Machine Learning Engineer - Senior Consultant
USA
About project
About Provectus
Provectus helps companies adopt ML/AI to transform the ways they operate, compete, and drive value. The focus of the company is on building ML Infrastructure to drive end-to-end AI transformations, assisting businesses in adopting the right AI use cases, and scaling their AI initiatives organization-wide in such industries as Healthcare & Life Sciences, Retail & CPG, Media & Entertainment, Manufacturing, and Internet businesses. Our team combines deep technical expertise with a consultative approach to deliver innovative AI solutions that create lasting business impact.
Position Impact
As a Senior AI/ML Engineer Consultant, you'll be responsible for the technical implementation of sophisticated AI solutions while mentoring junior team members and establishing best practices. You'll have the opportunity to solve complex technical challenges while growing into a trusted technical advisor for our enterprise clients.
What You'll Do:
- 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.
What You'll Bring:
- 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.
- Experience with deep learning models.
- Experience with machine learning pipelines to orchestrate complicated workflows.
- Experience with Spark/Dask.
What We Offer:
- 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.