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About the Role

As an AI/ML Applied Research Engineer, you will be at the forefront of our central machine learning infrastructure and research teams. Your primary role is to serve as "Customer Zero" for our internal ML Research platform, focusing on benchmarking, rapid prototyping, and stress-testing software and hardware layers across our distributed ML stack using AI agents and auto-research capabilities. You will identify bottlenecks, create a frictionless testing environment for novel machine learning models, and act as a technical advisor by sharing insights on research progress and guiding strategic engineering efforts.

Responsibilities

Serve as the primary feedback loop for the entire ML stack.
Actively run complex models through our full ML pipeline to test training and inference environments.
Validate the central infrastructure in practice, identifying system bottlenecks before broader rollout.
Build high-level abstractions to bypass setup friction for users.
Integrate core ML tooling with simulation and data frameworks for unified tech stack access.
Enable rapid iteration on real-world data and seamless distributed training via Ray.
Leverage AI agents and auto-research workflows to autonomously generate experiments and stress-test distributed clusters.
Provide data-driven feedback on infrastructure optimization and development needs.
Act as a bridge between infrastructure builders and ML researchers.
Be the first to exhaustively test new models and push the platform's limits.
Document and publish empirical findings on system capabilities and hardware performance.
Assist engineering teams with platform improvements and advise researchers on stack utilization.

Requirements

Deep proficiency in Python and software design principles.
Ability to build clean, scalable APIs and abstractions.
Hands-on experience with modern ML frameworks (PyTorch, TensorFlow, etc.).
Strong practical understanding of training, evaluating, and deploying models at scale.
Experience scaling ML workloads across GPUs and multi-node clusters using frameworks like Ray, Dask, or PyTorch Distributed.
Familiarity with LLM tooling, agentic frameworks, and using AI for automation.
Ability to debug and identify bottlenecks across hardware and software layers.

Skills

Python
Software Design Principles
API Development
Machine Learning
PyTorch
TensorFlow
Distributed Computing
Ray
Dask
PyTorch Distributed
LLM Tooling
Agentic Frameworks
System Profiling
Optimization

Location

NYC Financial District

Work Type

Hybrid

Experience Level

Applied Research Engineer

Salary/Compensations

$200,000-$300,000 base
Discretionary bonus

Benefits

Generous paid time off policies
Savings plans and financial wellness tools
Hybrid working opportunities
Free breakfast, lunch, and snacks daily
In-office wellness experiences and reimbursement
Company-sponsored sports teams and fitness events
Volunteer opportunities and charitable giving
Social events, happy hours, treats, and celebrations
Workshops and continuous learning opportunities

About the Company

Tower Research Capital is a leading quantitative trading firm founded in 1998, built on a high-performance platform and independent trading teams with a 25+ year track record of innovation.
Tower is home to world-class systematic trading and engineering talent, empowering portfolio managers independently while providing global organizational scale.
Engineers develop electronic trading infrastructure, solving challenging problems in low-latency programming, FPGA technology, hardware acceleration, and machine learning.
Ongoing investment in talent and technology ensures an unmatched platform in functionality, scalability, and performance.
Business Support teams are essential to building and maintaining the platform, enabling trading and engineering teams to perform at their best.
Employees find a stimulating, results-oriented environment with highly intelligent and motivated colleagues.
Tower’s headquarters are in NYC’s Financial District, with a global impact and over a dozen offices worldwide.
The company fosters a culture where smart, driven people thrive without egos, valuing a friendly, collaborative environment with an open concept workplace and casual dress code.
A collaborative and welcoming culture, a diverse team, and a workplace that values both performance and enjoyment, with no unnecessary hierarchy or ego.

Equal Opportunity

Tower Research Capital is an equal opportunity employer.