Senior/Staff Deep Reinforcement Learning Engineer

Covey Technologies, Inc.

Job Overview

Location

San Francisco, CA

Job Type

Full-time

Full Job Description

📋 Description

• As a Senior/Staff Deep Reinforcement Learning Engineer at Covey Technologies, Inc., you will design, train, and deploy deep reinforcement learning policies that enable real-time driving decisions for autonomous vehicles, directly contributing to the advancement of safe, scalable, and adaptive self-driving technology.
• You will own the full lifecycle of RL policy development—from problem formulation and reward design through large-scale distributed training in JAX to on-vehicle inference—ensuring seamless integration of learned components into the autonomy stack for robust, production-ready behavior.
• You will formulate complex driving tasks as RL problems with well-shaped reward functions and expressive state/action representations, enabling the system to generalize across novel scenarios and handle long-tail edge cases effectively.
• You will design and train model-based deep RL agents using GPU-accelerated simulation at massive scale, including contributing to simulator improvements to enhance fidelity, scalability, and training efficiency.
• You will build and maintain distributed training infrastructure in JAX across large compute clusters, optimizing for throughput, latency, and resource utilization to accelerate experimentation cycles.
• You will develop agentic optimization systems that autonomously improve code, run experiments, analyze metrics, and iterate on RL policies with minimal human intervention, pushing the frontier of self-improving AI systems.
• You will collaborate with the DD Labs team, which specializes in real-time autonomous delivery systems, where the Planning & Decision-Making group is pioneering unified architectures that jointly handle prediction and planning using pure JAX end-to-end—eliminating C++ rewrites and TensorRT exports for rapid policy-to-vehicle deployment in minutes.
• You will work within a culture that values data-driven decision-making, where experiment pipelines, training run analysis, and metric-guided architectural choices are central to innovation, enabling continuous improvement from large-scale fleet data.
• You will have the opportunity to publish research at top-tier venues (NeurIPS, ICML, ICLR, CoRL, RSS, ICRA) and ship learned components into production robotics or autonomous vehicle stacks, advancing both academic knowledge and real-world impact.
• You will grow your expertise in cutting-edge RL techniques including policy gradients, value functions, exploration-exploitation, model-based RL, reward shaping, and sim-to-real transfer, while working with a functional ML stack that unifies training and inference environments.

🎯 Requirements

• BS/MS/PhD in Computer Science, Electrical Engineering, Robotics, or a related field with a strong foundation in reinforcement learning and deep learning.
• Hands-on experience training RL agents at scale, preferably in robotics, autonomous driving, or other real-time decision-making domains.
• Proficiency in JAX or a similar functional ML framework, including comfort with JIT compilation, vectorized environments, and GPU-accelerated simulation.
• Deep understanding of core RL concepts: policy gradients, value functions, exploration-exploitation, model-based RL, reward shaping, and sim-to-real transfer.
• Data-driven mindset: proven ability to build experiment pipelines, analyze training runs, and let metrics guide architectural decisions.

🏖️ Benefits

• Competitive base salary ranging from $168,000 to $247,000 USD, localized to work location and determined by skills, experience, qualifications, and market conditions.
• Equity grant opportunities as part of the total compensation package.
• Comprehensive benefits including 401(k) with employer matching, 16 weeks of paid parental leave, medical/dental/vision coverage, wellness benefits, commuter benefits match, paid time off, paid sick leave, disability and basic life insurance, family-forming assistance, and mental health programs.
• Access to DoorDash’s broader perks: premium healthcare, wellness expense reimbursement, 11 paid holidays, and support for employee well-being through inclusive policies and accommodations.
• Commitment to diversity, inclusion, and fair chance hiring—qualified applicants with arrest or conviction records are considered consistent with local regulations (e.g., San Francisco Fair Chance Ordinance).

Skills & Technologies

REST

Senior

Remote

Degree Required

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Covey Technologies, Inc.

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About Covey Technologies, Inc.

Covey is a platform designed to streamline and enhance the delivery and field service operations for businesses. It offers a comprehensive suite of tools that integrate dispatching, routing, proof of delivery, and customer communication into a single, user-friendly interface. The platform aims to improve efficiency, reduce operational costs, and boost customer satisfaction by providing real-time visibility and control over mobile workforces. Covey caters to a variety of industries, including logistics, food delivery, and home services, enabling companies to manage their field operations more effectively and scale their services with confidence. Its features support automated assignments, route optimization, and performance analytics.

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