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**Provectus is an AWS Premier Consulting Partner and AI consultancy featured in Forrester's AI Technical Services Landscape, with 15+ years of experience and 400+ engineers. We build production AI for general enterprises in partnership with Anthropic, Cohere, and AWS.**:
**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;
- 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.

**What You Need**:
**Machine Learning**
- 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.

**LLMs & Generative AI**
- 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.

**Agentic Engineering (required)**
- 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.

**Cloud & Infrastructure**
- 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).

**MLOps & Data**
- 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.

**Experience & Education**
- 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.

**Key Traits**
- 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.

**Nice to Have**
- AWS certifications;
- Kubernetes experience;
- GraphRAG or custom MCP server experience
- Open-source contributions or published work on agentic systems.

**What We Offer**:

- 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.

Postúlate en Kit Empleo: kitempleo.com.co/empleo/1as5t0

📌 Middle Ai/ Ml Engineer (Medellín)
🏢 Provectus
📍 Medellín