Director, Machine Learning

5 days ago

Bengaluru, Karnataka, India Talent Nexa Consulting Full time

Role: Director – Machine Learning

Location: Bangalore / Chennai / Hyderabad (Work from Office – Flexible Hybrid Model)

Experience: 15–18 Years

Compensation: Best in class (based on experience) + ESOPs

Role & Responsibilities
  • Drive the end-to-end architecture and implementation of large-scale Machine Learning systems across business-critical platforms.
  • Lead strategic ML initiatives including real-time personalization, intelligent automation, predictive analytics, and recommendation engines.
  • Collaborate with engineering, data science, and product teams to deliver AI-first capabilities that scale.
  • Own the design and scalability of ML infrastructure using Python and Java architecture principles.
  • Build and maintain production-grade ML pipelines using best practices in MLOps, distributed computing, and cloud-native development.
  • Define long-term technical roadmaps, mentor senior engineers, and guide architectural decisions.
  • Ensure high performance, robustness, and maintainability of ML systems across environments.


Preferred Candidate Profile

  • 15–18 years of experience in software engineering, with deep expertise in Java and Python architecture.
  • 6+ years of experience in Machine Learning systems – from prototyping to production at scale.
  • Strong track record of building high-performance, low-latency ML platforms in product-based or SaaS environments.
  • Proficient in designing and scaling ML microservices and distributed data processing systems.
  • Solid understanding of cloud platforms (AWS, GCP, Azure) and modern MLOps tools.
  • Proven leadership ability with strong team management and stakeholder collaboration skills.
  • Bachelor's/Master's degree in Computer Science, Engineering, or related discipline (Tier-1 institutions preferred).


Perks and Benefits

  • Build AI-first products at scale with real-world business impact.
  • Competitive compensation with equity in a fast-scaling tech environment.
  • High ownership, flat hierarchy, and tech-driven culture.
  • Collaborate with top talent and thought leaders in ML and engineering.
  • Exposure to solving high-impact, large-scale problems with cutting-edge technology.

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