Responsibilities

• Technical Delivery (60%)
• Design and implement end-to-end ML solutions from experimentation to production;
• Build scalable ML pipelines and infrastructure;
• Optimize model performance, efficiency, and reliability;
• Write clean, maintainable, production-quality code;
• Conduct rigorous experimentation and model evaluation;
• Troubleshoot and resolve complex technical challenges
• Collaboration and Contribution (25%);
• Mentor junior and mid-level ML engineers;
• Conduct code reviews and provide constructive feedback;
• Share knowledge through documentation, presentations, and workshops;
• Collaborate with cross-functional teams (DevOps, Data Engineering, SAs);
• Contribute to internal ML practice development
• Innovation and Growth (15%)
• Stay current with ML research and emerging technologies;
• Propose improvements to existing solutions and...