Senior Machine Learning Engineer, Post-Training and Inference

Join one of the top options market makers in the industry, a firm known for its cutting-edge technology, world-class engineering talent, and commitment to advancing AI and machine learning in trading.

The firm is building a new ML initiative from the ground up and is seeking a Senior ML Engineer with deep expertise in post-training and inference. The current team consists of four people, including engineers from two leading competitors and a researcher from a top FAANG AI lab. With only a handful of hires planned, this is an opportunity to have outsized ownership and influence on the direction of the platform from day one.

Unlike traditional trading firms that rely on star traders, leading market makers depend on elite engineers and researchers to build high-performance, data-intensive systems that drive the business. If you're excited about working on cutting-edge ML challenges in a highly technical environment, this is a unique opportunity to help shape the future of AI in trading.

What You'll Do

• Design and build scalable infrastructure for large-scale model training, post-training, and inference.
• Develop and optimize inference systems to maximize performance, efficiency, and reliability.
• Improve and extend deep learning frameworks and tooling for advanced ML workloads.
• Partner closely with researchers to accelerate experimentation and production deployment.
• Take ownership over key areas of the ML stack, helping define architecture, systems, and best practices from the ground up.

What You Bring

• 8 years of machine learning experience at a top technology, AI, trading, or research-focused organization promotions
• Strong expertise in post-training techniques, model optimization, or large-scale inference systems.
• Experience with low-level performance optimization, including CUDA or similar GPU programming technologies.
• Deep knowledge of modern deep learning frameworks such as PyTorch, JAX, or TensorFlow.
• Strong C and Python programming skills.
• BS, MS, or PhD in Computer Science, Engineering, Mathematics, or a related technical field.

Why Consider It?

• Join a small, elite team with direct impact on strategy, architecture, and technical direction.
• Work alongside engineers and researchers from some of the most respected firms and AI labs in the world.
• Tackle challenging ML infrastructure problems at the intersection of machine learning and quantitative trading.
• Significant ownership, autonomy, and visibility from day one.