Senior Forward Deployed Engineer II (AI/ML)
DigitalOcean6 days ago
Base Salary
$167k - $209k/yr
Responsibilities
- Architect, deploy, optimize, and scale production AI and agentic workloads for strategic customers and AI startups.
- Optimize distributed inference and runtime performance through benchmarking, GPU tuning, KV-cache optimization, speculative decoding, prefill/decode disaggregation, and multi-node deployments.
- Validate AI-native platform capabilities and communicate operational insights, architectural gaps, and scaling bottlenecks to Product Engineering and Research teams.
- Build deployment frameworks, benchmarking systems, automation tooling, AI starter kits, fine-tuning workflows, operational playbooks, and reference architectures.
- Collaborate with GPU vendors, model providers, infrastructure partners, and ISVs on technical validation, optimization, co-development, and launch readiness.
- Enable customer-facing and partner teams with validated deployment patterns, technical guidance, demos, and operational insights.
- Travel up to 30% for customer engagements, workshops, partnerships, conferences, and internal collaboration.
Requirements
- 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 LLM optimization techniques such as continuous batching, quantization, KV-cache optimization, and speculative decoding.
- Deep expertise with NVIDIA and AMD GPU platforms and related 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 automation, deployment workflows, benchmarking frameworks, and operational platforms.
- Proven 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, engineering teams, and ecosystem partners while managing strategic production deployments.
- At least 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.
- Preferred experience includes platform enablement, ecosystem integration, open-source AI or infrastructure contributions, and collaboration with GPU, infrastructure, model, or ecosystem partners.
Benefits
- Remote work arrangement.
- Up to 30% travel for customer and ecosystem engagements.
- Reimbursement for relevant conferences, training, and education.
- Access to LinkedIn Learning with 10,000+ courses.
- Employee Assistance Program, local employee meetups, and flexible time off.
- Potential performance bonus, equity compensation, equity grants upon hire, and 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.