Data Science Engineer
Wabtec View all jobs
- Bangalore, Karnataka
- Permanent
- Full-time
- Own the implementation and deployment of the embedded vision software platform for Wabtec Bus Solutions' products, including applications in enhanced sensing for bus and charging pantograph applications.
- Work closely with the DAT ML engineers to build and deploy highly scalable AI solutions in line with processes and standards set by the DAT team.
- Investigate and identify opportunities for the use of AI to create new solutions or enhance existing products in the transit bus industry.
- Expected to stay in tune with latest trends in artificial intelligence and digital technologies.
- Become a subject matter expert on the application of AI in the transit bus space.
- Participate in designing and executing data science pipelines including edge device management, data collection, exploratory data analysis, ground truth annotation, building machine/deep learning models and their deployment.
- Devise and utilize algorithms and models to mine big-data stores; perform data and error analysis to improve models; clean and validate data for uniformity and accuracy.
- Participate in discussions and host information sharing sessions on latest trends in artificial intelligence and digital technologies as needed.
- Bachelor's in engineering, Physics, Mathematics, Robotics or Computer Science from an accredited university or college, or relevant and significant industry experience.
- Minimum 2 years of hands-on experience in the fields of Artificial Intelligence/Machine Learning and video analytic edge computing.
- Proficient in machine learning languages: python, GO, or similar languages for the development of AI models.
- Proficient in embedded programming in C/C++.
- Hands on experience with real time OS including Linux based systems, and low-level system and device configuration.
- Proficient with standard computer vision tools such as Open CV, Deep Learning Frameworks (Keras, TensorFlow, PyTorch).
- Proficient in software design principles.
- Working knowledge with Docker and Kubernetes.
- Working knowledge in Cloud, Cloud Native applications, and application platforms.
- Working knowledge of inter-process communication strategies and protocols for real time systems (shared memory or pub-sub strategies).
- Master's degree in engineering, Physics, Mathematics, Robotics or Computer Science from an accredited university or college, or relevant and significant industry experience
- Experience with developing embedded software solutions for real time systems in the transportation or industrial applications.
- Experience with developing deep learning models for computer vision applications such as object detection and segmentation.
- Experience in AWS SageMaker, and other MLOPs tools and practises.
- Experience with embedded edge devices such as NVIDIA Jetson boards.
- Ability to work in a fast-paced environment with tight customer-focused product delivery schedules.
- Strong interpersonal, leadership, communication, and presentation skills.
- A critical thinker that can quickly understand a new problem space and apply analytic techniques to identify potential value.
- Self-starter with the ability to work to set schedule and goals with minimum supervision.
- Ability to engage and build positive relationships with both customers and internal and external employees.
- Ability to work in a cross-functional, global environment.
- Effective team building and problem-solving abilities.