P
AI Summary
Lead a team of ML engineers, shape standards and best practices, and act as a bridge between leadership, HR, and engineering teams. Manage multiple AI-driven projects and ensure delivery excellence. Mentor engineers and drive career growth.
Key Highlights
Build, lead, and mentor high-performing ML teams
Recruit, onboard, and coach new team members
Evaluate and improve delivery processes
Collaborate with other managers and senior stakeholders
Represent the company at conferences and community events
Technical Skills Required
Benefits & Perks
Attractive annual bonus
Long-term B2B collaboration
Fully remote setup
Comprehensive private medical insurance
Paid sick leave, vacation, and public holidays
Continuous learning support
Job Description
About The Role
We are looking for a Machine Learning Practice Leader — a senior technical and people leader who will guide the direction of our ML practice, mentor engineers, and ensure delivery excellence across multiple AI-driven projects.
This role combines hands-on machine learning expertise with strategic leadership. As a Practice Leader, you’ll manage and grow a team of ML engineers, shape standards and best practices, and act as the bridge between leadership, HR, and engineering teams.
Key Responsibilities
- Build, lead, and mentor high-performing ML teams
- Recruit, onboard, and coach new team members
- Set objectives, conduct performance reviews, and drive career growth
- Evaluate and improve delivery processes, ensuring consistency across projects
- Collaborate with other managers and senior stakeholders across the company
- Identify skill gaps, arrange training, and foster a culture of continuous learning
- Ensure alignment with the company’s mission, vision, and values
- Represent the company at conferences, meetups, and community events
- Deep understanding of Python best practices and ML design patterns
- Proven experience across the full ML lifecycle: data preparation, model training, validation, deployment, and monitoring
- Experience with deep learning model development and transformer architectures
- Strong background in one or more domains: NLP, Computer Vision, Forecasting, Recommender Systems
- Expertise in agentic workflows, RAG, and GraphRAG architectures
- Practical experience with AWS or other cloud/open-source MLOps platforms
- Hands-on experience with model post-production: monitoring, retraining automation, and maintenance
- Familiarity with diverse data sources (OLTP, OLAP, DataLake, Streaming)
- Experience in DataOps or MLOps is a strong advantage
- Proven experience managing teams or departments in a technical environment
- Ability to coach, mentor, and define clear growth paths for engineers
- Strong communication and diplomatic skills — empathy, ethics, and conflict resolution
- Calm, structured, and reliable leadership style in high-pressure environments
- Confidence to explain complex ML decisions and roadmaps to non-technical stakeholders
- Attractive annual bonus based on performance
- Long-term B2B collaboration
- Fully remote setup
- Comprehensive private medical insurance or budget for your medical needs
- Paid sick leave, vacation, and public holidays
- Continuous learning support, including unlimited AWS certification sponsorship
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