Manager, Engineering, Data Science and Machine Learning

Overview

Lead a multidisciplinary team of engineers and data scientists building AI and ML solutions and robust data collection pipelines that process and categorize large volumes of unstructured data.

What you'll do

• Drive the execution of AI and ML initiatives related to data collection, aligned with overall business goals and strategies.
• Provide hands-on technical leadership in the engineering of ML models and services focused on unstructured data, NLP and classifiers.
• Lead, mentor and develop a high-performing team, fostering innovation and continuous improvement.
• Contribute to NLP techniques, including classifiers, transformers and LLMs, to process and categorize unstructured data.
• Design, develop and maintain advanced data collection pipelines using orchestration, messaging, database and data platform technologies.
• Collaborate with other AI/ML teams, data collection engineering teams and product management to support broader AI/ML goals.
• Explore and implement new technologies and methodologies to improve the efficiency and accuracy of data collection and processing systems.
• Ensure data collection systems meet high standards of integrity, security and compliance, including data governance and model transparency.
• Play an active role in recruiting, training and retaining engineering talent.
• Apply Agile, Lean and Fast-Flow principles to improve team efficiency and delivery.

What you'll need

• Bachelor's, Master's or PhD in Computer Science, Mathematics, Data Science or a related field.
• 8+ years of experience in software engineering, with a focus on AI and ML technologies, particularly data collection and unstructured data processing.
• 3+ years of experience in a leadership role managing individual contributors.
• Strong expertise in NLP and machine learning, with hands-on experience in classifiers, large language models (LLMs) and other NLP techniques.
• Extensive experience with data pipeline and messaging technologies such as Apache Kafka, Airflow and cloud data platforms (e.g., Snowflake).
• Expert-level proficiency in Java, Python, SQL and other relevant programming languages and tools.
• Strong understanding of cloud-native technologies and containerization (e.g., Kubernetes, Docker), with experience managing these systems globally.
• Demonstrated ability to solve complex technical challenges and deliver scalable solutions.
• Excellent communication skills with a collaborative approach to working with global teams and stakeholders.
• Experience working in fast-paced environments, particularly in data-intensive industries.

Nice to have

• Experience in fintech.

Details

• Location: Mumbai.
• Work mode: hybrid, with four days in-office each week in most locations.
• Working conditions: standard office setting; limited corporate travel to remote offices or business meetings and events may be required.