Lead Machine Learning Engineer @ Remote

JOB DESCRIPTION Employment Type – CONTRACT ONLY W2/1099 Client is looking for Citizens/GC s As a Senior or Lead Machine Learning Engineer on our Applied AI team, you will operate at the frontier of AI-driven innovation. You will design, fine-tune, and implement state-of-the-art language model applications and machine learning systems, integrating AI-powered solutions for fraud detection, decision automation, and process optimization. This role requires a blend of technical leadership, hands-on engineering expertise, and a genuine passion for deploying AI and ML models at scale. What We're Seeking • Experience: 5+ years of hands-on experience in machine learning engineering, with a strong track record delivering large-scale AI/ML systems from research to production. • ML Foundations: Deep expertise in ML algorithms, deep learning architectures, and the underlying mathematical foundations — particularly linear algebra, probability, and statistics. • Data & Pipelines: Proven proficiency in working with large-scale datasets and building efficient, reliable AI data pipelines. • Model Deployment: Hands-on experience packaging and deploying ML models as APIs for seamless integration into production environments. • MLOps: Familiarity with MLOps tooling and platforms such as MLflow, Azure ML, or Vertex AI, with an understanding of model lifecycle management. • Cloud-Native AI: Experience with cloud-native AI architectures, including distributed model training and scalable deployment patterns on AWS, GCP, or Azure. • LLM Expertise: Strong background in LLM architectures, prompt engineering, fine-tuning, model adaptation, and RAG techniques. • Evaluation & Testing: Robust understanding of AI evaluation methodologies, testing frameworks, and A/B testing for AI-driven applications. • Deep Learning Frameworks: Proficiency with PyTorch, JAX, or TensorFlow. • Vector Databases & Monitoring: Knowledge of vector databases (e.g., Pinecone, Weaviate, pgvector) and AI model monitoring practices including drift detection and governance. • Software Engineering: Strong software engineering fundamentals, with demonstrated ability to write clean, maintainable, and production-quality AI code. • Leadership: Experience mentoring engineering teams and driving AI adoption across cross-functional groups. • Research Contributions: Publications, patents, or open-source contributions in AI/ML are a plus. • Education: Bachelor's, Master's, or PhD in Computer Science, a related field, or equivalent practical experience, with a focus on machine learning. Best Regards. Bini Skaria, DRS IT Solutions Inc, 28175 Haggerty Road, Novi, MI 48377 (C) 248-440-7600 EXT-1 (F) 248-859-4430 Bini Skaria | LinkedIn Bini@drsitsolutions.com www.drsitsolutions.com An E-Verified Company Certified Women Business Enterprise (WBENC) Certified Women Owned Small Business (WOSB)