AI/ML Engineer

Experience: 3-6 years
Location: Bangalore (Should be available for F2F interview)
Job Description:
A Data Scientist with expertise in Artificial Intelligence is a professional who skillfully combines data analysis and business acumen to tackle cognitive computing challenges. They are proficient in advanced analytics techniques for structured data and have a deep understanding of Natural Language Processing (NLP) and Machine Learning (ML) methods for unstructured content. They are specialized in foundation models and large language models and skilled in architecting and delivering AI solutions using cutting-edge technologies, with a strong focus on foundation models and large language models. In this role, you will be responsible for architecting and delivering AI solutions using cutting-edge technologies, with a strong focus on foundation models and large language models; along with Experience in tools like Github Copilot, Amazon Code Whisperer. This expertise enables them to create comprehensive cognitive solutions that effectively process and analyze both structured and unstructured data. The professional should also have a strong foundation in one of the following areas: NLP, Image Processing, Video Processing, Voice Processing, or Watson technologies. This skill set is valuable in solving complex business problems and leveraging the power of artificial intelligence for cognitive computing. They have strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras or Hugging Face; understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc; familiarity with cloud platforms (e.g. Kubernetes, AWS, Azure, GCP) and related services. They work with a variety of relational and NoSQL databases (SQL, Postgres, DB2, MongoDB), operating systems (Linux, Windows, iOS, Android), and modern UI frameworks (Backbone.js, AngularJS, React.js, Ember.js, Bootstrap, and JQuery). They have experience in full AI project lifecycle, from research and prototyping to deployment in production.

Work arrangement
No