Senior Forward Deployed Engineer – AI/ML

This is a fully remote position, open to applicants in California.

📋 Description

• Collaborate with strategic AI-focused enterprises and emerging AI startups to design, implement, enhance, and scale production AI and agentic systems on DigitalOcean’s AI-Native Cloud.

• Assist with intricate migrations, production-ready proofs of concept, deployment acceleration, and long-term workload expansion across inference and runtime platforms.

• Enhance distributed inference and runtime performance through benchmarking, optimizing GPU efficiency, KV-cache optimization, speculative decoding, prefill/decode disaggregation, multi-node deployments, and optimizing latency/cost.

• Serve as the initial customer for DigitalOcean’s AI-native platform features, including the Inference Engine, runtimes, orchestration systems, GPU platforms, and deployment workflows.

• Identify operational insights, architectural shortcomings, and scaling challenges to relay to Product Engineering and Research teams.

• Develop benchmarking systems, automation tools, AI starter kits, deployment frameworks, operational playbooks, fine-tuning workflows, and reference architectures.

• Collaborate with GPU vendors, model providers, infrastructure partners, and ISVs on co-development, technical validation, optimization, and readiness for launch.

• Empower customer-facing technical teams and partner teams through deployment strategies, benchmarking insights, playbooks, reference architectures, demonstrations, and technical support.

• Travel up to 30% for customer interactions, strategic onsite workshops, ecosystem partnerships, conferences, and internal collaboration.

• Foster customer adoption, ensure production success, influence product development, deliver assets and tools, enable the field, and enhance ecosystem scale.

⛳️ Requirements

• Experience in designing and operationalizing production AI systems, including inference workloads, agentic runtimes, orchestration frameworks, and AI-native applications.

• Practical experience with inference and serving frameworks such as vLLM, SGLang, Ray Serve, NVIDIA Dynamo, llm-d, or similar systems.

• Familiarity with LLM optimization techniques, including continuous batching, quantization, KV-cache optimization, and speculative decoding.

• Extensive expertise with NVIDIA and AMD GPU platforms and software ecosystems, including CUDA, ROCm, TensorRT, Triton, NCCL, RCCL, NVLink, XGMI, and RoCE.

• Strong knowledge of Kubernetes, distributed systems, networking, storage systems, Infrastructure as Code, and large-scale AI infrastructure architectures.

• Experience with AI orchestration and agent frameworks such as LangGraph, CrewAI, MCP ecosystems, LlamaIndex, OpenAI Agents SDK, or similar runtime systems.

• Proficient in production coding using Python or Go.

• Proven experience in building tools, automation systems, deployment workflows, benchmarking frameworks, and operational platforms.

• Demonstrated ability to benchmark and optimize AI infrastructure for scalability, reliability, GPU efficiency, runtime performance, latency optimization, and workload economics.

• Capability to establish technical credibility with CTOs, Principal architects, Product Engineering teams, and ecosystem partners.

• Over 6 years of experience in Forward Deployed Engineering, ML Engineering, Applied AI Engineering, AI Infrastructure, Technical Consulting, or other customer-facing engineering roles focused on production AI systems.

• Willingness to travel up to 30% for customer interactions, strategic onsite workshops, ecosystem partnerships, conferences, and internal collaboration.

🏝️ Benefits

• Reimbursement for relevant conferences, training, and educational opportunities.

• Access to over 10,000 courses through LinkedIn Learning.

• Employee Assistance Program available.

• Local Employee Meetups for networking.

• Flexible time-off policy to support work-life balance.

• Eligibility for bonuses based on individual and company performance.

• Equity compensation, including equity grants upon hire.

• Option to participate in the Employee Stock Purchase Program.