We're looking for a Machine Learning Team Lead to own real parts of it.
What you'll actually do?
Lead, mentor, and grow a multidisciplinary team composed of Data Scientists, Data Analysts, and DLP Analysts.
Define and lead the team's technical vision and execution strategy, driving technical excellence and ensuring alignment with business priorities and product objectives.
Oversee the design, development, validation, and deployment of advanced machine learning solutions for customer-facing products.
Hands-on ownership of current AI services.
Establish and enforce best practices for model development, experimentation, evaluation, documentation, and code quality.
Collaborate closely with Product Managers, Data Engineers, Software Engineers, and domain experts to translate business challenges into scalable ML solutions.
Drive execution and delivery, balancing innovation, technical quality, and time-to-market considerations.
Promote operational excellence by improving the reliability, scalability, and maintainability of production machine learning systems.
Establish scalable engineering processes, workflows, and best practices.
Lead the team transformation from an early-stage organisation into a mature, production-grade AI engineering team.
Requirements: 3+ years of experience in Machine Learning, Data Science, or related fields, with a proven track record of deploying machine learning models into production environments.
2+ years of experience leading, mentoring, or managing technical teams.
Hands-on experience designing and operationalizing end-to-end machine learning solutions.
Product-oriented mindset with proven experience delivering ML PoCs and MVPs from ideation to production.
Ability to balance strategic leadership with hands-on technical involvement when needed.
Hands-on experience working in a cloud environment.
Experience working closely with cross-functional stakeholders, including Product Managers and Engineering teams.
Excellent communication, prioritization, and decision-making skills.
Advantages:
MLOps experience, including CI/CD practices for machine learning and model monitoring.
Experience with AWS AI / ML stack - Bedrock, SageMaker.
Experience working with non-tabular data.
Previous work as an early-stage start-up/founding engineer.
This position is open to all candidates.