Director – Machine Learning Engineering – Bengaluru (On-site) – SaaS Product Company

ThoughtWin - A CMMI Level 3 Company; Bengaluru; On-site; INR 15,000,000 - 18,000,000; Full time

Job summary

ThoughtWin - A CMMI Level 3 Company in Bengaluru on-site is seeking a Director of Machine Learning Engineering. You will lead a high-performing ML team, guide product development from concept to deployment, and design scalable ML architectures for production AI solutions. Collaboration with product, design, data science, and business teams is essential. Preference for candidate backgrounds in SaaS and enterprise products.

Qualifications

• Advanced degree in a data/ML related field.
• Strong foundation in probability, statistics, and problem solving.
• Hands-on expertise with ML, MLOps, and model deployment.
• Experience building scalable SaaS platforms and production systems.
• Knowledge of microservices and data pipelines.

Responsibilities

• Lead and scale a high-performing ML Engineering team.
• Guide product development from concept to deployment.
• Design scalable ML architectures and drive AI solutions.
• Collaborate with Product, Design, Data Science, and Business teams.
• Own MLOps pipelines and production readiness of models.

Skills

Data science

Statistics

ML engineering

MLOps

Distributed systems

Backend architectures

Education

Bachelor's/Masters/PhD in Data Science/Math/OR/Applied Math/Computational Science

Tools

Java/Python

TensorFlow/PyTorch

Apache Spark

Kafka

Cloud platforms (AWS/GCP/Azure)

Job description

Director Machine Learning Engineering

Bengaluru (On-site) | SaaS Product Company | Budget: Upto 1.8 Cr + ESOPs

Experience: 1418 years

Team Size to Manage: 10-15 Engineers (ICs and Leads)

Required Skills & Experience

• Bachelor's, Masters, or Ph.D. in Data Science, Mathematics, Operations Research, Applied Mathematics, Computational Science, or a related field.
• Strong foundation in probability, statistics, and scientific problem-solving.
• Strong expertise in Machine Learning, MLOps, and Model Deployment.
• Deep hands‑on experience with Java/Python, TensorFlow/PyTorch, Apache Spark, Kafka, and Cloud Platforms (AWS/GCP/Azure).
• Experience managing large‑scale SaaS platforms, production systems and distributed computing environments with a focus on scalability and performance.
• Strong backend architecture knowledge: Microservices, Data Pipelines, Rest APIs.
• Experience managing customer‑facing AI products.

Role and Responsibilities

• Lead and scale a high‑performing ML Engineering team.
• Guide product development from concept to deployment.
• Design scalable ML architectures and drive delivery of AI solutions.
• Collaborate with cross‑functional teams: Product, Design, Data Science, and Business.
• Act as the technical leader and key decision‑maker for AI/ML products.
• Own MLOps pipeline and production readiness of ML models.

Preference will be given to candidates from product‑based companies due to the nature of the role.

Preferred Background: Experience in SaaS, Enterprise Products, Consumer Internet, or high‑growth startups is a strong plus.

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