RGM - Data Scientist

RGM - Data Scientist

SKILLS – MUST HAVE: • Design, build, and deploy Hyperscalers-based (Azure, AWS, GCP or Databricks) ML models, including large-scale data processing, computationally intensive statistical modeling, and advanced analytics – Expert • Implementation of Generative AI models for business solutions and experience on Azure Open AI, AWS Bedrock or Vertex AI or open-source models – Expert • Python programming with robust code – Expert • Developing a framework or generic pipeline to retrieve, optimize, and deploy Open-Source Models – Expert • Explore and design a reference architecture for developing virtual assistants using foundation models – Expert • Familiarity with deep learning, machine learning and frameworks (like Keras, TensorFlow or PyTorch etc.), HuggingFace Transformers and libraries (like scikit-learn, spacy, gensim, CoreNLP etc.) – Working knowledge • Understanding of LLMs and Gen AI especially as applied to text and image analysis and training – Working knowledge • Experienced in fine-tuning of LLM models, implementation of AI Guardrails and Responsible AI Framework (explainability, bias detection, hallucination control) – Working knowledge • Experienced in implementing LangChain Frameworks – Working knowledge • Linux, HTTP/ REST – Working knowledge • Cloud Technologies – At least one of GCP, AWS, Azure • JIRA, Conflence – Working knowledge SKILLS – GOOD TO HAVE: • Linux shell-scripting • Multilingual NLP SOFT SKILLS: • Good communication • Ability to work in a team as well as independently deliver modules • Team player LEADERSHIP SKILLS: • People Leadership: Able to lead and mentor a team of ~10-15 people • Thought Leadership: Having papers published in renowned journals, presentations in conferences, patent-filing preferred RESPONSIBILITIES: • Invent, research, envision, design, solution and deliver AI/ ML applications at scale delivering measurable value • Build end-to-end AI/ ML solutions: Develop, refine, implement, customize and deploy state-of-the-art Machine Learning algorithms and systems, and AI models • Designing, developing, and researching Machine Learning systems, models, and schemas through data science and data analytics prototypes. • Continuous learning – Certifications. • Incubation mindset – Research oriented, ability to deliver quick POC’s, and come up with ideas. • Communication and Documentation – Ability to share knowledge, conduct presentations and sessions, talk to clients and stakeholders, write good-quality technical documentation. • Problem Solving – Technical depth in solving real-world problems with appreciation of business imperatives.