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Senior ML Engineer

Leapfrog Technology · Kathmandu, Bagmati, Nepal

What Leapfrog Technology asks for

  • 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.
  • 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.
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Employer
Leapfrog Technology
Location
Kathmandu, Bagmati, Nepal
Type
Fulltime Permanent
Posted
today

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.

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