Senior AI Engineer

DV Trading

3d • $200,000 - $300,000 • Onsite

About The Position

DV Trading is building a centralized AI function and is now hiring for the model layer. The long-term goal is for DV to own its model capability — not to be permanently dependent on what frontier providers choose to offer, at what price, for how long. This role is how that happens: fine-tuning and distilling open-weight models for DV-specific tasks, operating the inference infrastructure to run them on-prem, and building the model gateway that routes intelligently across open and closed providers. The near-term result is lower cost and better latency. The long-term result is a firm that controls its own AI stack.

Requirements

• 5+ years software engineering; strong Python
• Production fine-tuning or distillation of open-weight models (not just inference API wrappers)
• Experience serving LLMs on-prem (vLLM, TGI, Triton, or equivalent)
• Experience managing GPU infrastructure (provisioning, scheduling, utilization monitoring) in a production environment
• Model evaluation and regression testing in production
• Kubernetes and GPU workload management
• Strong grasp of the tradeoffs between open and closed models across cost, quality, latency, and data sensitivity

Nice To Haves

• Quantization, PEFT/LoRA, or other efficient training techniques
• Model gateway or inference proxy design (routing, fallback, rate limiting)
• Financial services or other regulated/sensitive-data environments
• Familiarity with the open model ecosystem (Hugging Face, model cards, licensing)

Responsibilities

• Build and operate a model gateway routing inference across open and closed models with cost, latency, and quality tracking
• Design and run distillation pipelines: use frontier model outputs to generate training data for task-specific open models
• Fine-tune and evaluate open-weight models (Llama, Qwen, Mistral, or similar) for DV-specific tasks
• Deploy and maintain on-prem inference infrastructure (vLLM, TGI, or equivalent) on Kubernetes
• Build model evaluation frameworks for quality, cost, latency, and regression
• Define criteria and tooling for model selection: when open models are production-ready vs. when to use closed APIs
• Partner with the agent engineering team to ensure the model layer meets agent workload

Benefits

• Discretionary bonus eligibility
• Medical, dental, and vision insurance
• HSA, FSA, and Dependent Care Options
• Employer Paid Group Term Life and AD&D insurance
• Voluntary LTD, Life & AD&D insurance
• Flexible Vacation policy
• Retirement plan with employer match

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed