Senior Staff AI Scientist

I00M05 Wipro GE Healthcare Private Limited; Bengaluru; On-site; INR 3,000,000 - 5,000,000; Full time

Job summary

I00M05 Wipro GE Healthcare Private Limited in Bengaluru is looking for a Sr Staff AI Scientist to lead advanced research in AI technologies. The ideal candidate will possess extensive expertise in machine learning, deep learning, and responsible AI practices, ideally holding a PhD in a related field.

Key responsibilities involve designing AI algorithms and deploying LLM applications while collaborating across teams to drive innovation in AI solutions. The role is for highly analytical professionals ready to make a significant impact in the field.

Qualifications

• PhD or master's in computer science, artificial intelligence, machine learning, NLP, or data science.
• Strong research background with contributions in AI/ML.
• Demonstrated deep knowledge of generative AI and large language models.

Responsibilities

• Conduct advanced research in artificial intelligence.
• Design and validate novel AI algorithms and workflows.
• Build and deploy LLM-powered applications.
• Collaborate with product and engineering teams to define AI strategy.

Skills

Machine Learning

Deep Learning

NLP

Generative AI

AWS Bedrock

AWS SageMaker

Python

AI Ethics

Education

PhD or Masters in Computer Science or related field

Tools

PyTorch

TensorFlow

Keras

SQL

NoSQL

Job description

Job Description Summary

We are looking for an exceptional Sr Staff AI Scientist with a strong research background and deep expertise in Machine Learning, Deep Learning, GANs, NLP, Generative AI, LLMs, and Agentic AI. This role is ideal for a highly analytical and innovation‑driven professional who can lead advanced AI research, design production‑grade intelligent systems, and translate emerging AI capabilities into real business impact. The ideal candidate will hold a PhD or Masters in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Computational Linguistics, Applied Mathematics, Statistics, or a related field, with proven experience in both scientific research and practical AI solution development. The candidate should also have hands‑on expertise with AWS Bedrock, AWS SageMaker, and Responsible AI practices, including fairness, explainability, governance, privacy, and bias mitigation. This role requires a rare blend of scientific depth, engineering strength, business understanding, and the ability to work across highly ambiguous and fast‑evolving AI problem spaces.

Key Responsibilities

• Conduct advanced research in artificial intelligence, focusing on machine learning, deep learning, generative AI, large language models, natural language processing, GANs, multimodal AI, and agentic AI systems.
• Design, prototype, and validate novel AI algorithms, architectures, and workflows for real‑world use cases.
• Explore and apply cutting‑edge approaches such as transformers, fine‑tuning, retrieval‑augmented generation, prompt optimization, autonomous agents, multi‑agent systems, model alignment, and reasoning frameworks.
• Lead experimentation across model training, evaluation, benchmarking, and optimization.
• Stay current with emerging AI advances and translate academic research and industry innovation into scalable enterprise solutions.
• Publish research findings, contribute to patents, or create internal technical thought leadership that advances the organization’s AI maturity.
• Build, fine‑tune, and optimize ML/DL models, including supervised, unsupervised, reinforcement, and self‑supervised learning systems.
• Develop and deploy LLM‑powered applications such as conversational AI, summarization systems, semantic search, knowledge assistants, and intelligent automation platforms.
• Create generative AI applications using foundation models for text, image, code, synthetic data, and multimodal outputs.
• Design and implement GAN‑based solutions for synthetic data generation, image synthesis, anomaly simulation, data augmentation, and domain‑specific generative use cases.
• Develop agentic AI systems capable of task planning, tool usage, workflow orchestration, memory integration, retrieval, and decision support.
• Utilise AWS Bedrock to build and scale foundation model applications, including model access, orchestration, secure integration, and GenAI experimentation.
• Use AWS SageMaker for model training, tuning, experimentation, MLOps, deployment, and monitoring at scale.
• Work with structured and unstructured data across large‑scale datasets to support AI research and production systems, leading data cleaning, feature engineering, and dataset curation.
• Build robust AI pipelines that integrate with enterprise data systems, APIs, cloud services, and downstream applications.
• Apply SQL, NoSQL, database modelling, and data warehousing concepts to support efficient model training and inference.
• Partner with engineering teams to productionise models with scalability, observability, reliability, and security in mind.
• Ensure all AI systems are designed and deployed with strong Responsible AI principles.
• Develop practices for fairness, transparency, interpretability, explainability, privacy, accountability, and bias mitigation.
• Assess risks associated with foundation models, LLM outputs, hallucinations, model drift, adversarial misuse, and unsafe automation.
• Implement guardrails, evaluation standards, governance frameworks, and human‑in‑the‑loop processes where necessary.
• Support compliance with evolving data privacy, security, and ethical AI requirements.
• Translate complex AI concepts into clear business value propositions for stakeholders, leadership teams, and non‑technical audiences.
• Collaborate with product, engineering, security, legal, data, and business teams to define AI strategy and deliver measurable outcomes.
• Mentor junior scientists, ML engineers, and data professionals.
• Contribute to roadmap planning, architecture reviews, technical hiring, and AI capability development across the organization.

Educational Qualifications

PhD or master’s in computer science, artificial intelligence, machine learning, NLP, data science, or a related quantitative discipline.

Required Qualifications

• Strong research background with demonstrated contributions in AI/ML through publications, patents, applied research, industrial innovation, or equivalent scientific work.
• Deep knowledge of machine learning, deep learning, natural language processing, generative AI, large language models, agentic AI/AI agents.
• Proven experience developing advanced AI models from research through implementation and evaluation.
• Strong experience with AWS Bedrock and AWS SageMaker for foundation model development, model lifecycle management, and deployment workflows.
• Strong understanding of Responsible AI, including model governance, fairness, explainability, privacy, bias mitigation, and risk control.

Core Technical Skills

• Expert‑level proficiency in Python.
• Strong understanding of core ML concepts, including transformer architectures.
• Hands‑on experience with PyTorch, TensorFlow, Keras.
• Experience with model selection, hyper‑parameter tuning, training optimisation, evaluation metrics, model compression, and inference performance improvement.
• Strong expertise in NLP techniques: text classification, NER, embeddings, summarization, semantic retrieval, question answering, sentiment analysis, conversational AI.
• Experience building LLM applications: prompt engineering, fine‑tuning, RAG pipelines, evaluation, grounding, safety controls.
• Expertise in generative AI architectures, foundation models, and enterprise use‑cases involving text, image, document, and multimodal generation.
• Strong experience building AI agents and autonomous workflows, including agent architecture and orchestration, tool use and function calling, retrieval systems, memory design, reliability engineering, evaluation and guardrails, multi‑step planning and execution.
• Familiarity with modern agent frameworks and orchestration patterns for enterprise‑grade agentic systems.
• Experience in data cleaning, preprocessing, feature engineering, SQL, NoSQL, data warehousing, large‑scale data handling.
• Ability to apply mathematical reasoning to model design, tuning, experimentation, and performance analysis.
• Strong experience with AWS Bedrock, AWS SageMaker, AWS data and ML services relevant to AI model development and deployment.
• Familiarity with cloud‑native AI system design, scalable training, model serving, monitoring, and MLOps practices.
• Commitment to designing fair, accountable, transparent, and human‑centred AI systems.
• Ability to identify, assess, and mitigate ethical risks in model design, training data, inference, and deployment.
• Expertise in crafting, testing, and optimizing prompts for foundation models and LLM‑driven applications.
• Strong communication skills to explain technical concepts, model limitations, trade‑offs, and business implications to technical and non‑technical stakeholders.
• Strong collaboration skills across research, engineering, product, and leadership teams.
• Strong curiosity and commitment to ongoing learning in a rapidly evolving AI landscape.
• Ability to evaluate new tools, methods, and research directions and determine where they create business value.

Preferred Qualifications

• Postdoctoral research, industrial research lab experience, or significant applied research leadership in AI.
• Strong publication record in reputable AI/ML/NLP conferences or journals.
• Experience with multimodal AI, including text, image, audio, video, or document intelligence systems.
• Experience with RAG pipelines, vector databases, tool‑using agents, and advanced LLM evaluation frameworks.
• Familiarity with MLOps, CI/CD for ML, model monitoring, A/B testing, and production observability.
• Knowledge of privacy‑preserving AI techniques, model security, red teaming, and governance workflows.
• Experience leading AI innovation programmes or enterprise AI transformation initiatives.

Employment Eligibility

GE Healthcare is an Equal Opportunity Employer where inclusion matters. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.

Additional Information

Relocation Assistance Provided: No