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Lead Machine Learning Engineer, Inference & Performance

2 weeks, 6 days ago
Anywhere
Full-time
Senior
Machine Learning Engineer
Software Development
GCP Generative AI Kubernetes LLM Machine Learning Neural Networks Python Shell Scripting SQL
Apply Now
Egen.ai

Egen.ai

Egen.ai specializes in providing technology services that leverage cloud computing, data analytics, and artificial intelligence to enhance document intelligence and drive productivity and growth for its clients.

IT Services
Founded 2000
View All Jobs 10

Description

  • Own the full lifecycle of AI features from initial prototype to robust, scalable production services.
  • Design and optimize production LLM serving to maximize throughput and minimize latency.
  • Instrument and profile training runs to identify bottlenecks and improve performance.
  • Tune attention implementations and other inference/training techniques for specific hardware platforms.
  • Deploy and operate multiple models within shared GPU clusters on Google Kubernetes Engine (GKE).
  • Improve GPU utilization, throughput-per-dollar, and overall fleet efficiency.
  • Collaborate with clients to translate business needs and constraints into AI architectures.
  • Write clean, maintainable code and apply a disciplined software engineering approach to AI systems.

Requirements

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
  • 5+ years of experience in ML/AI engineering, with meaningful experience in performance, infrastructure, or systems.
  • Proven track record of deploying and optimizing models in a production environment.
  • Demonstrated experience profiling and improving GPU utilization for training and/or inference.
  • Hands-on experience with vLLM, SGLang, or comparable high-performance serving stacks.
  • Strong Kubernetes experience, specifically deploying and autoscaling multiple models on shared GPU clusters on Google Cloud/GKE.
  • Mastery of Python and shell scripting.
  • Solid grasp of GPU architecture, LLM inference fundamentals, and the attention mechanism.
  • Fluency with profiling tools for diagnosing compute-bound and memory-bound bottlenecks.
  • Knowledge of data engineering and SQL.
  • Experience with classic machine learning, neural nets, training, and tuning is a strong plus.
  • Comfort reading lower-level CUDA-adjacent performance code is a strong plus.

Benefits

  • Competitive salary.
  • Comprehensive health insurance.
  • Paid leave, including vacation/PTO.
  • Paid holidays.
  • Sick leave.
  • Parental leave.
  • Bereavement leave.
  • 401(k) employer match.
  • Employee referral bonuses.

Interested in this position?

Apply directly on the company website

Apply Now

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