Machine Learning Engineer - Senior Consultant

Provectus helps companies adopt ML/AI to transform their operations and drive value. As a Senior AI/ML Engineer Consultant, you'll be responsible for implementing sophisticated AI solutions, mentoring junior team members, and solving complex technical challenges while serving as a trusted advisor for enterprise clients.

Responsibilities:

• Design and build enterprise-grade AI/ML systems end-to-end — from data pipeline through model development, deployment, and production monitoring — given functional and non-functional requirements
• Develop an experimentation roadmap. Set up a reproducible experimentation environment and maintain experimentation pipelines
• Monitor and maintain ML models in production to ensure optimal performance
• Develop robust, production-quality Python code and reusable software modules that power data processing workflows, ML pipelines, and AI-driven applications — going well beyond notebook-style scripting
• Leverage cloud-native data and ML services (AWS stack preferred: SageMaker, EMR, S3, Lambda, ECR)
• Conduct technical discovery workshops with enterprise clients, contributing to solution architecture and proposal development with a full-stack technical perspective
• Lead technical delivery for major client initiatives
• Drive adoption of MLOps best practices and technical standards
• Mentor junior engineers and shape the team's technical direction
• Evaluate and champion new technologies and frameworks

Requirements:

• 5+ years of hands-on ML engineering experience
• A bachelor's degree in Computer Science, Mathematics, or a related field is required
• Comfortable with standard ML algorithms and underlying math
• Strong hands-on experience with LLMs in production, RAG architecture, and agentic systems
• Practical experience with solving classification and regression tasks in general, feature engineering
• Practical experience with cloud platforms (AWS stack is preferred, e.g. Amazon SageMaker, ECR, EMR, S3, AWS Lambda)
• Experience with MLOps, strong track record of delivering production ML systems
• Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines
• Solid software engineering skills (i.e., ability to produce well-structured modules, not only notebook scripts)
• Python expertise, Docker
• Excellent communication and problem-solving skills
• Excellence in technical leadership and mentoring
• Prior experience in consulting or professional services
• Master's degree is preferred
• AWS stack preferred: SageMaker, EMR, S3, Lambda, ECR
• Experience with deep learning models
• Experience with machine learning pipelines to orchestrate complicated workflows
• Experience with Spark/Dask