What are the responsibilities and job description for the Quantitative Software Engineer: Techniques Engineering position at Two Sigma?
Position Summary
Two Sigma is a financial sciences company, combining data analysis, invention, and rigorous inquiry to help solve the toughest challenges in investment management, securities, private equity, and venture capital.
Our team of scientists, technologists, and academics looks beyond the traditional to develop creative solutions to some of the world’s most complex economic problems.
We’re seeking an experienced Machine Learning/AI Engineer who is passionate about bridging innovative research with production-level deployment. In this role, you will work closely with researchers, data teams, and platform engineers to transform innovative ideas into scalable, efficient, and robust production systems. You’ll have the opportunity to develop and refine ML workflows and drive best practices across the entire ML lifecycle—from initial prototyping to inference and support.
You Will Take On The Following Responsibilities
We are proud to be an equal opportunity workplace. We do not discriminate based upon race, religion, color, national origin, sex, sexual orientation, gender identity/expression, age, status as a protected veteran, status as an individual with a disability, or any other applicable legally protected characteristics.
Two Sigma is committed to providing reasonable accommodations to qualified individuals in accordance with applicable federal, state, and local laws.
If you believe you need an accommodation, please visit our website for additional information.
Two Sigma is a financial sciences company, combining data analysis, invention, and rigorous inquiry to help solve the toughest challenges in investment management, securities, private equity, and venture capital.
Our team of scientists, technologists, and academics looks beyond the traditional to develop creative solutions to some of the world’s most complex economic problems.
We’re seeking an experienced Machine Learning/AI Engineer who is passionate about bridging innovative research with production-level deployment. In this role, you will work closely with researchers, data teams, and platform engineers to transform innovative ideas into scalable, efficient, and robust production systems. You’ll have the opportunity to develop and refine ML workflows and drive best practices across the entire ML lifecycle—from initial prototyping to inference and support.
You Will Take On The Following Responsibilities
- Collaborate with ML researchers to explore model architectures, training methodologies, and experimental objectives
- Translate prototypes into reusable, maintainable, and production-ready code, ensuring research insights scale seamlessly into operation
- Design, implement, and optimize fully automated training pipelines and evaluation workflows
- Optimize models for production—improving efficiency through techniques like quantization, distillation, and intelligent batching
- Continuously assess and fine-tune both research and production workflows, integrating user feedback and automated monitoring systems
- Identify and implement opportunities for process improvements to reduce bottlenecks and improve overall modeler efficiency.
- Stay ahead of industry trends and new technologies, incorporating sophisticated methodologies into production systems
- Provide technical guidance and mentorship to peers, ensuring the team uses new tools and techniques that drive innovation
- BS in Computer Science, Mathematics, Physics, or related technical subject area
- Minimum 1 year of experience required; 7-15 years of experience preferred
- Strong software engineering skills using Python, version control, testing frameworks, and CI/CD practices
- Ability to work across functions and influence technical strategy while balancing research innovation with operational excellence
- A phenomenal teammate that can work efficiently with modeling and engineering partners
- Experience with leading ML frameworks (e.g., PyTorch, TensorFlow, HuggingFace) and familiarity with model serving/deployment tools, distributed systems and data infrastructures
- Experience with the following are preferred but not required:
- Working with LLMs, multimodal models, or time-series forecasting
- ML Ops platforms
- Background in research or a proven understanding of ML theory
- 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
We are proud to be an equal opportunity workplace. We do not discriminate based upon race, religion, color, national origin, sex, sexual orientation, gender identity/expression, age, status as a protected veteran, status as an individual with a disability, or any other applicable legally protected characteristics.
Two Sigma is committed to providing reasonable accommodations to qualified individuals in accordance with applicable federal, state, and local laws.
If you believe you need an accommodation, please visit our website for additional information.
Salary : $165,000 - $300,000