Provectus

Provectus

Provectus provides consulting services in artificial intelligence and machine learning, assisting businesses in integrating AI solutions to meet their unique objectives and enhance their operational capabilities across various industries.

Professional Services
251-1K
Founded 2010

Description

  • Design and deliver ML pipelines from experimentation through production.
  • Build, train, and optimize supervised, unsupervised, and generative AI models.
  • Write clean, tested, and modular Python code for ML and GenAI solutions.
  • Deploy, monitor, and maintain models, including performance tracking and drift prevention.
  • Develop LLM applications such as RAG systems and agent workflows.
  • Use AI coding tools daily to accelerate delivery and improve code quality.
  • Build with agent frameworks and integrate or build MCP servers for internal and client use.
  • Mentor junior engineers and provide actionable code review feedback.
  • Collaborate closely with DevOps, Data Engineering, and Solutions Architects.
  • Share knowledge through documentation, presentations, and internal workshops.

Requirements

  • 1–3 years of hands-on ML engineering experience.
  • At least one ML model deployed to production or near-production.
  • Strong understanding of supervised and unsupervised ML, including algorithms, evaluation, and trade-offs.
  • Hands-on deep learning experience with CNNs, RNNs, and Transformers, including training and fine-tuning.
  • Experience in at least one domain such as NLP, Computer Vision, Recommendation, or Time Series.
  • Experience building LLM applications with OpenAI, Anthropic, or Hugging Face APIs.
  • Hands-on RAG design experience, including chunking, embeddings, retrieval, and generation.
  • Familiarity with vector databases such as OpenSearch, Pinecone, Chroma, or FAISS.
  • Proficiency with AI coding tools such as Claude Code, Cursor, or Copilot beyond autocomplete.
  • Experience building tool-using, stateful agents with an orchestration framework.
  • Understanding of Model Context Protocol (MCP) and the ability to consume or build MCP servers.
  • Strong AWS knowledge, including SageMaker, Lambda, S3, ECR, ECS, and API Gateway.
  • Familiarity with Amazon Bedrock, including model invocation, Knowledge Bases, and Agents.
  • Basic awareness of Infrastructure as Code tools such as Terraform or CloudFormation.
  • Experience with production ML deployment, experiment tracking, CI/CD, monitoring, and drift detection.
  • Advanced Python skills, including async/await, OOP, and packaging, plus strong pandas, NumPy, SQL, and Docker skills.
  • Bachelor's or Master's degree in Computer Science, Data Science, Math, or equivalent practical experience.
  • Fluent English at B2+ level.
  • AWS certifications, Kubernetes experience, GraphRAG or custom MCP server experience, and open-source contributions are preferred.

Benefits

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

Interested in this position?

Apply directly on the company website

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