Lead ML & AI Engineer
HERE Technologies View all jobs
- Mumbai, Maharashtra
- Permanent
- Full-time
- Provide technical leadership in designing, developing, and deploying ML solutions used to create high-definition, ISA and ADAS maps.
- Own and drive end-to-end ML system architecture, including data preprocessing, model training, inference pipelines, deployment, monitoring, and scaling.
- Lead innovation and develop models based on computer vision, NLP, deep-learning and machine learning
- Build systems using Agentic AI, Generative AI, and foundational ML techniques.
- Build ML systems that are scalable, reliable, reproducible, and optimized for production environments (on-cloud or in-vehicle).
- Implement MLOps practices: CI/CD for ML, model versioning, feature stores, drift detection, experimentation frameworks.
- Own one or more ML or data components within the broader mapping/routing ecosystem.
- Collaborate with platform and backend teams to integrate ML outputs into map compilation workflows.
- Work on feature requirements, model behavior, accuracy expectations, and performance characteristics.
- Conduct code reviews, architecture reviews, and share best practices in ML engineering
- Champion efficient, reusable, high-quality code; drive continuous improvement in ML development processes.
- Bachelor’s or Master’s degree in Computer Science, AI/ML, Mathematics, or a related quantitative field
- Strong development experience in Python
- Experience in machine learning engineering, applied ML, data engineering, or backend systems with ML components.
- Proven experience building end-to-end ML systems
- Strong understanding of ML algorithms, deep learning, data structures, algorithms, and software engineering principles.
- Experience with SQL/NoSQL databases
- Spark/Flink or other distributed data processing systems
- AWS (S3, EMR, Lambda, SageMaker or similar ML platforms) is a plus
- Docker/Kubernetes, CI/CD, Jenkins
- Experience with MLOps tooling and practices is a strong advantage.
- Able to translate business requirements into scalable ML system designs.
- Working with map data formats (NDS, GIS, RDF, GDF), HD lane models, or location-based datasets.
- Experience with ETL pipelines, data transformation, and large-scale data engineering.
- Deep understanding of building high-precision map or routing models.