Senior AI Engineer

Title: Senior AI Engineer

Reporting to: Director, Data & AI

Location: Bengaluru (Bangalore)

Opportunity:

Get Well is seeking a talented and innovative Senior AI Engineer to join our growing team of AI experts focused on developing and deploying cutting-edge AI solutions in healthcare environments. This role is designed for a seasoned professional with extensive experience in machine learning (ML) and generative AI (GenAI), with a proven track record of productionizing models. The successful candidate will lead complex AI initiatives, driving innovation through all phases of the AI development lifecycle, from ideation and data preparation to model training, evaluation, deployment, and maintenance. 

This position reports directly to the Director, Data & AI, collaborating with cross-functional teams to implement AI solutions that enhance precision care, patient engagement and operational efficiency.

Responsibilities:

• Architect, train, and fine-tune large language models (LLMs) and traditional ML models for healthcare-specific applications ensuring scalability and performance.
• Design and implement techniques for domain adaptation of existing foundation models to healthcare contexts
• Design and implement multimodal AI systems that can process unstructured and structured healthcare data, including images
• Optimize model latency, throughput and resource efficiency in production environments, balancing accuracy and computational constraints

• Lead the deployment of AI models into production, ensuring seamless integration with existing healthcare systems and infrastructure.
• Implement robust MLOps practices, including automated model retraining, monitoring, and drift detection, to maintain model performance over time.
• Develop and maintain CI/CD pipelines for AI model deployment, ensuring reliability and scalability in high-stakes healthcare settings.
• Collaborate with DevOps teams to containerize models (e.g., using Docker, Kubernetes) and deploy them on cloud platforms (e.g., AWS, Azure, GCP).

• Mentor junior AI engineers, providing guidance on best practices for model development, evaluation, and deployment.
• Lead technical reviews of AI solutions, ensuring adherence to coding standards, reproducibility, and scalability.
• Drive the adoption of advanced ML techniques, such as ensemble methods, reinforcement learning, or graph neural networks, where applicable.
• Contribute to architectural decisions for AI systems, aligning technical solutions with business and clinical objectives.

• Oversee the design and implementation of scalable data pipelines for training, validation, and continuous model improvement.
• Ensure compliance with healthcare regulations (e.g., HIPAA, GDPR) in data handling, storage, and processing.
• Develop advanced techniques for synthetic data generation to address data scarcity or privacy concerns in healthcare datasets.
• Develop strategies for handling imbalanced, sparse, or noisy healthcare datasets

• Establish comprehensive evaluation frameworks, incorporating both quantitative metrics (e.g., F1 score, AUC) and qualitative assessments tailored to healthcare outcomes.
• Lead efforts to identify, quantify, and mitigate biases in training data and model outputs, ensuring fairness and ethical AI practices.
• Conduct stress testing and adversarial analysis to ensure model robustness in real-world healthcare scenarios.
• Develop KPIs to measure long-term model impact on clinical and operational outcomes.

• Partner closely with product teams to translate requirements into technical implementations
• Collaborate with clinical experts to ensure AI solutions meet healthcare needs
• Participate in agile development processes, including sprint planning and reviews
• Document technical approaches, model architectures, and implementation details

• Stay current with the latest advancements in LLMs and AI for healthcare
• Experiment with emerging techniques and technologies to improve model capabilities
• Contribute to internal knowledge sharing and technical discussions
• Identify opportunities for innovation and improvement in existing AI systems

Requirements:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field
• Minimum 6+ years of hands-on experience in AI/ML development.
• Experience in running models in real-world applications at scale
• Minimum 2+ years of hands-on experience with:
• Training and fine-tuning LLMs
• Implementing multimodal AI solutions
• Working through the complete AI development lifecycle
• Developing AI solutions for complex domain use cases
• Technical proficiency in:
• Python programming and ML frameworks (PyTorch, TensorFlow, or equivalent)
• Fine-tuning techniques for LLMs (prompt engineering, PEFT, LoRA, etc.)
• Natural Language Processing (NLP) and Understanding (NLU)
• Cloud computing and ML operations platforms
• Version control and collaborative development tools
• Experience with:
• Developing AI systems in regulated environments
• Healthcare data or other complex domain data
• Implementing evaluation metrics for AI model performance
• Deploying models to production environments
• Strong problem-solving skills and analytical thinking
• Ability to work effectively in fast-paced, agile environments
• Experience working with cross-functional teams
• Self-motivated with ability to work independently and collaboratively
• Excellent communication skills, both written and verbal
• Ability to explain technical concepts to non-technical stakeholders
• Strong documentation habits and attention to detail
• Collaborative mindset and team-oriented approach
• Basic understanding of healthcare data types and workflows (preferred)
• Awareness of healthcare regulatory requirements (e.g., HIPAA, GDPR)
• Knowledge of responsible AI practices and ethical considerations
• Familiarity with healthcare terminology and patient care processes (a plus)
• Adhere to all organizational information security policies and protect all sensitive information including but not limited to ePHI and PHI in accordance with organizational policy and Federal, State, and local regulations

About Get Well:

Now part of the SAI Group family, Get Well is redefining digital patient engagement by putting patients in control of their personalized healthcare journeys, both inside and outside the hospital. Get Well is combining high-tech AI navigation with high-touch care experiences driving patient activation, loyalty, and outcomes while reducing the cost of care. For almost 25 years, Get Well has served more than 10 million patients per year across over 1,000 hospitals and clinical partner sites, working to use longitudinal data analytics to better serve patients and clinicians. AI innovator SAI Group led by Chairman Romesh Wadhwani is the lead growth investor in Get Well. Get Well’s award-winning solutions were recognized again in 2024 by KLAS Research and AVIA Marketplace. Learn more at Get Well and follow-us on LinkedIn and Twitter.

Get Well is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.

About SAI Group:

• SAIGroup commits to $1 Billion capital, an advanced AI platform that currently processes 300M+ patients, and 4000+ global employee base to solve enterprise AI and high priority healthcare problems. SAIGroup - Growing companies with advanced AI; https://www.cnbc.com/2023/12/08/75-year-old-tech-mogul-betting-1-billion-of-his-fortune-on-ai-future.html
• Bio of our Chairman Dr. Romesh Wadhwani: Team - SAIGroup (Informal at Romesh Wadhwani - Wikipedia)

TIME Magazine recently recognized Chairman Romesh Wadhwani as one of the Top 100 AI leaders in the world - Romesh and Sunil Wadhwani: The 100 Most Influential People in AI 2023 | TIME