ML Engineer

Strategy

• Lead the AI/ML Delivery team with active involvement in all phases of machine learning project development as a core developer.
• Develop strategic approaches for integrating AI/ML solutions aligned with business objectives to drive impactful results.

Business Execution

• Engage closely with business stakeholders to thoroughly understand requirements and translate them into effective machine learning solutions.
• Ensure that project milestones are met within the agreed timelines, managing expectations and deliverables efficiently.

Process Management

• Oversee the complete lifecycle of AI/ML use cases from concept through design, validation, deployment, and ongoing improvements.
• Maintain compliance with Responsible AI (RAI) practices, governance policies, and security protocols throughout development cycles.
• Lead model validation efforts and implement enhancements to optimize performance and reliability.
• Manage stakeholder communications to keep all parties informed and engaged.

People and Talent Development

• Assign projects and manage deadlines within the team, ensuring balanced workloads and timely delivery.
• Build and nurture a team specialising in reviewing models applied to both unstructured and structured data sources.
• Participate in talent acquisition efforts and foster professional growth through coaching and skill development initiatives.

Risk Management

• Assume full ownership of project delivery, proactively identifying and escalating risks to relevant stakeholders.
• Design and implement effective mitigation plans following a clear risk roadmap to address potential challenges.

Full-time, office-based position located in Bangalore, India, offering an engaging and collaborative work environment.