DV Trading is hiring a Senior AI Engineer in Technology — Chicago; Hong Kong; London; New York; Singapore. The overview below is synthesized from the employer posting on job-boards.greenhouse.io: factual requirements and scope are preserved, but prose is rewritten with editorial context. Verify details and apply via the employer link.
About Us
Company context from the listing:
:
Founded 20 years ago and headquartered in Chicago, the DV Group of financial services firms has grown to more than 600 people operating throughout North America, Europe and Asia. Since spinning out of a large brokerage firm in 2016, DV Trading has rapidly scaled as an independent proprietary trading firm utilizing its own capital, trading strategies, and risk management methodologies to provide liquidity to worldwide financial markets and hedging opportunities to commodity producers and users.
Overview
Company context from the listing:
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.
model gateway that routes intelligently across open and closed providers. The near-term result is lower cost and better latency.
Job 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 KubernetesBuild 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
Requirements
Experience and skills the team lists as required:
- 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
Preferred:
- 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
Benefits
What the posting highlights about the offer:
- 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
DV is not accepting unsolicited resumes from search firms. Only search firms with valid, written agreements with DV should submit resumes in response to DV’s posted positions.
The range below reflects the expected base salary for this position. It represents a good-faith estimate of the base pay we anticipate offering, with actual compensation determined by your experience, education, skills, and performance throughout the interview process.
Base Salary Range
$200,000—$300,000 USD
Build a standout application
For the Senior AI Engineer at DV Trading, reviewers look for concise evidence over buzzwords. Mirror the language of the posting sparingly, quantify support or delivery outcomes, and show how you handled ambiguity, time-zone collaboration and user empathy. Keep your resume to impact, keep your cover note to one page, and link to artifacts — tickets resolved, docs shipped, dashboards owned — that prove you can operate in a fast-moving Web3 team. Prepare to discuss a time you turned a confusing user report into a clear fix and how you measure quality in support and operations.
Web3 hiring values reliability: on-time follow-through, clear writing, and a track record of improving runbooks and tooling. Treat the application as a work sample. For interviews, be ready to walk through how you prioritize across time zones, handle a difficult user, and decide when to escalate versus resolve directly. Show how you document decisions so the next teammate benefits.
In a distributed Web3 org, trust builds through written clarity. Use the cover note to demonstrate it.
