Senior AI/ML Engineer - Scale & Deploy Intelligent Models

HP

Spring (TX)

On-site

USD 147,000 - 231,000

Full time

4 days ago
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Benefits offered by this job

Health insurance
Dental insurance
Vision insurance
Disability insurance
Life insurance
Flexible spending account
Parental leave
Paid holidays

Job summary

HP is seeking a Senior Machine Learning Engineer to design, develop, and implement cutting-edge ML models. You will collaborate with cross-functional teams to transform data into actionable insights by selecting, training, and optimizing algorithms for robust production systems.

You will ensure models are trained, validated, and optimized for performance, and you will manage data pipelines, monitoring, and scalable data operations across distributed environments.

Qualifications

  • Bachelor’s or higher degree in Computer Science, Statistics, Mathematics, Data Science or related field.
  • Typically 7–10 years of work experience in ML, algorithms, or related area.

Responsibilities

  • Architects, develops and programs ML solutions supporting model lifecycle.
  • Builds data pipelines and monitoring in distributed environments.
  • Defines data collection protocols and develops, trains and evaluates models.
  • Optimizes scalable data operations to drive ML product improvements.
  • Collaborates with analytics to translate data needs into ML solutions.
  • Integrates models into production with DevOps and automated deployment.
  • Monitors delivery of AI/ML solutions and communicates results.
  • Participates in cutting-edge AI/ML research and stays current.
  • Manages compute cluster hosting and resource planning.

Skills

Python
PyTorch
Kubernetes
AWS
CUDA
NLP
Machine Learning
Big Data
vLLM
RAG
Software Engineering
Attention to detail
Communication

Education

Four-year or graduate degree in CS/Statistics/Data Science

Tools

Kubernetes
PyTorch
AWS
CUDA

Job description

HP is seeking a Senior Machine Learning Engineer to design, develop, and implement cutting-edge ML models. You will collaborate with cross-functional teams to transform data into actionable insights by selecting, training, and optimizing algorithms for robust production systems.

You will ensure models are trained, validated, and optimized for performance, and you will manage data pipelines, monitoring, and scalable data operations across distributed environments.

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