Provectus

Middle AI/ML Engineer

Apply Now

Job Description

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.

    • Apply Now
    Job Summary

    Senior Staff Machine Learning Engineer, Communication & Connectivity

    Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion gue

    • Remote USA
    • 26 days ago

    Senior Data Scientist / Machine Learning Engineer

    Astro Sirens is an IT staffing agency based in Austin, Texas. We connect talented professionals from around the world with U.S. companies, offering exciting opportunities

    • Senior
    • Remote India
    • 15 hours ago

    Senior Machine Learning Engineer - NLP

    We are looking for a Senior Machine Learning Engineer to join our growing engineering team. You’re the perfect fit for this role if you are passionate about solving probl

    • Senior
    • Remote United Kingdom
    • 5 months ago

    Senior AI/ML Engineer - Inventory Forecasting & Decision Systems

    Role: Senior AI/ML Engineer — Inventory Forecasting & Decision SystemsHours: 9am - 6pm Eastern Time (Remote)USD Salary: $20-$40/HRWe are seeking a highly skilled Senior A

    • Senior
    • Remote Croatia
    • 13 days ago