Senior AI/ML Engineer NLP & MLOps at Scale

Reflexive Concepts, LLC

Maryland

On-site

USD 120,000 - 180,000

Full time

2 days ago
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Job summary

Reflexive Concepts, LLC is seeking an AI/ML Engineer III to advance applied machine learning in large-scale programs and contracts. The role emphasizes data selection, model development, and production deployment with a focus on verification, validation, and system integration oversight.

Qualifications include ten years of ML experience, a Master’s or PhD in a related field, and expertise with PyTorch/TensorFlow. NLP experience is a plus, and MLOps practices in production environments are valued.

Qualifications

  • Ten years of applied ML experience required.
  • Master's or PhD in AI, data science, or related field.
  • 5 extra years of ML with a Bachelor's can substitute for a Master's.
  • Experience with PyTorch and TensorFlow.

Responsibilities

  • Select appropriate data sets and perform statistical analysis.
  • Research, implement, and tune a broad range of AI/ML algorithms and tools.
  • Build and operate MLOps pipelines to train, deploy, monitor, and retrain models at scale.
  • Transform prototypes into scalable production solutions.
  • Oversee test and evaluation of AI/ML algorithms through iterative design.
  • Design or select data and knowledge representation methods.
  • Verify data and model output quality and identify distribution shifts.
  • Provide system integration oversight.

Skills

Applied ML
PyTorch
TensorFlow
Data analysis
Statistical analysis

Education

Master's degree
PhD

Tools

MLOps

Job description

Reflexive Concepts, LLC is seeking an AI/ML Engineer III to advance applied machine learning in large-scale programs and contracts. The role emphasizes data selection, model development, and production deployment with a focus on verification, validation, and system integration oversight.

Qualifications include ten years of ML experience, a Master’s or PhD in a related field, and expertise with PyTorch/TensorFlow. NLP experience is a plus, and MLOps practices in production environments are valued.

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