Software Engineer - Machine Learning: Techniques Engineering

New York, New York, United States

Share with: Facebook Twitter Send to a friend

Two Sigma is a financial sciences company, combining data analysis, invention, and rigorous inquiry to help solve the toughest challenges in investment management, insurance technology, 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.

Within Techniques Engineering, our mission is to accelerate the release of new models and ensure we continue to provide an innovative platform by collaborating closely with partner teams to build engineering capabilities that advance the needs of the business.

We're seeking a Sr. Software Engineer to join our growing team! As an Engineer on Techniques Engineering, you will collaborate with researchers and software engineers to deploy cutting-edge ML models and algorithms. Your primary responsibilities will be to speed up the machine learning process, improve model training and runtime performance, and ensure scalability in the research and productionization process.


You will take on the following responsibilities:

  • Lead the architecture and execution of sophisticated technical projects requiring coordination and alignment of requirements with multiple quantitative research teams and engineering partners.
  • Build tools and frameworks to automate research, model training, evaluation, and deployment processes.
  • Deploy models into our production environment, ensuring scalability, reliability, and maintainability.
  • Mentor junior engineers, perform code/design review, and promote best practices.

You should possess the following qualifications:

  • Minimum of 7 years of experience required; 7-15 years of experience preferred
  • BS or MS degree in Computer Science, Engineering, or a related field.
  • Strong background with ML algorithms, deep learning frameworks, and statistical modeling techniques.
  • Proficiency in programming languages such as Python, Java and C++, and experience with machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn). Familiarity with cloud platforms (AWS, Azure, GCP) is a plus.
  • Strong experience building and deploying machine learning models in production environments + problem-solving and analytical skills with the ability to debug and optimize complex machine learning pipelines. 

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.

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.