Machine Learning Engineer

About Tower Research Capital

Founded in 1998, Tower Research Capital is a premier quantitative trading firm renowned for its high-performance trading platform and independent trading teams. With over 25 years of innovation and a record of uncovering unique market opportunities, Tower boasts a globally distributed team of top tier systematic trading and engineering experts. The company fosters an empowering environment where portfolio managers build their strategies supported by comprehensive infrastructure and scalable technology.

Engineers at Tower excel in developing cutting-edge electronic trading infrastructure, tackling challenges in low-latency programming, FPGA technology, hardware acceleration, and machine learning. The continuous investment in talent and technology secures Tower's leadership in platform functionality, scalability, and performance. Every team, including Business Support, contributes to the platform's success through critical services like market access, data, compute, risk management, and compliance.

Employees experience an intellectually stimulating, goal-oriented culture where highly skilled peers encourage ongoing growth.

Key Responsibilities

• Design and build the next-generation machine learning research platform focused on scalability, dependability, observability, and reproducibility.
• Develop infrastructure supporting large-scale experiments, model training, and simulation across on-premises high-performance computing (HPC) and multi-cloud systems.
• Collaborate closely with quantitative researchers to translate research workflows into robust platform features.
• Create and optimize distributed training pipelines tailored for high-throughput GPU-accelerated tasks.
• Advance experiment management, model versioning, artifact tracking, and data tracing to maintain transparency and reproducibility of research.
• Build tools and frameworks to expedite feature engineering, dataset creation, and extensive backtesting.
• Lead initiatives to enhance compute efficiency, resource allocation, and workload isolation in diverse computing environments.
• Improve platform observability by adding metrics, logging, tracing, and debugging capabilities specifically for machine learning workloads.
• Support rapid development cycles by implementing features and fixes swiftly while upholding rigorous engineering standards.
• Contribute to architectural strategies enabling the platform to scale with growing data volumes and increasingly complex models.

Candidate Qualifications

• Minimum of 2 years’ experience designing and developing extensive distributed systems, preferably for research or data-intensive contexts.
• Proficient in Python programming, focusing on clean, maintainable, and efficient code.
• Experience operating applications on Linux HPC clusters and/or cloud infrastructure.
• Solid grasp of distributed computing, parallelism, and resource management.
• Familiar with GPU-based workloads and modern machine learning frameworks such as PyTorch, TensorFlow, or JAX.
• Skilled in optimizing data pipelines and managing large-scale structured and unstructured data sets.
• Strong problem-solving ability with expertise debugging complex multi-layer system issues.
• Capable of autonomous work in fast-moving, research-driven environments.
• Excellent communication skills and proven experience partnering with researchers or data scientists.

Preferred Experience

• Background in building large-scale internal machine learning platforms or research tools.
• Knowledge of experiment tracking tools, workflow orchestration systems, and model lifecycle management.
• Familiarity with containerization and orchestration technologies such as Docker and Kubernetes.
• Experience within quantitative finance, simulation systems, or domains demanding high performance and low latency.

Benefits and Culture

Tower’s main office is located in the iconic Equitable Building in NYC’s Financial District, with additional offices globally. The company values a workplace that blends challenge with enjoyment, promoting a culture free of ego where collaboration and respect are paramount. Features include:

• Generous paid time off policies.
• Financial wellness programs and savings plans tailored to each region.
• Hybrid work opportunities.
• Complimentary breakfast, lunch, and snacks every day.
• Wellness initiatives including in-office experiences and reimbursements for gym memberships or personal training.
• Company-sponsored sports teams and fitness events.
• Volunteer programs and charitable contributions.
• Regular social events, happy hours, and celebrations.
• Opportunities for continuous learning and workshops.

The company fosters a diverse, collaborative, and supportive environment where high performance goes hand-in-hand with employee well-being, without hierarchical barriers or egos. Tower Research Capital is proud to be an equal opportunity employer.