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Provectus
Provectus

Middle AI/ML Engineer (GenAI, AWS)

Colombia
Full-Time
Remote

TLDR

Design and deliver ML solutions using AI coding tools, mentor junior engineers, and contribute to the internal AI toolkit in a dynamic engineering environment.

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 global 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;
  • 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.
    • 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.

    • Benefits

    Health Insurance

    Health benefits

    Learning Budget

    Learning budget for courses, certifications, and conferences

    Provectus
    Provectus

    Provectus builds robust machine learning infrastructure and production-grade solutions that empower companies to leverage AI and transform their operations and competitive strategies. We cater to businesses facing complex ML challenges, delivering innovative technology that drives significant value and societal impact.

    Founded
    Founded 2010
    Employees
    500+ employees
    Industry
    Professional Services
    View company profile
    ML Engineer
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