Roles and Responsibilities
- Lead the end-to-end architecture and development of machine learning solutions for Cyients Customers across Comms, Transportation and Portfolio of sectors.
- Implement machine learning algorithms into services and pipelines to be consumed at web-scale.
- Implement test cases to automate testing of frontend and backend code.
- Responsible for understanding and implementing Deep Learning models for AI solutions, meeting development schedules and ensuring the delivered solution meets the technical specifications.
- Solid theoretical background in image processing, computer vision and machine learning
- Design, develop, and deliver AI/machine learning enabled solutions for specific industry problems.
- Build scalable, available, and supportable processes to collect, manipulate, present, and analyze large datasets in a production environment
- Articulate problem definition and work on all aspects of data including acquisition, exploration/visualization, feature engineering, and experimentation with machine learning algorithms, deploying models.
- Develop working prototypes of algorithms and evaluate and compare metrics based on the real-world data sets
- Provide design input specifications, requirements, and guidance to software engineers for algorithm implementation
- Use large data sets to find anomalies and using models to test the effectiveness of different courses of action.
- Strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations
- Work closely with Automation and Innovation Head in updating projects status to stakeholders as well as ensure Automation Governance compliance using appropriate tracking tool
Skills Required
- Ability to think critically, question assumptions and devise solutions to challenging technical problems.
- Self-motivated, persevering and capable of working with minimal supervision.
- Solid team work and communication skills.
- Hands-on experience with one or more of the following technologies
o Back end web-services: Python, Java, Spring Boot, Flask, Django, Kubernetes, Docker
o Machine Learning: TensorFlow, Keras, Deep learning algorithms,
o ML Technologies: NLP, Computer Vision, Model Management, Google Tesseract OCR
o Big Data technologies: Kafka, Apache Spark, Hadoop
- Solid Experience architecting and developing AI and machine learning applications
- Experience in Computer vision, Deep learning for object detection
- In-depth understanding of image processing algorithms, pattern recognition methods, and rule-based classifiers
- 10 years of working experience; experience in leading a 10+ members team with agile framework
- 15 - 18 Years of relevant professional experience is required
- Degree in applied math, statistics, machine learning or computer science. PhD/ MS is preferred
- Deep understanding of statistics and experience with machine learning algorithms/techniques.
- Proven programming skills, in particular C++ and Python, strong experience with DL frameworks such as TensorFlow, Theano and others
- Scientific expertise and real-world experience in deep learning (convolutional neural networks, restricted Boltzmann machines, and deep neural networks)
- Passion for solving challenging analytical problems
- Ability to quickly qualitatively and quantitatively assess a problem
- Ability to work productively with team members, identify and resolve tough issues in a collaborative manner.
- Experience in applying machine learning techniques to real-world problems in a production
Education Requirements
- B.Sc., B. Tech, MTech or MS in Computer Science or related field.
- Certifications in ML, Deep Learning
