Senior Machine Learning Engineer – Consultant
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Job Description
Senior AI/ML Engineer Consultant responsible for implementing AI solutions and mentoring juniors at leading AI consultancy Provectus. Join to solve complex technical challenges and impact 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. Master's degree is preferred.
- 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.
Benefits:
- Opportunity to lead the technical implementation of cutting-edge AI solutions.
- A clear path to the Solution Architect role.
- Exposure to diverse technical challenges across industries.
- Professional development and certification support.
- Flexible, remote-first workplace.
- Comprehensive benefits, including health, dental, vision, 401(k) with company match, and unlimited PTO.
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