Robert Bosch Engineering and Business Solutions Private Limited (RBEI), is a 100% owned subsidiary of Robert Bosch GmbH, one of the world’s leading global supplier of technology and services, offering end to end engineering, IT and Business solutions.
With over 25000 associates, RBEI is the largest software development center of Bosch outside Germany, indicating we are the Technology Powerhouse of Bosch in India. We have a global footprint with presence in US, Europe and the Asia Pacific region. RBEI is ISO 9001:2008 certified (2012), appraised at CMMI-L5 as per version 1.3 (2011), ASPICE - level3 based on version 2.5 and ISO 15504- 5 and 7, and also ISO 27001 with seven state-of-the-art facilities spread across Bangalore and Coimbatore in India, Ho Chi Minh City in Vietnam and Guadalajara in Mexico, ISO/IEC 20000-1:2011 certified (2014).
We nurture, build and sustain enduring customer relationships to enable direct operational and strategic benefits to our customers. We make it happen through qualified, motivated and flexible professional associates, who uphold the heritage and values of Bosch - time-tested over 125 years of a successful journey; a journey marked by quality, reliability and innovation of service to enhance the interest of our customers and the community we live in.
We provide solutions for businesses in primarily three areas:
- Engineering Services
- IT services
- Business services
Our focal industries:
- Automotive industry
- Industrial Technology
- Consumer Goods and Building Technology.
“We see RBEI as helping us to achieve the technological lead we need to have in order to prevail in increasingly competitive world markets….. RBEI is about ensuring product excellence under conditions that allow us to maintain our global competitiveness” – Mr. Franz Fehrenbach, Chairman of the Board of Management, Robert Bosch GmbH.
2+ years of work experience in deploying and maintaining software product in production environments
- 3+ years of work experience with Machine Learning techniques (e.g., deep learning, SVM, clustering, prediction, time series analysis) and their applications to solve challenging problems in a product development environment ; Software development experience/full stack developer
- Technology Experience: o Experience with Docker and Kubernetes; Experience with cloud technologies on Azure; Experience with Python AI/ML analysis libraries (TF, Keras, Pytorch, pandas, sklearn, numpy, scipy, and matplotlib), and Spark MLlib
- Application Development: o Experience in developing and operating machine learning (ML) applications in production environments using state of the art technologies (e.g., Kubeflow, MLflow)
o Hands-on industry work experience designing and building large-scale data, machine learning, and analytics applications and pipelines that are well-designed, cleanly coded, well-documented, operationally stable, and timely delivered
Must have skills:
- Responsible for building containerized applications for innovative ML product using modern technologies in the area of AI and Security
- Build and deploy SaaS Product on cloud (e.g., AWS, Azure) working with technology stack comprising of Docker, Kubernetes, ML Flow, Kubeflow, Rabbit MQ, Mongo DB, Azure Storage Account, ADL Gen 2, Spark, Elasticsearch, Logstash, Kibana, MEAN stack
- Solid software engineering skills, with proficiency in Python and experience in providing them as services
- Transform research and concept into production-grade codes
- Extending company’s data with third party sources of information when needed
- Processing, cleansing, and verifying the integrity of data used for analysis
- Implement tests to validate and verify your implementation
- Ship well-tested, secure, reliable, and maintainable code within committed timelines that delights product user
- Move developed codebases and models to production for serving at scale and passionately own product lifecycle
- Architect and deploy robust data infrastructure to support Product development with MLOps
- Support tooling for data persistence, transformation, exploration, and visualization (e.g., Spark, Hive, Django, Dash, Streamlight)
- Creating automated anomaly detection systems and constant tracking of its performance
- Working with machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
- Working with AI techniques and algorithms, such as CNN, RNN, etc.
- Working with Python AI/ML analysis libraries (TF, Keras, Pytorch, pandas, sklearn, numpy, scipy, and matplotlib), and Spark MLlib )
- Building microservices-based API with containerization technologies
- Experience in developing and operating machine learning (ML) applications in production environments using state of the art technologies (e.g., Kubeflow, MLflow)
- Proficiency with Python, AI, and machine learning frameworks
- Proficiency with web APIs development and design (e.g., REST)
- Proficiency with database technologies (e.g., SQL Server, MongoDB)
- Familiar with agile development processes
- Ability to work with teams and individually in a highly dynamic and exciting environment.
- Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
- Excellent understanding of AI techniques and algorithms, such as CNN, RNN, etc.
- Understanding of Microservices architecture and its design patterns,12 factor App
- CI/CD or ModelOps
BE / BTech / MS/MTech in Computer Science, Computer Engineering, Software Engineering, Computational Science, Machine Learning, Data Science
- Contribute technical expertise to the team with the development of APIs and machine learning services
- Assist in the evaluation, requirements gathering, time estimation, and planning of software projects using agile methods
- Propose architectural design and technology decision
- Follows standards and industry best practices concerning the design, implementation, and especially maintenance of software applications
- Support fellow engineers through peer code reviews and constructive discussions that concern architecture, data model, and feature implementation decision
- Provide and receive meaningful feedback from the group to ensure the extensibility and reusability of the code
- Great communication skills
- Good ability to anticipate issues and formulate remedial actions.
- Good interpersonal and team working skills.