Overview
Develop and support machine learning models and data-driven solutions for healthcare use cases including document processing, analytics, and intelligent automation. Work with senior engineers, product teams, and business stakeholders to build, test, and deploy scalable AI solutions.
What you'll do
- Develop and implement machine learning models under guidance to solve business problems in healthcare.
- Work on data preprocessing, feature engineering, and model evaluation as part of AI/ML pipelines.
- Assist in building and integrating ML solutions with APIs and applications.
- Collaborate with engineering, product, and data teams to understand requirements and deliver solutions.
- Support development of AI solutions that adhere to privacy, security, and responsible AI principles.
- Work with structured and unstructured data, including text data for NLP use cases.
- Assist in optimizing model performance and improving accuracy through iterative testing.
- Create basic dashboards, reports, or visualizations to present insights.
- Participate in code reviews, testing, and debugging to ensure quality delivery.
- Document solutions, workflows, and model behavior for reuse and knowledge sharing.
- Design and optimize prompts for Large Language Models to achieve desired outputs for various use cases.
- Build and maintain Retrieval-Augmented Generation pipelines for document Q&A, knowledge retrieval, and contextual response generation.
- Develop and support agentic AI workflows using frameworks such as LangChain, LangGraph, or similar orchestration tools.
- Implement and manage ETL pipelines for data ingestion, transformation, and preparation for ML/GenAI workloads.
- Deploy and manage AI/ML solutions on AWS cloud infrastructure, including SageMaker, Lambda, Bedrock, and S3.
- Monitor and evaluate LLM performance, including response quality, latency, and cost optimization.
What you'll need
- 2–4 years of experience in Machine Learning, Data Science, or the AI domain.
- Develop and support agentic AI workflows using frameworks such as LangChain, LangGraph, or similar orchestration tools.
- Hands-on experience with Python and libraries such as Pandas, NumPy, and Scikit-learn.
- Basic understanding of machine learning concepts such as classification, regression, clustering, and NLP.
- Exposure to the model development lifecycle, including data preparation, training, and evaluation.
- Experience working in a team environment on shared deliverables or projects.
- Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
- Strong foundation in machine learning and data analysis.
- Good understanding of data structures and programming fundamentals.
- Knowledge of Python-based ML tools and frameworks.
- Familiarity with cloud-based environments.
- Strong analytical and problem-solving skills.
- Good communication skills to work with both technical and non-technical stakeholders.
- Ability to work collaboratively in a fast-paced team environment.
- Willingness to learn and adapt to emerging AI/ML technologies.
Nice to have
- Exposure to Generative AI, LLM concepts, and prompt engineering.
- Familiarity with frameworks such as PyTorch or TensorFlow.
- Experience with APIs, data integration, or cloud platforms such as Azure, AWS, or GCP.
- Knowledge of vector databases or basic information retrieval concepts.
- Experience working with data formats such as CSV, JSON, or documents including PDF and Word.
Details
- Location: Hyderabad, India.
- Hybrid work arrangement.
- Working hours: 2:30 PM IST to 11:30 PM IST.
Read the full description and apply on the company’s own careers page.