Staff Software Engineer, AI/ML
$217k - $271k • Seattle • Full-time
Posted 4mo ago
This job has been open for more than 60 days. It may no longer be actively hiring, so check with the company before putting a lot into an application.
Job Location
Seattle
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Agent Engineer
About the job
This role focuses on building AI agents that learn and improve over time by incorporating feedback, correcting mistakes, and optimizing towards user-defined outcomes. As a Staff AI/ML Engineer on the Applied Research team, you will lead the technical direction for feedback-driven learning within DigitalOcean's agentic systems. This includes owning the roadmap for reward modeling, preference optimization, reinforcement learning, and the necessary evaluation infrastructure to ensure these systems are effective. You will be responsible for shipping research into production, setting technical direction, running large-scale experiments, and closing the loop between user signals and model behavior.
Responsibilities
- Define and execute the applied research agenda for feedback-driven agentic AI, including reward modeling, preference optimization, online learning, and human feedback loops.
- Translate user feedback, human evaluation data, and product signals into concrete training and optimization strategies for AI systems.
- Design and implement learning loops to enhance agent reasoning, planning, tool use, and action execution over time.
- Build evaluation frameworks to measure reasoning quality, instruction following, task success, safety, and real user outcomes at both offline and online scales.
- Run large-scale experiments to connect model changes with measurable improvements in user experience and business impact.
- Set technical direction for modeling, experimentation strategy, evaluation design, and production readiness.
- Partner with product, engineering, design, and research teams to move work from prototype to shipped capability.
- Communicate complex AI systems clearly to both technical and non-technical stakeholders.
Requirements
- 8+ years of experience building production AI/ML systems (LLMs, GenAI, agentic systems, recommendation, search, personalization, or applied research at scale).
- Hands-on experience improving AI systems through reinforcement learning, reward modeling, fine-tuning, human feedback, or preference optimization.
- Strong understanding of agentic AI concepts: reasoning, planning, tool use, action execution, instruction following, and self-correction.
- Strong software engineering skills in Python and at least one production systems language.
- Ability to balance model quality, product impact, latency, reliability, cost, and maintainability, and communicate these tradeoffs clearly.
- Experience with agent evaluation, offline/online experiments, and human feedback loops in production.
- Direct experience with RLHF, RLAIF, DPO, PPO, GRPO, or related optimization techniques.
- Prior Staff, Senior Staff, Tech Lead, or equivalent senior IC experience.
- Master's or PhD in CS, ML, AI, or a related field, or equivalent depth demonstrated through industry work.
- Experience with production ML infrastructure such as model serving, observability, data pipelines, feature stores, or experimentation platforms.
- Research contributions via publications, patents, open-source work, or demonstrated applied research impact in RL, reward modeling, evaluation, or recommendation systems.
Benefits
- Flexible time off
- Local team meetups
- Mental health and well being support
- Reimbursement for relevant conferences, training, and education