korn ferry is partnering with gen ai-native health tech company which transforms the patient experience by enabling greater engagement through personalized digital health tools. the platform is used by more than 1,000 healthcare organizations and serves over 10 million patients annually, improving healthcare outcomes by empowering patients to manage their care.
title: ai engineer
reporting to: director, data & ai
location: bengaluru (bangalore)
opportunity:
get well is seeking a talented and innovative 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 ideal for a technically proficient professional with hands-on experience in training and customizing llms (both unimodal and multimodal) for complex domain use cases. the successful candidate will work through all phases of the ai development life cycle, including concept 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:
ai model development and customization
- develop, train, and fine-tune large language models (llms) for healthcare-specific applications
- 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 performance, accuracy, and efficiency for production environments
technical implementation
- write clean, maintainable code for ai model training, evaluation, and inference
- maintain data pipelines for model training and continuous improvement using feedback loops
- implement best practices for model versioning, experiment tracking, and reproducibility
- integrate ai solutions with existing product architectures and infrastructure
data engineering and management
- process and prepare healthcare data for use in training and testing ai models
- implement data privacy and security measures compliant with healthcare regulations
- create synthetic data generation solutions when appropriate
- develop strategies for handling imbalanced, sparse, or noisy healthcare datasets
evaluation and bias assessment
- design and implement robust evaluation frameworks for ai model performance
- develop metrics and kpis to measure model effectiveness in real-world scenarios
- identify and address potential biases in training data and model outputs
- conduct thorough testing to ensure model reliability and accuracy
collaborative development
- work 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
continuous learning and innovation
- 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 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
