ML Engineer

Weekday (YC W21)

. Design, develop, deploy, monitor, and maintain proprietary ML models, LLMs, and multi-agent AI systems for healthcare applications .

Posted 9/26/2026full-timeRemote • IndiaMid-LevelSenior💰 ₹2,500,000 - ₹5,000,000 per yearWebsite

Tech Stack

Tools & technologies

CloudGoogle Cloud PlatformKubernetesMicroservicesPythonPyTorchTensorflow

About the role

Key responsibilities & impact

Design, develop, deploy, monitor, and maintain proprietary ML models, LLMs, and multi-agent AI systems for healthcare applications
Develop AI solutions that improve healthcare operations, workflows, efficiency, and service delivery
Customise and fine-tune open-source LLMs and integrate enterprise LLM platforms for healthcare-specific requirements
Develop prompting strategies to improve LLM performance across complex healthcare use cases
Build AI solutions for workflows such as prior authorisation and other healthcare operational processes
Develop scalable, secure, and maintainable Python microservices using FastAPI
Design and implement RESTful APIs and backend services supporting ML and AI applications
Deploy and orchestrate services using Kubernetes, focusing on reliability, scalability, security, and operational performance
Work with GCP infrastructure to deploy and manage production AI and ML workloads
Monitor model and service performance and optimise reliability, latency, scalability, and resource utilisation
Research emerging AI and ML techniques applicable to healthcare and translate relevant research into practical solutions
Conduct independent technical research and contribute to scientific publications and research papers
Develop intelligent simulation systems that emulate or automate service-led workflows to achieve efficiency and cost improvements
Collaborate with product, engineering, healthcare, and other stakeholders to translate requirements into effective AI solutions
Ensure AI systems follow ethical, privacy, security, and healthcare regulatory requirements
Maintain technical documentation and communicate AI concepts, system capabilities, limitations, and outcomes to technical and non-technical stakeholders
Contribute to continuous improvement of AI engineering practices, model development processes, and production infrastructure

Requirements

What you’ll need

3–5 years of experience building scalable ML systems, AI applications, and backend services
Bachelor's degree in Computer Science, Engineering, or a related discipline, preferably from a Tier-I institution
Strong hands-on expertise in Large Language Models (LLMs), prompting, fine-tuning, and Generative AI
Strong understanding of machine learning concepts and practical experience with TensorFlow, PyTorch, or similar frameworks
Experience developing, deploying, monitoring, and optimising production ML models
Strong proficiency in Python and hands-on experience with FastAPI for building RESTful microservices
Experience with Kubernetes and containerised application deployment
Familiarity with Google Cloud Platform (GCP) and cloud-based ML/AI infrastructure
Experience building scalable backend systems and production-grade AI services
Ability to conduct independent AI/ML research and contribute to scientific papers or technical publications
Strong analytical and problem-solving skills with an ability to translate research into practical engineering solutions
Understanding of AI ethics, healthcare data privacy, security, and regulatory considerations
Excellent written and verbal communication skills, including the ability to explain complex technical concepts to non-technical stakeholders
Strong ownership, collaboration, and execution skills in fast-paced, cross-functional environments
Willingness to travel to the Vadodara, Gujarat headquarters for approximately one week when required