Senior GenAI & Agentic Systems Engineer (Production ML)

Provectus; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Provectus in the United States is seeking an ML Engineer to build and productionize AI/ML solutions. You will collaborate with engineers, data scientists, and product managers to create robust models and scalable pipelines.

Responsibilities include creating models from scratch or improving existing ones, designing experimentation roadmaps, and maintaining production systems. Strong Python and Docker skills, plus experience with LLMs, RAG, and cloud platforms, are highly valued.

Qualifications

• Comfortable with standard ML algorithms and underlying math.
• Hands-on experience with LLMs in production, RAG and agentic systems.
• AWS Bedrock experience strongly preferred.
• Experience with classification and regression tasks and feature engineering.
• ML models in production experience.
• Experience with NLP, LLMs, and recommendation engines.
• Solid software engineering practices.

Responsibilities

• Create ML models from scratch or improve existing models.
• Collaborate with engineering, data scientists, and product managers on production models.
• Develop experimentation roadmap.
• Set up a reproducible experimentation environment and maintain experimentation pipelines.
• Monitor and maintain ML models in production to ensure optimal performance.
• Write clear and comprehensive documentation for ML models, processes, and pipelines.
• Stay updated with the latest developments in ML and AI and propose innovative solutions.

Skills

ML algorithms

Production ML

Problem solving

Communication

Tools

Python

Docker

AWS Bedrock

Spark/Dask

Job description

Provectus in the United States is seeking an ML Engineer to build and productionize AI/ML solutions. You will collaborate with engineers, data scientists, and product managers to create robust models and scalable pipelines.

Responsibilities include creating models from scratch or improving existing ones, designing experimentation roadmaps, and maintaining production systems. Strong Python and Docker skills, plus experience with LLMs, RAG, and cloud platforms, are highly valued.