and scaling of DoorDash’s data infrastructure, building reliable pipelines and models for analytics, reporting, and financial systems using Python/Scala, Spark, Airflow, and streaming tech.
Builds and deploys ML models for personalization and growth, focusing on recommendation systems and causal inference to enhance DoorDash’s grocery/retail search experience using PyTorch/TensorFlow in Python.
Builds and maintains the shared infrastructure that lets DoorDash teams safely deploy generative AI products, focusing on evaluation, observability, and agent systems using Python, distributed systems, and ML tooling.
Build and scale the shared infrastructure that powers DoorDash’s generative AI products, including real-time and batch LLM inference, fine-tuning, and agent platforms across San Francisco, Sunnyvale, and Seattle.
Lead the architecture and evolution of DoorDash’s event streaming platform (Kafka, WarpStream, AutoMQ) that handles trillions of events daily, setting multi-year technical strategy and solving distributed-systems challenges at massive scale.
Build and deploy ML models for delivery ETAs, prep-time prediction, and logistics optimization at DoorDash Drive, using deep learning, reinforcement learning, and multimodal AI.
Build and maintain DoorDash’s high-performance traffic infrastructure, including Envoy-based data planes and xDS control planes, to ensure reliable, low-latency communication across thousands of services.
The Unified Gateway team builds and maintains the API gateway platform that handles traffic routing, authentication, and request translation for DoorDash's global logistics infrastructure. Engineers in this role use Kotlin and gRPC to develop scalable, high-throughput services that empower product teams to deploy endpoints efficiently.
Veeam is the Data and AI Trust Company, specializing in helping organizations ensure their data and AI are fully understood, secured, and resilient to enable the acceleration of safe AI at scale. As the market leader…
About Vasco Vasco is the revenue context layer for AI agents. The product was built around one idea: confident is not the same as correct, and revenue decisions get made on confidence all the time. We structure CRM,…
We couldn't check your fit for this role — add a CV to your profile to see it next time.
