AI Machine Learning Engineer

Position: AI Machine Learning Engineer

Location: The Role is Hybrid in Virginia, Washington DC and Maryland

Employment Type: Full-time / Contract

Role Overview

We are seeking an experienced Machine Learning Engineer with a strong background in Large Language Models (LLMs), Healthcare, MLOps, and AWS cloud technologies. The ideal candidate will be responsible for building scalable data pipelines, optimising machine learning models, and deploying AI solutions into production environments. This role requires close collaboration with Data Scientists, Engineers, and cross-functional teams to develop innovative AI-driven solutions.

Key Responsibilities

• Design, build, and maintain robust data pipelines supporting the end-to-end machine learning lifecycle.
• Develop and optimize machine learning models for performance, scalability, and reliability.
• Create and manage deployment scripts for automated model deployment and monitoring.
• Lead production deployments of machine learning and AI solutions.
• Work closely with Data Scientists and business stakeholders to deliver AI initiatives.
• Implement MLOps best practices for model training, versioning, deployment, and monitoring.
• Utilize AWS services such as SageMaker, Lambda, Glue, and related technologies to build and manage ML solutions.
• Ensure high-quality data processing, model governance, and operational excellence throughout the project lifecycle.
• Required Qualifications
• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
• 6+ years of experience as a Machine Learning Engineer.
• 3+ years of hands-on experience with Large Language Models (LLMs).
• 3+ years of experience within the Healthcare domain.
• Strong expertise in building and managing ML data pipelines.
• Proven experience deploying machine learning models to production environments.
• Experience writing deployment and automation scripts for ML applications.
• Deep understanding of AI/ML concepts, algorithms, and real-world applications.

Technical Skills

• Strong programming skills in Python, SQL, and/or R.
• Experience with machine learning frameworks such as TensorFlow.
• Hands-on experience with AWS cloud services, including:
• AWS SageMaker
• AWS Lambda
• AWS Glue
• Other AWS AI/ML services
• Knowledge of Natural Language Processing (NLP) and Generative AI concepts.
• Understanding of Big Data processing and analytics.

Preferred Experience

• Developing and deploying Healthcare-related AI/ML solutions.
• Building and supporting LLM-based applications.
• Working with cloud-native AI architectures and MLOps platforms.
• Experience collaborating in Agile development environments.

Soft Skills

• Excellent analytical and problem-solving abilities.
• Strong verbal and written communication skills.
• Ability to explain complex technical concepts to both technical and non-technical stakeholders.
• Ability to manage multiple projects in a fast-paced environment while maintaining high-quality deliverables.
• If this opportunity aligns with your experience, especially your background in Machine Learning Engineering, LLMs, Healthcare, and AWS, please let me know. I would be happy to discuss the role further and walk you through the next steps.