Digital Ocean

4 weeks ago

Staff Software Engineer, AI/ML

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 17 hours agoStatus: Live

Job Summary

Senior IC role driving the applied research and production learning systems for agentic AI at DigitalOcean. You will own the feedback-driven learning roadmap, design scalable learning loops, and lead technical direction across modeling, experimentation, and production readiness to ship real learning systems that impact user outcomes and product decisions.

Location: Seattle

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Own the feedback learning roadmap — define and execute the applied research agenda for feedback-driven agentic AI, translate user feedback into training and optimization strategies, and stay close to RLHF/RLAIF/DPO/PPO/GRPO frontiers.
•Build production learning systems — design learning loops to improve agent reasoning and action execution, create evaluation frameworks for offline/online measurement, and run large-scale experiments linking model changes to user outcomes and business impact.
•Provide technical leadership — set direction across modeling, experimentation, and production readiness; collaborate with product, engineering, design, and research teams to ship features; communicate complex AI systems to diverse stakeholders.
•Partner with product, engineering, design, and research teams to move work from prototype to shipped capability and ensure alignment with product goals.
•Communicate complex AI systems clearly to both technical and non-technical stakeholders.

Key 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 — with results you can point to.
•Strong understanding of agentic AI: reasoning, planning, tool use, action execution, instruction following, and self-correction.
•Strong software engineering in Python and at least one production systems language.
•The judgment to balance model quality, product impact, latency, reliability, cost, and maintainability — and communicate those tradeoffs clearly.

Experience:8+ yearsAI/MLCloudProduction AI

Skills:LeadershipCommunication

Languages:English

Tech Stack:PythonReinforcement learningRLHFRLAIFDPOPPOGRPO

Company Brief

Digital Ocean

Provides cloud infrastructure and developer-focused cloud services including scalable droplets, managed databases, Kubernetes, object storage, and networking to simplify deploying and managing applications for developers and small-to-medium businesses.

Industry: Cloud Computing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 250M to 500M

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: New York, United States

Founded: 2011

Glassdoor: 3.8

Website LinkedIn

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Digital Ocean

4 weeks ago

Staff Software Engineer, AI/ML

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 17 hours agoStatus: Live

Job Summary

Location: Seattle

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Own the feedback learning roadmap — define and execute the applied research agenda for feedback-driven agentic AI, translate user feedback into training and optimization strategies, and stay close to RLHF/RLAIF/DPO/PPO/GRPO frontiers.
•Build production learning systems — design learning loops to improve agent reasoning and action execution, create evaluation frameworks for offline/online measurement, and run large-scale experiments linking model changes to user outcomes and business impact.
•Provide technical leadership — set direction across modeling, experimentation, and production readiness; collaborate with product, engineering, design, and research teams to ship features; communicate complex AI systems to diverse stakeholders.
•Partner with product, engineering, design, and research teams to move work from prototype to shipped capability and ensure alignment with product goals.
•Communicate complex AI systems clearly to both technical and non-technical stakeholders.

Key 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 — with results you can point to.
•Strong understanding of agentic AI: reasoning, planning, tool use, action execution, instruction following, and self-correction.
•Strong software engineering in Python and at least one production systems language.
•The judgment to balance model quality, product impact, latency, reliability, cost, and maintainability — and communicate those tradeoffs clearly.

Experience:8+ yearsAI/MLCloudProduction AI

Skills:LeadershipCommunication

Languages:English

Tech Stack:PythonReinforcement learningRLHFRLAIFDPOPPOGRPO

Company Brief

Digital Ocean

Industry: Cloud Computing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 250M to 500M

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: New York, United States

Founded: 2011

Glassdoor: 3.8

Website LinkedIn