Senior ML Engineer

About Role

As a Senior Machine Learning Engineer at Leapfrog Technology, you will be at the forefront of shaping the future of data-driven solutions. You'll contribute significantly to the development of innovative ML projects, lead and mentor a talented team, and work collaboratively across functions to turn complex business challenges into actionable insights.

• Technical Leadership: Actively contribute to the design, development, and implementation of ML projects while working collaboratively with a team of ML Engineers and Data Scientists, ensuring technical excellence and innovation.

• End-to-End Ownership: Take full ownership of the ML project lifecycle, from ideation and design to development, deployment, and maintenance.

• Technological Innovation: Explore and assess emerging technologies to enhance the performance, maintainability, and reliability of ML systems.

• Engineering Best Practices: Apply robust software engineering practices to ML, including CI/CD pipelines, automation, and quality assurance.

• Architectural Leadership: Collaborate with technology experts to make informed architectural decisions, and ensure thorough technical documentation.

• Risk Mitigation: Proactively identify and address project risks, conduct root cause analysis, and implement preventive measures.

• Cross-functional Collaboration: Engage closely with cross-functional teams, including business stakeholders, product managers, software engineers, and data engineers, to deliver impactful data-driven solutions.

• Continuous Learning: Stay at the cutting edge of data science, ML, and AI developments, and leverage emerging technologies to solve complex business problems.

• Mentorship and Growth: Coach and motivate team members, identify training needs, and foster their professional development.

• Organizational Excellence: Actively uphold and promote the company's culture, processes, and standards to ensure consistent excellence in our work.

• Education and Experience:

• A degree (Master's preferred) in Computer Science, Engineering, Artificial Intelligence, Data Science, Applied Mathematics, or related fields.

• Minimum 3+ years of hands-on experience in Machine Learning or Data Science, preferably in real industry settings, with a track record of building data products that have positively impacted customer satisfaction and revenue growth.

• Technical Skills: