Machine Learning Infrastructure Engineer, Genai Technology

Point72 Asset Management LP

United States
Base: $180,000-$300,000 usd; bonus: discretionary ...
On-site
Distributed systems design
Kubernetes container orchestration
Python and go/c++/rust programming
Point72 Asset Management is seeking a Machine Learning Infrastructure Engineer to enhance their technology team's capabilities in supporting generative AI and machine learning workloads. The role focuses on designing and implementing scalable infrastructure while collaborating closely with ML researchers and engineers

Job Summary

  • The role involves designing high-performance infrastructure to support large-scale generative AI and machine learning workloads for faster model iteration.
  • Point72 offers fully-paid health care benefits, generous parental leave, and tuition assistance to support employee well-being and career growth.
  • Candidates will collaborate with ML researchers to optimize compute utilization, training throughput, and inference latency across cloud and on-prem environments.

Matching Summary

Match Score: 85

Point72 Asset Management is seeking a Machine Learning Infrastructure Engineer to enhance their technology team's capabilities in supporting generative AI and machine learning workloads. The role focuses on designing and implementing scalable infrastructure while collaborating closely with ML researchers and engineers.

Salary

Base: $180,000-$300,000 USD; Bonus: Discretionary bonus compensation included; Benefits: Comprehensive package with health care and 401(k) match

Skills & Requirements

Must-have

  • Distributed systems design
  • Kubernetes container orchestration
  • Python and Go/C++/Rust programming
  • GPU compute optimization
  • ML infrastructure tools like MLflow Ray
  • Cloud platforms AWS GCP Azure

Nice-to-have

  • Reinforcement learning concepts
  • Infrastructure-as-code Terraform
  • Security and compliance expertise
  • Mentoring engineering teams
  • Cost management strategies

Key Requirements

  • Bachelor's or master's degree in CS or EE
  • 3-7 years experience in scalable ML infrastructure
  • Proficiency in Python and systems-level languages

Work Rights

Not specified

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