Mid-Level ML Engineer

This is a fully remote position, open to applicants in Colombia.

📋 Description

• Design and execute machine learning pipelines from experimentation through to production with minimal oversight.

• Construct, assess, and enhance models for supervised, unsupervised, and generative AI applications.

• Create and sustain production-quality Python code: ensuring it is modular, well-tested, and thoroughly documented.

• Establish reproducible experimentation setups and manage experiment pipelines effectively.

• Deploy and oversee ML models in production, ensuring they maintain stability and performance.

• Actively engage in LLM-based applications, such as RAG systems and agent workflows.

• Utilize AI-assisted development tools to enhance productivity and the quality of code across all tasks.

• Claude Ecosystem Integration: effectively apply Claude Code or the Claude Agent SDK to provide exceptional greenfield customer interactions.

• Convert existing brownfield projects into AI-friendly configurations.

• Actively use the Provectus AI toolkit in daily operations.

• Internal Contributions: enhance the Provectus AI toolkit by developing specific agents, creating MCP servers, submitting bug fixes, adding features, or improving documentation.

• Mentor and assist junior ML engineers with technical tasks, code quality, and best practices.

• Perform thorough code reviews, providing constructive and actionable feedback.

• Collaborate with cross-functional teams, including DevOps, Data Engineering, and Solutions Architects.

• Stay updated with ML research and emerging frameworks, particularly within GenAI and agentic AI.

⛳️ Requirements

• Proven ability equivalent to 1-3 years of practical ML engineering experience.

• History of deploying at least one ML model in a production or production-like setting.

• Experience participating in team-based or client-facing projects (not exclusively academic or solo).

• Demonstrated expertise with AI-assisted development tools and agentic frameworks.

• Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, Engineering, or a related discipline.

• Equivalent self-taught knowledge with a verifiable history of production or near-production projects.

• Completion of a bootcamp or certification program with substantial practical ML engineering experience.

• Experience in consulting or client-facing roles.

• Prior experience working within distributed or remote international teams.

• Contributions to technical blogs, conference presentations, or open-source projects.

• Published research on agentic systems or AI tooling.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Flexible working hours and remote work options.

• Opportunities for professional development and continuous learning.

• Collaborative and inclusive work environment.

• Access to cutting-edge tools and technologies.

• Health, dental, and retirement benefits.