Job Title: Lead Data Science Engineer (ML)
Location: Irving TX – Onsite
Duration: 12 months
We are seeking a Lead Data Science Engineer specializing in Machine Learning Operations (MLOps) to join our growing Data & AI practice. In this role, you will own the end-to-end ML lifecycle — from experimentation and model development to automated deployment and production monitoring — using MLflow as the central platform for experiment tracking, model registry, and deployment orchestration.
Leadership & Collaboration
• Lead a team of 3–6 ML engineers and data scientists; conduct design reviews and mentor junior talent
• Collaborate with client stakeholders to gather requirements, translate them into ML system architecture, and communicate trade-offs
• Define MLOps maturity roadmaps for client engagements and internal projects
REQUIRED QUALIFICATIONS
Overall 12+ yrs of experience
• 8+ years of experience in data science, ML engineering, or a closely related discipline
• 5+ years of hands-on MLflow usage across Tracking, Projects, Models, and Registry components
• Strong proficiency in Python; experience with ML frameworks: scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow
• Demonstrated experience building production-grade ML pipelines on at least one major cloud platform (AWS, Azure, Google Cloud Platform)
• Deep knowledge of containerization (Docker, Kubernetes) and infrastructure-as-code (Terraform, Helm)
• Experience with feature store design, data versioning (DVC), and model governance frameworks
• Strong SQL and working knowledge of distributed computing (Spark, Dask)
• Excellent communication skills; ability to present technical concepts to executive and non-technical audiences
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