Software Engineer - Machine Learning: Techniques Engineering
New York, New York, United States
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.
- 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.
- 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