Senior Scientist – AI/ML at GE HealthCare

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

12 Sep, 26

Salary

0.0

Posted On

14 Jun, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Artificial Intelligence, Machine Learning, Generative AI, Large Language Models, Retrieval-Augmented Generation, Python, Docker, Flask, Time-series Modelling, Anomaly Detection, Physics-informed Modelling, Microservices Architecture, Prompt Engineering, Unsupervised Learning, Predictive Analytics, Technical Leadership

Industry

Hospitals and Health Care

Description

Job Description Summary The Senior Scientist – AI/ML will work in and lead teams as technical domain expert addressing statistical, machine learning and data understanding problems in early stage projects. In this role, you will contribute to the development and deployment of modern machine learning, semantic analysis, generative AI and statistical methods. GE HealthCare is a leading global medical technology and digital solutions innovator. Our purpose is to create a world where healthcare has no limits. Unlock your ambition, turn ideas into world changing realities, and join an organization where every voice makes a difference — and every difference builds a healthier world tex Job Description We are seeking a highly motivated Senior Scientist in AI/ML Domain to join our Healthcare Technology & Innovation Center, focused on building early-stage (low TRL) AI-driven solutions. This role is ideal for candidates who thrive at the intersection of applied machine learning, physics-informed modeling, and generative AI, and who are passionate about translating cutting-edge research into impactful innovations related to healthcare products, software and services. You will play a key role in conceptualizing, prototyping, and validating novel AI technologies, working closely with cross-functional teams and business stakeholders to shape the future of healthcare solutions, both for our customers and for internal users. Roles and Responsibilities As a Senior Scientist, you will be part of a data science or cross-disciplinary team on early development projects, typically involving large, complex data sets. These teams typically include statisticians, computer scientists, software developers, engineers, product managers, and end users, working in concert with partners in GE HC business units. Potential application areas include remote monitoring and diagnostics across infrastructure and industrial sectors, and operations optimization. Key Responsibilities AI/ML Innovation and Development Lead the design and development of novel AI/ML solutions for early-stage healthcare applications, including clinical decision support, equipment services productivity, and engineering workflow automation. Build and evaluate retrieval-augmented generation (RAG) and LLM-based agentic systems with emphasis on interpretability, traceability, and reliability. Develop advanced prompt engineering frameworks, including multi-agent workflows (e.g., Plan-and-Execute, ReAct) to enable complex reasoning tasks. Algorithm Design & Modelling Design and implement machine learning algorithms for structured and unstructured data, including: Time-series modelling Unsupervised and semi-supervised learning Anomaly detection and predictive analytics Integrate physics-informed or domain-aware models with data-driven approaches where applicable. Prototyping & Deployment Build end-to-end prototypes using modern software stacks (Python, Flask, microservices architecture). Deploy scalable solutions using containerization tools (Docker) and cloud-native environments. Develop modular, reusable ML pipelines for rapid experimentation in low-TRL environments. Technical Leadership: Provide technical leadership on projects, guiding architecture, design decisions, and development strategy. Mentor junior scientists and engineers, fostering a culture of innovation and rigor. Collaborate with clinical, product, and engineering stakeholders to translate business needs into AI solutions. Evaluation & Validation: Define evaluation frameworks to measure model accuracy, robustness, interpretability, and real-world applicability. Conduct pilot studies and validation exercises with domain experts. Establish best practices for responsible AI, explainability, and regulatory awareness. Education Qualification: Master’s or PhD in Computer Science, AI/ML, Engineering, or related fields (e.g., Aerospace, Mechanical, Electrical, Applied Math). Preferred Qualifications: Experience in healthcare AI or regulated industries (or strong interest in transitioning). ~10–15 years of experience in applied AI/ML, ideally in industrial or research environments. Strong programming skills in Python (experience with R/Matlab is a plus). Hands-on experience with: Machine Learning / Deep Learning frameworks Generative AI and Large Language Models (LLMs) Retrieval methods and RAG systems Time-series analysis and anomaly detection Experience with building and deploying ML systems (Flask, APIs, Docker, microservices). Demonstrated experience in leading technical projects or initiatives. Background in physics-based modelling, simulations, or engineering systems. Experience developing interpretable AI systems with explainability and traceability. Prior work on unsupervised learning, predictive maintenance, or sensor data analytics. Exposure to multi-agent systems and advanced prompt engineering techniques. Key Attributes Strong problem-solving and research mindset suited for ambiguous, early-stage problems. Ability to translate complex technical ideas into impactful solutions. Excellent collaboration and stakeholder engagement skills. Passion for innovation, experimentation, and real-world impact. Why Join Us Work on cutting-edge AI innovations in healthcare at low TRL. Opportunity to shape the future of clinical and engineering intelligence systems. Collaborative environment with world-class researchers and engineers. Access to real-world data, clinical insights, and global innovation programs. Nice-to-Have Skills Generative AI application frameworks (LangChain, agents, tool use) Cloud platforms (AWS/Azure/GCP) Data engineering and pipeline orchestration UI frameworks (optional: Streamlit, Flutter) Leadership: • Demonstrated expertise working in team settings in various roles • Demonstrated expertise in critical thinking and problem solving methods • Demonstrated expertise in presentation and communications skills Personal Attributes: • Demonstrated skill in serving as a change agent • Demonstrated skill in working in ambiguous environments Inclusion and Diversity 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. We expect all employees to live and breathe our behaviors: to act with humility and build trust; lead with transparency; deliver with focus, and drive ownership – always with unyielding integrity. Our total rewards are designed to unlock your ambition by giving you the boost and flexibility you need to turn your ideas into world-changing realities. Our salary and benefits are everything you’d expect from an organization with global strength and scale, and you’ll be surrounded by career opportunities in a culture that fosters care, collaboration and support. #EveryRoleIsVital #Hybrid #LI-SM1 At GE HealthCare, we see possibilities through innovation. We’re partnering with our customers to fulfill healthcare’s greatest potential through groundbreaking medical technology, intelligent devices, and care solutions. Better tools enabling better patient care. Together, we are not only building a healthier future but living our purpose to create a world where healthcare has no limits.

Responsibilities

Lead the design and development of novel AI/ML solutions for early-stage healthcare applications, including clinical decision support and engineering automation. Provide technical leadership by guiding architecture, mentoring junior scientists, and collaborating with cross-functional stakeholders.