TVM Signalling & Transportation Systems - Manager/Senior Technical Manager - Artificial Intelligence/Machine Learning

About the Role :

TSTS is looking for a highly experienced and technically deep Senior Technical Manager - AI/ML to join our team in Bengaluru. This is a key Individual Contributor role (with potential for technical leadership and mentoring) where you will be instrumental in designing, developing, and deploying cutting-edge AI and Machine Learning solutions to enhance our signalling and transportation systems. You will leverage your extensive experience (12-15 years) to build robust and scalable ML capabilities, from ideation and experimentation to production deployment and maintenance. This role requires a strong foundation in mathematics, statistics, algorithms, and a deep understanding of various ML techniques and MLOps practices.

Key Responsibilities :

- Lead the design, development, and implementation of advanced machine learning systems and models to solve complex problems within the transportation and signalling domain.

- Build cutting-edge AI/ML capabilities, including leveraging techniques from large language models (LLMs) and computer vision models relevant to transportation systems (e.g., predictive maintenance, traffic flow analysis, safety monitoring).

- Develop end-to-end ML pipelines for data ingestion, processing, model training, validation, deployment, and serving at scale.

- Write clear, efficient, and maintainable code primarily in Python, ensuring high standards of code quality and performance.

- Apply strong knowledge of basic mathematics, probability, statistics, and algorithms to inform model selection, development, and analysis.

- Utilize and demonstrate expertise in various ML libraries and packages such as pandas, numpy, scikit-learn, TensorFlow, and visualization libraries like Matplotlib and Seaborn. Experience with other relevant libraries (e.g., PyTorch, Keras) is a plus.

- Leverage industry best practices, tools, and frameworks for MLOps (Model Operations) to ensure reliable, scalable, and efficient deployment and maintenance of ML models in production environments.

- Continuously evaluate and integrate new technologies and approaches to improve the team's ability to build, operate, and maintain AI/ML products.

- Collaborate with cross-functional teams, including software engineers, domain experts, and product managers, to understand requirements and deliver impactful AI/ML solutions.

- Troubleshoot and optimize existing ML models and pipelines for performance, accuracy, and efficiency.

- Document technical designs, methodologies, and results clearly and comprehensively.

- (As a senior individual contributor) Provide technical guidance and mentorship to other team members, sharing knowledge and promoting best practices.

Required Skills and Qualifications :

- Minimum of 12-15 years of experience in software development with a strong focus on Artificial Intelligence and Machine Learning.

- Deep expertise in AI and ML concepts, algorithms, and techniques, including but not limited to supervised learning, unsupervised learning, deep learning, and reinforcement learning.

- Mandatory strong proficiency in Python programming language.

- Extensive hands-on experience with cloud platforms, specifically AWS and/or Azure, for building and deploying AI/ML solutions (e.g., Sagemaker, Azure ML, cloud storage, compute services).

- Mandatory strong experience with Scikit-learn and other key Python ML libraries (pandas, numpy).

- Solid understanding of relational and NoSQL databases and experience with data manipulation and querying.

- Proven ability to design and implement end-to-end ML pipelines.

- Strong understanding of MLOps principles and practices.

- Excellent analytical and problem-solving skills.

- Ability to work independently and take ownership of complex technical challenges.

- Good communication skills to effectively collaborate with technical and non-technical stakeholders.

Preferred Skills :

- Experience with Large Language Models (LLMs) or Computer Vision models and frameworks (e.g., OpenCV, PyTorch, Hugging Face).

- Experience in the transportation, railway, or related industrial domains.

- Familiarity with big data technologies (e.g., Spark, Hadoop).

- Experience with containerization (Docker) and orchestration (Kubernetes).

- Knowledge of software engineering best practices, including version control (Git), testing, and CI/CD.

- Publications or contributions to the AI/ML community.

Education :

- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, Statistics, or a related quantitative field. A Ph.D. is a plus.