Position Summary
We9re seeking a Quantitative Software Engineer to help scale the capabilities behind our AI/ML modeling techniques. You9ll work at the intersection of research enablement, advanced hardware efficiency, AI tooling, and software engineering discipline, partnering closely with researchers to turn techniques with real production impact into fast, well-tested, and maintainable systems that the rest of the firm can build on.
You will take on the following responsibilities:- Partner with ML researchers to explore model architectures, training methodologies, LLM and agentic engineering, and experimental objectives, translating modeling needs into engineering priorities.
- Translate prototypes into reusable, maintainable, production-ready code, ensuring research insights scale seamlessly into operation.
- Design and optimize data loading and pipeline infrastructure for training and inference at scale, including GPU utilization, batching/bin-packing strategies, and other large-scale compute optimizations.
- Extend core research libraries to support agentic workflows, integrating modern agent frameworks while maintaining a high quality bar for AI-assisted or AI-generated code and output.
- Lead structural improvements to keep a growing, multi-contributor codebase coherent, testable, and maintainable as usage and team size scale, evolving internal libraries toward open-source-caliber engineering practices.
You should possess the following qualifications:- BS in Computer Science, Mathematics, Physics, or related technical subject area
- Minimum 1 year of experience required; 7-15 years of experience preferred
- Experience in quantitative software engineering
- Strong software engineering skills using Python, AI coding tools, version control, testing frameworks, and CI/CD practices
- Hands-on experience building high-throughput GPU ML systems, including low-level performance optimization, batching, scheduling, orchestration, and training infrastructure
- Experience collaborating across research and engineering functions, applying the right level of rigor from prototype-stage code to production systems.
Preferred Skills- Experience with CUDA
- Experience building on and extending leading ML frameworks such as PyTorch, TensorFlow, or Hugging Face
- Experience using LLMs and agent frameworks to automate research and engineering workflows in ways that are reliable and useful in practice
- Experience in agent evaluation frameworks, RLHF, RLVR, policy optimization, or synthetic data generation.
You will enjoy the following benefits:- Core Benefits: Fully paid medical and dental insurance premiums for employees and dependents, competitive 401k match, employer-paid life & disability insurance
- Perks: Onsite gyms with laundry service, wellness activities, casual dress, snacks, game rooms
- Learning: Tuition reimbursement, conference and training sponsorship
- Time Off: Generous vacation and unlimited sick days, competitive paid caregiver leaves
- Hybrid Work Policy: Flexible in-office days with budget for home office setup
The base pay for this role will be between $165,000 and $300,000. This role may also be eligible for other forms of compensation and benefits, such as a discretionary bonus, health, dental and other wellness plans and 401(k) contributions. Discretionary bonus can be a significant portion of total compensation. Actual compensation for successful candidates will be carefully determined based on a number of factors, including their skills, qualifications and experience.
