ML Tech Lead, GenAI, AWS

🕒 May 25

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Provectus

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2012

🤖 Artificial Intelligence

☁️ SaaS

Artificial Intelligence • SaaS

Provectus is an artificial intelligence consultancy and solutions provider that helps businesses transform through AI. Offering both a use case and a platform approach, Provectus integrates AI into organizations to achieve unique business objectives and technical capabilities. Their solutions are cloud-native, vendor-agnostic, and open, allowing for deployment in customer's cloud without restrictive licenses. With applications in industries like retail, manufacturing, and healthcare, Provectus delivers AI-powered use cases and turnkey solutions to drive innovation and efficiency. They also offer consulting, customization, and managed AI services.

📋 Description

• Technical Leadership: Set technical direction and standards for ML projects • Technical Leadership: Make architectural decisions for ML systems • Technical Leadership: Review and approve technical designs • Technical Leadership: Identify and address technical debt • Technical Leadership: Champion best practices in ML engineering • Technical Leadership: Troubleshoot complex technical challenges • Technical Leadership: Evaluate and introduce new technologies and tools • Mentorship: Mentor junior and mid-level ML engineers (2-5 engineers) • Mentorship: Conduct technical code reviews • Mentorship: Provide guidance on technical problem-solving • Mentorship: Help engineers debug complex issues • Mentorship: Share knowledge through workshops and documentation • Mentorship: Build technical competency across the team • Hands-On Technical Work: Contribute code to critical or complex components • Hands-On Technical Work: Build proof-of-concepts for new approaches • Hands-On Technical Work: Maintain technical credibility through active coding.

🎯 Requirements

• Deep ML Expertise: Advanced knowledge across multiple ML domains • Production ML: Extensive experience building production-grade ML systems • Architecture: Ability to design scalable, maintainable ML architectures • MLOps: Strong understanding of ML infrastructure and operations • LLM Systems: Experience with modern LLM-based applications and RAG • Code Quality: Exemplary coding standards and best practices • Multiple ML Frameworks: Proficiency across TensorFlow, PyTorch, scikit-learn • Cloud Platforms: Advanced AWS experience, familiarity with others • Data Engineering: Understanding of data pipelines and infrastructure • System Design: Ability to design complex distributed systems • Performance Optimization: Experience optimizing ML models and infrastructure • Clean Code: Writes exemplary, maintainable code • Testing: Champions testing practices (unit, integration, ML-specific) • Git & Collaboration: Advanced Git workflows and collaboration patterns • CI/CD: Experience building and maintaining ML pipelines • Documentation: Creates clear, comprehensive technical documentation.

🏖️ Benefits

• Long-term B2B collaboration; • Fully remote setup; • A budget for your medical insurance; • Paid sick leave, vacation, public holidays; • Continuous learning support, including unlimited AWS certification sponsorship.