Manager, ML Engineering

2 weeks ago

Bengaluru, Karnataka, India Amoli Talents Full time ₹ 15,00,000 - ₹ 25,00,000 per year

Key Responsibilities

  • Drive Strategy & Vision: Partner with senior leadership, product management, and other stakeholders to define and execute the machine learning roadmap aligned with business goals.
  • Team Leadership: Lead, mentor, and grow a team of ML scientists and engineers. Create an environment that encourages innovation, high performance, and career development.
  • Technical Oversight: Guide and review the development of machine learning models and data pipelines, ensuring scalability, scientific validity, and production readiness.
  • Cross-Functional Collaboration: Collaborate with Product and Analytics teams to scope projects, prioritize initiatives, and ensure seamless data and model integration.
  • Operational Excellence: Define project goals, success metrics, and delivery timelines. Ensure effective resource allocation and continuous improvement in team processes.
  • Foster Scientific Rigor: Uphold high standards of experimentation, measurement, and peer review. Promote the use of reproducible research and robust evaluation practices.
  • Data Strategy: Partner with the operations and data teams to ensure access to high-quality labeled data, and proactively shape data acquisition strategies where needed.
  • Talent Development: Provide coaching and technical guidance to team members. Conduct performance reviews, identify skill gaps, and invest in team capability building.
  • Hiring: Attract, interview, and hire top talent to grow the team and enhance its diversity of thought and background.

Minimum Qualifications

  • Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field with 6+ years of relevant industry experience, including 3+ years in people management.
  • Proven experience leading machine learning teams in an applied industrial setting.
  • Deep understanding of modern ML approaches including classification, regression, NLP, clustering, deep learning, and/or reinforcement learning.
  • Strong programming background in Python, Java, or similar, with exposure to production-grade ML systems.
  • Proficiency with big data processing frameworks such as Hadoop, Spark, and SQL.
  • Excellent communication, storytelling, and stakeholder management skills.
  • Demonstrated ability to translate business needs into scientific problems and to prioritize for impact.

Additional Qualifications

  • Master's or Ph.D. in a relevant field (Computer Science, ML, Stats, etc.)
  • Track record of impactful publications and/or patents in machine learning or related areas.
  • Contributions to open-source ML tools or frameworks.
  • Experience with modern large language models, graph-based ML, or knowledge graph construction.

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