Machine Learning Infrastructure Engineer, GenAI Technology
New York | Stamford
Full Time Senior-level / Expert USD 185K - 300K
Point72
We invest in Discretionary Long/Short, Macro, and Systematic strategies. We’re inventing the future of finance by revolutionizing how we develop our people and how we use data to shape our thinking. Join our team to innovate, experiment, and be...A Career with Point72’s Technology Team
As Point72 reimagines the future of investing, our Technology group is constantly improving our company’s IT infrastructure, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts experimenting, discovering new ways to harness the power of open source solutions, and embracing enterprise agile methodology. We encourage professional development to ensure you bring innovative ideas to our products while satisfying your own intellectual curiosity.
What you’ll do
- 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, focusing on compute utilization, orchestration, and deployment pipelines.
- Own infrastructure monitoring, observability, and cost optimization for GPU/accelerator-based compute environments.
- Evaluate and integrate emerging technologies across cloud and on-prem platforms to improve system performance, reliability, and scalability.
- Ensure robust security, compliance, and operational excellence in GenAI/ML infrastructure.
What’s REQUIRED
- 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 (e.g., AWS, GCP, Azure).
- Hands-on experience with MLOps and infrastructure tools (e.g., MLflow, Ray, Airflow, Kubeflow, Terraform).
- 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.
We take care of our people
We invest in our people, their careers, their health, and their well-being. When you work here, we provide:
- Fully-paid health care benefits
- Generous parental and family leave policies
- Volunteer opportunities
- Support for employee-led affinity groups representing women, people of color and the LGBTQ+ community
- Mental and physical wellness programs
- Tuition assistance
- A 401(k) savings program with an employer match and more
About point72
Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth. For more information, visit www.Point72.com/about.
The annual base salary range for this role is $185,000-$300,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.
Tags: Agile Airflow AWS Azure Computer Science Distributed Systems Engineering GCP Generative AI GPU Kubeflow Kubernetes Machine Learning MLFlow ML infrastructure MLOps Model training Open Source Pipelines Python Rust Security Terraform
Perks/benefits: 401(k) matching Career development Health care Parental leave Salary bonus Startup environment Wellness
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