LOG IN
SIGN UP
Canary Wharfian - Online Investment Banking & Finance Community.
Sign In
or continue with e-mail and password
Forgot password?
Don't have an account?
Create an account
or continue with e-mail and password
By signing up, you agree to our Terms & Conditions and Privacy Policy.

Machine Learning Engineer

ExperiencedNo visa sponsorship
Tower Research logo

at Tower Research

Proprietary Trading

Posted 5 days ago

No clicks

**Machine Learning Engineer** at Tower Research Capital focuses on architecting and developing the next generation of our ML research platform, emphasizing scalability, reliability, and user-centric design. Key responsibilities include: - Building and optimizing large-scale distributed systems for ML workloads across on-premises HPC and multi-cloud environments. - Collaborating with quantitative researchers to enhance workflows and design platform capabilities. - Designing and optimizing distributed training pipelines for GPU-accelerated workloads, improving compute efficiency, and isolating resources. - Enabling large-scale experimentation, model versioning, and transparent research through robust tool development. - Supporting rapid iteration while maintaining high engineering standards. Candidates should have 2+ years of experience designing and developing large-scale distributed systems, strong Python programming skills, and knowledge of modern ML frameworks. Familiarity with Linux-based HPC clusters, GPU-based workloads, and experience optimizing data pipelines are highly desired. A Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field is also preferred. A global leader in quantitative trading, Tower empowers its employees to thrive in a dynamic, stimulating environment where highly intelligent and motivated colleagues inspire one another. We offer competitive benefits, hybrid work arrangements, and a culture that values teamwork and enjoyment. Join us and help shape the future of our ML research platform, enabling our trading and research teams to perform at their highest potential.

Compensation
Not specified USD

Currency: $ (USD)

City
New York City
Country
United States

Full Job Description

Tower Research Capital is a leading quantitative trading firm founded in 1998. Tower has built its business on a high-performance platform and independent trading teams. We have a 25+ year track record of innovation and a reputation for discovering unique market opportunities.

Tower is home to some of the worlds best systematic trading and engineering talent. We empower portfolio managers to build their teams and strategies independently while providing the economies of scale that come from a large, global organization.

Engineers thrive at Tower while developing electronic trading infrastructure at a world class level. Our engineers solve challenging problems in the realms of low-latency programming, FPGA technology, hardware acceleration and machine learning. Our ongoing investment in top engineering talent and technology ensures our platform remains unmatched in terms of functionality, scalability and performance.

At Tower, every employee plays a role in our success. Our Business Support teams are essential to building and maintaining the platform that powers everything we do combining market access, data, compute, and research infrastructure with risk management, compliance, and a full suite of business services. Our Business Support teams enable our trading and engineering teams to perform at their best.

At Tower, employees will find a stimulating, results-oriented environment where highly intelligent and motivated colleagues inspire each other to reach their greatest potential.

Responsibilities

  • Architecting and developing the next generation of Towers machine learning research platform, with an emphasis on scalability, reliability, observability, and reproducibility
  • Building infrastructure that enables large-scale experimentation, model training, and simulation across on-premises HPC and multi-cloud environments
  • Partnering closely with quantitative researchers to understand evolving research workflows and translate them into robust platform capabilities
  • Designing and optimizing distributed training pipelines for high-throughput, GPU-accelerated workloads
  • Improving experiment management, model versioning, artifact tracking, and data lineage to ensure transparent and reproducible research
  • Developing tools and frameworks that streamline feature engineering, dataset generation, and large-scale backtesting
  • Leading initiatives to improve compute efficiency, resource scheduling, and workload isolation across heterogeneous environments
  • Enhancing platform observability, including metrics, logging, tracing, and debugging capabilities tailored to ML workloads
  • Supporting rapid iteration by implementing features and fixes on tight timelines while maintaining high engineering standards
  • Contributing to long-term architectural decisions that enable the platform to scale with increasing data volumes and model complexity

Qualifications

  • 2+ years of experience designing and building large-scale distributed systems, ideally in support of research or data-intensive workloads
  • Strong programming experience in Python, with a focus on writing clean, maintainable, and high-performance code
  • Experience developing and operating applications on Linux-based HPC clusters and/or cloud platforms
  • Solid understanding of distributed computing concepts, parallel processing, and resource management
  • Experience with GPU-based workloads and familiarity with modern ML frameworks (e.g., PyTorch, TensorFlow, JAX)
  • Experience optimizing data pipelines and handling large-scale structured and unstructured datasets
  • Strong troubleshooting skills with the ability to debug complex, cross-layer system issues
  • Ability to work independently in a fast-paced, research-driven environment
  • Strong communication skills and experience collaborating directly with researchers or data scientists

Preferred Attributes

  • Experience building internal ML platforms or research tooling at scale
  • Familiarity with experiment tracking systems, workflow orchestration frameworks, and model lifecycle management
  • Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes)
  • Exposure to quantitative finance, simulation systems, or other latency- and performance-sensitive domains

Benefits

Towers headquarters are in the historic Equitable Building, right in the heart of NYCs Financial District and our impact is global, with over a dozen offices around the world.

At Tower, we believe work should be both challenging and enjoyable. That is why we foster a culture where smart, driven people thrive without the egos. Our open concept workplace, casual dress code, and well-stocked kitchens reflect the value we place on a friendly, collaborative environment where everyone is respected, and great ideas win.

Our benefits include:

  • Generous paid time off policies
  • Savings plans and other financial wellness tools available in each region
  • Hybrid working opportunities
  • Free breakfast, lunch and snacks daily
  • In-office wellness experiences and reimbursement for select wellness expenses (e.g., gym, personal training and more)
  • Company-sponsored sports teams and fitness events (JPM Corporate Challenge, Cycle for Survival, Wall Street Rides FAR and more)
  • Volunteer opportunities and charitable giving
  • Social events, happy hours, treats and celebrations throughout the year
  • Workshops and continuous learning opportunities

At Tower, youll find a collaborative and welcoming culture, a diverse team and a workplace that values both performance and enjoyment. No unnecessary hierarchy. No ego. Just great people doing great work together.

Tower Research Capital is an equal opportunity employer.

Machine Learning Engineer

Compensation

Not specified USD

City: New York City

Country: United States

Tower Research logo
Proprietary Trading

5 days ago

No clicks

at Tower Research

ExperiencedNo visa sponsorship

**Machine Learning Engineer** at Tower Research Capital focuses on architecting and developing the next generation of our ML research platform, emphasizing scalability, reliability, and user-centric design. Key responsibilities include: - Building and optimizing large-scale distributed systems for ML workloads across on-premises HPC and multi-cloud environments. - Collaborating with quantitative researchers to enhance workflows and design platform capabilities. - Designing and optimizing distributed training pipelines for GPU-accelerated workloads, improving compute efficiency, and isolating resources. - Enabling large-scale experimentation, model versioning, and transparent research through robust tool development. - Supporting rapid iteration while maintaining high engineering standards. Candidates should have 2+ years of experience designing and developing large-scale distributed systems, strong Python programming skills, and knowledge of modern ML frameworks. Familiarity with Linux-based HPC clusters, GPU-based workloads, and experience optimizing data pipelines are highly desired. A Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field is also preferred. A global leader in quantitative trading, Tower empowers its employees to thrive in a dynamic, stimulating environment where highly intelligent and motivated colleagues inspire one another. We offer competitive benefits, hybrid work arrangements, and a culture that values teamwork and enjoyment. Join us and help shape the future of our ML research platform, enabling our trading and research teams to perform at their highest potential.

Full Job Description

Tower Research Capital is a leading quantitative trading firm founded in 1998. Tower has built its business on a high-performance platform and independent trading teams. We have a 25+ year track record of innovation and a reputation for discovering unique market opportunities.

Tower is home to some of the worlds best systematic trading and engineering talent. We empower portfolio managers to build their teams and strategies independently while providing the economies of scale that come from a large, global organization.

Engineers thrive at Tower while developing electronic trading infrastructure at a world class level. Our engineers solve challenging problems in the realms of low-latency programming, FPGA technology, hardware acceleration and machine learning. Our ongoing investment in top engineering talent and technology ensures our platform remains unmatched in terms of functionality, scalability and performance.

At Tower, every employee plays a role in our success. Our Business Support teams are essential to building and maintaining the platform that powers everything we do combining market access, data, compute, and research infrastructure with risk management, compliance, and a full suite of business services. Our Business Support teams enable our trading and engineering teams to perform at their best.

At Tower, employees will find a stimulating, results-oriented environment where highly intelligent and motivated colleagues inspire each other to reach their greatest potential.

Responsibilities

  • Architecting and developing the next generation of Towers machine learning research platform, with an emphasis on scalability, reliability, observability, and reproducibility
  • Building infrastructure that enables large-scale experimentation, model training, and simulation across on-premises HPC and multi-cloud environments
  • Partnering closely with quantitative researchers to understand evolving research workflows and translate them into robust platform capabilities
  • Designing and optimizing distributed training pipelines for high-throughput, GPU-accelerated workloads
  • Improving experiment management, model versioning, artifact tracking, and data lineage to ensure transparent and reproducible research
  • Developing tools and frameworks that streamline feature engineering, dataset generation, and large-scale backtesting
  • Leading initiatives to improve compute efficiency, resource scheduling, and workload isolation across heterogeneous environments
  • Enhancing platform observability, including metrics, logging, tracing, and debugging capabilities tailored to ML workloads
  • Supporting rapid iteration by implementing features and fixes on tight timelines while maintaining high engineering standards
  • Contributing to long-term architectural decisions that enable the platform to scale with increasing data volumes and model complexity

Qualifications

  • 2+ years of experience designing and building large-scale distributed systems, ideally in support of research or data-intensive workloads
  • Strong programming experience in Python, with a focus on writing clean, maintainable, and high-performance code
  • Experience developing and operating applications on Linux-based HPC clusters and/or cloud platforms
  • Solid understanding of distributed computing concepts, parallel processing, and resource management
  • Experience with GPU-based workloads and familiarity with modern ML frameworks (e.g., PyTorch, TensorFlow, JAX)
  • Experience optimizing data pipelines and handling large-scale structured and unstructured datasets
  • Strong troubleshooting skills with the ability to debug complex, cross-layer system issues
  • Ability to work independently in a fast-paced, research-driven environment
  • Strong communication skills and experience collaborating directly with researchers or data scientists

Preferred Attributes

  • Experience building internal ML platforms or research tooling at scale
  • Familiarity with experiment tracking systems, workflow orchestration frameworks, and model lifecycle management
  • Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes)
  • Exposure to quantitative finance, simulation systems, or other latency- and performance-sensitive domains

Benefits

Towers headquarters are in the historic Equitable Building, right in the heart of NYCs Financial District and our impact is global, with over a dozen offices around the world.

At Tower, we believe work should be both challenging and enjoyable. That is why we foster a culture where smart, driven people thrive without the egos. Our open concept workplace, casual dress code, and well-stocked kitchens reflect the value we place on a friendly, collaborative environment where everyone is respected, and great ideas win.

Our benefits include:

  • Generous paid time off policies
  • Savings plans and other financial wellness tools available in each region
  • Hybrid working opportunities
  • Free breakfast, lunch and snacks daily
  • In-office wellness experiences and reimbursement for select wellness expenses (e.g., gym, personal training and more)
  • Company-sponsored sports teams and fitness events (JPM Corporate Challenge, Cycle for Survival, Wall Street Rides FAR and more)
  • Volunteer opportunities and charitable giving
  • Social events, happy hours, treats and celebrations throughout the year
  • Workshops and continuous learning opportunities

At Tower, youll find a collaborative and welcoming culture, a diverse team and a workplace that values both performance and enjoyment. No unnecessary hierarchy. No ego. Just great people doing great work together.

Tower Research Capital is an equal opportunity employer.