Note: The job is a remote job and is open to candidates in USA. Confidential is seeking an ML & AI Engineering Team Lead to guide and mentor a team of machine learning, AI, and data professionals in a consulting environment. The role combines technical leadership, team management, client consultation, and hands-on oversight of end-to-end AI/ML delivery on AWS, including generative AI, MLOps, data pipelines, and cloud architecture.
Responsibilities
- Mentor & Lead: Direct, mentor, and foster professional growth for a team of ML/Data Engineers and Data Scientists, driving engineering best practices, code reviews, and high delivery standards
- Project & Resource Orchestration: Partner with Project Managers and Solutions Architects to estimate project scope, allocate engineering resources, and ensure on-time delivery across multiple client engagements
- Client & Stakeholder Management: Serve as a trusted technical voice in client discussions, helping translate complex business requirements into scalable AI/ML architectures
- Process Improvement: Establish standard operating procedures, reusable AI/ML solution patterns (blueprints), and MLOps frameworks to accelerate client time-to-value
- AI/ML & GenAI Architecture: Lead the technical design and deployment of predictive models, deep learning architectures, and generative AI/Agentic solutions on AWS
- Data Lake & Pipeline Engineering: Oversee the architecture and operation of scalable big data pipelines, data lakes, and streaming architectures (SQL, Spark, Kafka, Kinesis)
- Model Lifecycle & MLOps: Standardize the ML lifecycle—from data prep and feature engineering to deployment, monitoring, and bias tracking using AWS AI/ML services (SageMaker, Bedrock, etc.)
- Security & Compliance: Ensure all client solutions adhere to strict data security, compliance, data isolation, and governance standards in AWS environments
Skills
- 2+ years of experience leading, mentoring, or managing technical teams (ML Engineers, Data Scientists, or Data Engineers) in a professional services or consulting setting
- 5+ years of hands-on experience in Machine Learning, AI, or Data Engineering, with a Bachelor's or Master's degree in Computer Science, Mathematics, or a related quantitative field
- Strong expertise in AWS native services (SageMaker, Bedrock, Glue, EMR, Redshift, Kinesis, EC2, Lambda)
- Advanced proficiency in Python (including PyTorch, TensorFlow, Scikit-learn) and complex SQL query authoring
- Proven track record building end-to-end MLOps pipelines, continuous model monitoring, and automated retraining workflows
- Experience with big data engines (Spark, ElasticSearch), relational databases (PostgreSQL, MySQL), and NoSQL engines (DynamoDB)
- Exceptional verbal and written communication skills with experience presenting technical roadmaps to external enterprise clients and executive teams
- AWS Machine Learning Specialty (Strongly Preferred)
- AWS Solutions Architect - Associate (Strongly Preferred)
Benefits
- Home based
- Full-time, Permanent
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