Senior Machine Learning Engineer

This is a fully remote position, open to applicants in New York.

📋 Description

• Collaborate with PhD researchers to conceptualize, execute, and commercialize machine learning models that enhance quantitative trading strategies.

• Create and sustain intricate data pipelines, encompassing data ingestion, feature engineering, validation, and quality assurance.

• Convert research prototypes and innovative concepts into efficient, thoroughly tested, production-ready code.

• Develop flexible tools and frameworks that expedite the model development and experimentation process.

• Oversee, analyze, and address subtle data quality challenges across both research and production settings.

• Take the initiative to lead projects from requirements gathering to delivery, making independent decisions regarding scope, dependencies, and trade-offs, focusing on long-term sustainability.

• Coordinate and assist with deployment activities while mentoring junior engineers and researchers; collaborate with research and engineering stakeholders on ownership, execution, and prioritization.

• Promote engineering consistency, standards, and best practices within the research team.

⛳️ Requirements

• A Bachelor's degree (or higher) in Computer Science, Applied Mathematics, Statistics, or a related quantitative discipline.

• Over 5 years of professional software engineering experience, demonstrating strong computer science fundamentals (data structures, algorithms, systems design).

• Proven mathematical proficiency — familiarity with the concepts and terminology used in statistics, linear algebra, optimization, and probability.

• Advanced expertise in Python; familiarity with R and/or C/C++ is highly advantageous.

• Extensive background with numerical and data science libraries (e.g., NumPy, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow, or similar).

• Demonstrated capability in building or maintaining machine learning systems within a distributed computing framework.

• Skilled in development within a Linux environment, with a focus on performance, accuracy, and reproducibility.

• Exceptional attention to detail, especially when dealing with imperfect or diverse data sets.

• Strong verbal and written communication abilities, along with the capability to collaborate effectively with researchers whose main expertise is not in software engineering.

🏝️ Benefits

• Comprehensive medical, dental, and vision insurance.

• Life and AD&D insurance coverage.

• 20 days of paid time off.

• 9 sick days.

• 401(k) plan with company matching.