Senior Forward Deployed Engineer II (AI/ML)
DigitalOcean6 days ago
Base Salary
$167k - $209k/yr
Responsibilities
- Partner with strategic AI-native enterprises and startups to architect, deploy, optimize, and scale production AI and agentic workloads.
- Support complex migrations, production-ready proofs of concept, deployment acceleration, and long-term workload expansion across inference and runtime platforms.
- Benchmark and optimize distributed inference, GPU efficiency, KV-cache use, speculative decoding, prefill/decode disaggregation, multi-node deployments, latency, and cost.
- Validate AI-native platform capabilities as a first customer and communicate operational insights, architectural gaps, and scaling bottlenecks to Product Engineering and Research.
- Build benchmarking systems, automation tooling, deployment frameworks, AI starter kits, fine-tuning workflows, operational playbooks, and reference architectures.
- Collaborate with GPU vendors, model providers, infrastructure partners, ISVs, customer-facing technical teams, and ecosystem partners on validation, enablement, and launch readiness.
- Travel up to 30% for customer engagements, workshops, partnerships, conferences, and internal collaboration.
Requirements
- 6+ years of experience in Forward Deployed Engineering, ML Engineering, Applied AI Engineering, AI infrastructure, technical consulting, or equivalent customer-facing engineering roles supporting production AI systems.
- Experience designing and operationalizing production AI systems involving inference workloads, agentic runtimes, orchestration frameworks, and AI-native applications.
- Hands-on experience with inference and serving frameworks such as vLLM, SGLang, Ray Serve, NVIDIA Dynamo, or llm-d, plus techniques including continuous batching, quantization, KV-cache optimization, and speculative decoding.
- Deep expertise with NVIDIA and AMD GPU platforms and ecosystems including CUDA, ROCm, TensorRT, Triton, NCCL, RCCL, NVLink, XGMI, and RoCE.
- Strong proficiency with 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, or OpenAI Agents SDK.
- Strong production coding skills in Python or Go and experience building tooling, automation systems, deployment workflows, benchmarking frameworks, or operational platforms.
- Ability to benchmark and optimize AI infrastructure for scalability, reliability, GPU efficiency, runtime performance, latency, and workload economics.
- Ability to establish technical credibility with CTOs, principal architects, product engineering teams, and ecosystem partners while managing strategic deployments.
- Experience building deployment standards, technical enablement programs, platform adoption frameworks, or ecosystem integration strategies is preferred.
- Active open-source contributions and experience collaborating with GPU, infrastructure, model, or ecosystem vendors are preferred.
Benefits
- Hybrid work arrangement.
- Up to 30% travel for customer engagements, workshops, partnerships, conferences, and internal collaboration.
- Reimbursement for relevant conferences, training, and education.
- Access to LinkedIn Learning with more than 10,000 courses.
- Employee Assistance Program, local employee meetups, and flexible time off.
- Potential performance bonus and equity compensation, including equity grants upon hire and an Employee Stock Purchase Program.
Tech Stack
Categories
Forward Deployed
About DigitalOcean
DigitalOcean provides cloud infrastructure and platform services for developers, startups, and small to mid-sized businesses, including virtual machines (Droplets), managed Kubernetes and databases, object/block storage, networking, and GPUs for AI workloads. It operates a usage-based, self-service public cloud with APIs, CLI, and a marketplace to deploy and scale applications. Founded in 2012 and headquartered in Broomfield, Colorado, DigitalOcean is a public company listed on the NYSE.