[Hiring] Middle AI/ML Engineer @Provectus

Role Description

As a Middle ML Engineer at Provectus, you will design, build, and deploy production ML solutions for our clients — working independently on most tasks while growing toward senior technical ownership. You'll use AI coding tools daily, mentor junior engineers, and contribute to Provectus's internal AI toolkit.

What You'll Do:

• Build & Ship ML (55%)
  • Design and deliver ML pipelines from experimentation to production;
  • Build and optimize models — supervised, unsupervised, and generative AI;
  • Write clean, tested, modular Python code;
  • Deploy and monitor models; track performance and prevent drift;
  • Contribute to LLM applications: RAG systems and agent workflows;
  • Use AI coding tools on every task to move faster and write better code.
• Agentic & AI-Assisted Engineering (20%)
  • Use Claude Code or similar AI tools to deliver client projects;
  • Build with agent frameworks (Bedrock AgentCore, Strands, CrewAI, or similar);
  • Integrate or build MCP servers for internal and client use;
  • Contribute features, bug fixes, or docs to the Provectus AI toolkit.
• Collaborate & Mentor (15%)
  • Mentor junior engineers and give actionable code review feedback;
  • Work closely with DevOps, Data Engineering, and Solutions Architects;
  • Share knowledge through docs, presentations, or internal workshops.
• Learn & Innovate (10%)
  • Stay current with ML research, GenAI, and agentic frameworks;
  • Propose process improvements and reusable ML accelerators;
  • Participate in architectural design and trade-off discussions.

Qualifications

• Solid grasp of supervised/unsupervised ML: algorithms, evaluation, trade-offs;
• Deep learning hands-on experience: CNNs, RNNs, Transformers — training and fine-tuning;
• Depth in at least one domain: NLP, Computer Vision, Recommendation, or Time Series.
• Experience building LLM apps with OpenAI, Anthropic, or Hugging Face APIs;
• Hands-on RAG design: chunking, embedding, retrieval, generation;
• Familiarity with vector databases (OpenSearch, Pinecone, Chroma, FAISS);
• Understanding of prompt engineering and LLM evaluation.
• Proficient with AI coding tools (Claude Code, Cursor, Copilot, etc.) — beyond autocomplete;
• Experience building tool-using, stateful agents with an orchestration framework;
• Understanding of Model Context Protocol (MCP) — consume or build MCP servers;
• Can write technical specs for AI execution and review/correct AI-generated output;
• Aware of agent monitoring, evaluation, and cost optimization in production.
• Solid AWS: SageMaker, Lambda, S3, ECR, ECS, API Gateway;
• Familiarity with Amazon Bedrock (model invocation, Knowledge Bases, Agents);
• Basic awareness of Infrastructure as Code (Terraform or CloudFormation).
• Production ML deployment experience;
• Experiment tracking with MLflow, W&B, or similar;
• CI/CD pipelines for ML; model monitoring and drift detection;
• Advanced Python (async/await, OOP, packaging); strong pandas, NumPy, SQL;
• Docker for containerized ML workloads.
• 1–3 years of hands-on ML engineering experience;
• At least one ML model deployed to production (or near-production);
• Team-based or client-facing project experience;
• Demonstrated use of AI-assisted development tools;
• Education: Bachelor's/Master's in CS, Data Science, Math, or equivalent practical experience.

Requirements

• Strong problem-solver — breaks complexity into testable pieces;
• Clear communicator — written docs, PRs, and explanations to non-technical stakeholders;
• Fluent English (B2+);
• Proactive — raises blockers early and comes with proposed solutions;
• Collaborative mentor who helps without creating dependency.

Benefits

• Competitive salary based on competencies and market rates;
• Premium AI tooling: Claude Code, Cursor, and Provectus AI toolkit;
• Mentorship from Senior ML Engineers and Tech Leads;
• Clear growth path: Mid-Level → Senior ML Engineer → Tech Lead;
• Learning budget for courses, certifications, and conferences;
• Remote-first culture; work on projects across LATAM, North America, and Europe;
• Health benefits.