Job description
Job Description
Must have Skills : Generative AI Fundamentals (Capable), Cloud architecture (Capable),
Job Description : Position: Principal Engineer AI / Data Science
The Industry and Automation Practice at Nagarro is responsible for working with a wide range of industrial clients to enable their business transformation goals. We help co-create digital solutions that assist our clients in their Industry 4.0 journey. These Industry 4.0 solutions leverage diverse technologies such as Industrial IoT, Cloud, Reality Technologies, Artificial Intelligence, Data Analytics, SAP S/4 Hana, Custom Application, 5G, and more.
We are looking for a technology leader to steer some of our key initiatives with clients:
Essential skills: Python, data science, machine learning, deep learning, natural language processing, machine learning libraries like TensorFlow, Pandas, sci-kit-learn, Keras, etc., deep learning libraries like Torch, OpenCV and OpenVINO, etc., and Natural Language Processing libraries like NLTK, Gensim, CoreNLP. Good understanding of the Generative AI on text and image with Hugging Face, LangChain, Google Generative AI Studio, Azure Open AI services, and Generative AI on AWS(Bedrock) and demonstrable experience with foundational models such as GPT3.5⁄4, LLMA, Stable Diffusion, etc.
The candidate must demonstrate the following skills and experience:
1. Demonstrated experience of working on Data Science (DS) / ML (Machine Learning) technologies using custom algorithms or data platforms.
2. Demonstrated experience working on DL (Deep Learning)/ AI (Artificial Intelligence) technologies using custom algorithms or technology platforms.
3. Working experience with SQL and NoSQL databases like MongoDB, Cassandra, Redis, etc.
4. Working experience with Python/ Spark AI and ML stack. Ability to design and implement workflows of Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), Variational Auto Encoders, Transformers, and Generative Pre-Trained Transformers.
5. Experience in creating AI and ML Models, leading to quality deliveries adhering to the best practices of MLOps. Experience working with mlflow, and Kubeflow conducting machine learning deployments in the cloud and on-premises. Experience in optimizing machine learning and deep learning models, preferably putting ML models on edge.
6. Experience in architecting Data, AI solutions on machine vision, and generative AI working collaboratively with enterprise application architects.
7. Work with business stakeholders, business consultants, and pre-sales consultants to understand and translate their needs into technical requirements.
8. The candidate should be fluent in the agile delivery model with experience in working with any of the an agile product management tool, preferably JIRA.
9. Ability to guide the team on AI and ML approaches, and technical solutions, perform code review, and define integration strategy.
10. Effective written and verbal communication skills are essential to communicate in a global team and with clients.
11. Preferable to have a working knowledge of at least 1 cloud hyperscaler out of Azure, AWS and Google Cloud.
12. It is highly desirable to have extensive knowledge and hands-on experience with at least two AI frameworks out of vision, audio, and text.
13. It would be advantageous to have experience as a technical lead while working in one or more of the following domains: manufacturing, industrial automation, heavy engineering, robotics, automotive, and consumer goods.
