Senior ML Engineer

We are seeking an experienced Machine Learning Engineer to design, build, and operationalize scalable AI/ML solutions supporting mission-critical initiatives. This role focuses on transforming data science prototypes into secure, high-performing production systems using Python, leading ML frameworks, and modern cloud infrastructure.

What You'll Do:

Model Development

• Partner with data scientists and domain experts to design, build, and train ML systems

• Develop experiments, prototypes, and proof-of-concepts to refine model performance

• Build scalable, reusable training pipelines using Databricks and MLflow

LLM & Advanced AI Implementation

• Implement and optimize Large Language Models (LLMs)

• Develop Retrieval-Augmented Generation (RAG) systems

• Design and deploy AI agent architectures for enterprise applications

Deployment & MLOps

• Productionize models using CI/CD best practices

• Deploy solutions via MLflow, AWS SageMaker, or custom APIs

• Monitor models for performance, drift, latency, and accuracy

• Continuously improve efficiency and scalability

Data Architecture & Integration

• Align ML pipelines with Bronze, Silver, and Gold layers in a Medallion Architecture

• Engineer high-quality features and maintain robust training/inference pipelines

Collaboration & Leadership

• Document ML processes, artifacts, and outcomes clearly

• Contribute to agile ceremonies and stakeholder updates

• Mentor junior engineers and promote ML best practices

Required Qualifications

• 5+ years of experience in ML Engineering or Applied Machine Learning

• Strong Python programming expertise

• Hands-on experience with ML frameworks (scikit-learn, XGBoost, PyTorch, TensorFlow)

• Experience with TensorFlow, PyTorch, or Hugging Face training frameworks

• Proficiency in Databricks, MLflow, and PySpark

• Strong understanding of end-to-end model lifecycle and MLOps

• Experience with AWS-based infrastructure and DevOps workflows

• Proven experience productionizing ML models

• Experience with supervised, unsupervised, and deep learning techniques

• Solid software engineering fundamentals

• Practical experience building and deploying LLMs, RAG systems, and AI agents

• Experience with AWS services including S3, EC2, Lambda, SageMaker, and Step Functions

• Strong communication and teamwork skills

Clearance Requirement

• Must be a U.S. Citizen

• Must be able to obtain a U.S. Federal Government client badge

• Ability to pass a government background investigation required

• Active DOT clearance preferred