Deputy Manager - Technical Lead Data Science, Nissan ISIT
Job Description
Company
RNTBCI PL
Job Description
Tech Lead leads the planning, execution, and delivery of AI/ML programs across the organization. This role requires a strong blend of technical expertise (ML, DL, Generative AI, Computer Vision/OpenCV) and program management capabilities to drive scalable, high‑impact AI initiatives.The individual will work closely with data scientists, ML engineers, software teams, and business units to transform AI strategies into production-grade solutions
Program Management- Lead multiple AI/ML projects from concept to deployment by defining scope, timelines, deliverables, and KPIs.
- Develop AI roadmaps aligned with business goals and strategic outcomes.
- Ensure smooth cross-functional collaboration between data science, engineering, product, IT, and business teams.
- Drive Agile/Scrum ceremonies for AI teams-backlog grooming, sprint planning, retrospectives.
- Manage risks, dependencies, and resource allocation across AI portfolios.
- Lead the design and implementation of GenAI-powered applications like chatbots, copilots, document intelligence, synthetic data, and automation.
- Drive enterprise adoption of LLMs and multimodal AI systems.
- Manage experimentation, PoCs, and pilot deployments of GenAI solutions.
- Provide technical guidance on ML/DL model selection, evaluation, data requirements, and deployment strategy.
- Review architectures involving CNNs, RNNs, Transformers, autoencoders, and custom vision models.
- Oversee computer vision initiatives using OpenCV:
- Image classification, object detection, segmentation
- OCR and document analysis
- Support the team in optimizing models for performance, compute efficiency, and scalability.
- Strong understanding of Machine Learning, Deep Learning, NLP, Generative AI, and Computer Vision.
- Hands-on familiarity with:
- Python, TensorFlow, PyTorch
- OpenCV, YOLO, Vision Transformers
- LLMs, prompt engineering, vector databases (FAISS, Pinecone)
- MLOps tools (MLflow, Kubeflow, ML, AWS Sagemaker)
- Data engineering concepts (ETL, pipelines, APIs)
- Experience with Agile/Scrum methodologies.
- Strong documentation and communication capabilities.
- Ability to balance technical depth with strategic business understanding.
- Experience managing large-scale, cross-functional projects.
Job Family
Information Technologies & Systems
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