Machine Learning Infrastructure Engineer, GenAI Technology
Description For Machine Learning Infrastructure Engineer, GenAI Technology
Point72, a leading global alternative investment firm, is seeking a Machine Learning Infrastructure Engineer to join their GenAI Technology team. This role sits at the intersection of machine learning and infrastructure engineering, focusing on building and optimizing high-performance systems for large-scale AI workloads.
The position offers an exciting opportunity to work with cutting-edge technology in the financial sector, where you'll be responsible for designing and maintaining scalable distributed systems for model training and inference. You'll collaborate closely with ML researchers and engineers to productionize models efficiently, while ensuring optimal compute utilization and robust deployment pipelines.
The ideal candidate will bring 3-7 years of experience in building ML infrastructure systems, along with deep expertise in distributed systems, container orchestration, and cloud platforms. Strong programming skills in Python and systems-level languages (Go, C++, or Rust) are essential, as is experience with MLOps tools and frameworks.
Point72 offers a comprehensive benefits package including fully-paid healthcare, generous parental leave, mental wellness programs, and competitive compensation with a base salary range of $185,000-$300,000. The company is committed to professional development and maintains a culture that values innovation and technical excellence.
This role presents an unique opportunity to work on sophisticated ML infrastructure challenges while contributing to Point72's mission of reimagining the future of investing. The position is based in either New York or Stamford, where you'll be part of a dynamic team pushing the boundaries of financial technology.
Responsibilities For Machine Learning Infrastructure Engineer, GenAI Technology
- Design, build, and optimize high-performance infrastructure to support large-scale GenAI/ML workloads
- Develop and maintain reliable, scalable distributed systems for model training, inference, and data processing
- Collaborate with ML researchers and engineers to productionize models efficiently
- Own infrastructure monitoring, observability, and cost optimization for GPU/accelerator-based compute environments
- Evaluate and integrate emerging technologies across cloud and on-prem platforms
- Ensure robust security, compliance, and operational excellence in GenAI/ML infrastructure
Requirements For Machine Learning Infrastructure Engineer, GenAI Technology
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related technical field
- 3–7 years of experience building and maintaining scalable compute or ML infrastructure systems
- Deep understanding of distributed systems, container orchestration (Kubernetes), and cloud platforms
- Hands-on experience with MLOps and infrastructure tools
- Proficiency in Python and systems-level programming (e.g., Go, C++, or Rust)
- Strong debugging, performance profiling, and optimization skills across GPU and CPU compute stacks
- Excellent collaboration and communication skills, with a systems-thinking mindset
- Commitment to the highest ethical standards
Benefits For Machine Learning Infrastructure Engineer, GenAI Technology
- Fully-paid health care benefits
- Generous parental and family leave policies
- Volunteer opportunities
- Support for employee-led affinity groups
- Mental and physical wellness programs
- Tuition assistance
- 401(k) savings program with employer match
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