USD per year
Staff Software Engineer, AI/ML
Seattle Dive in and do the best work of your career at DigitalOcean. Journey alongside a strong community of top talent who are relentless in their drive to build the simplest scalable cloud. If you have a growth mindset, naturally like to think big and bold, and are energized by the fast-paced environment of a true industry disruptor, you’ll find your place here. We value winning together—while learning, having fun, and making a profound difference for the dreamers and builders in the world. Building AI agents that take real actions is the easy part. Building agents that get better over time — that learn from feedback, correct mistakes, and optimize toward outcomes users actually care about — is one of the hardest open problems in production AI today. That's what this team works on. As a Staff AI/ML Engineer on our Applied Research team, you'll own the technical direction for feedback-driven learning in DigitalOcean's agentic systems: reward modeling, preference optimization, reinforcement learning, and the evaluation infrastructure needed to measure whether any of it is actually working. This is a senior IC role with broad technical scope. You'll set direction, run experiments at scale, and close the loop between user signals and model behavior - shipping research into production, not just writing it up.
What You’ll Be Doing
Own the feedback learning roadmap
- Define and execute the applied research agenda for feedback-driven agentic AI — from reward modeling and preference optimization to online learning and human feedback loops.
- Translate user feedback, human evaluation data, and product signals into concrete training and optimization strategies.
- Stay close to the research frontier on RLHF, RLAIF, DPO, PPO, GRPO, and related methods and know when to apply them versus when simpler approaches win.
Build production learning systems
- Design and implement learning loops that improve agent reasoning, planning,...
DigitalOcean provides simple tools and predictable pricing for infrastructure management, enabling digital native enterprises to develop, manage, and scale applications using compute, storage, and networking solutions. They offer scalable cloud compute products including Droplets (virtual machines), Kubernetes managed service, serverless Functions, Gradient AI Agentic Cloud for AI apps, managed hosting with App Platform, backups & snapshots, networking solutions (firewalls, load balancers, VPC), managed databases (MongoDB, Kafka, PostgreSQL, MySQL), storage options (Spaces object storage and Volumes block storage), developer tools (API, CLI), and management tools (monitoring, projects, IAM).
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