ML Engineer

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Experience: 3+ yrs

Location: Remote (India)

Job Type: Full-time

We are looking for an experienced ML Engineer to design, build, deploy, and maintain advanced Machine Learning, Large Language Model (LLM), and multi-agent AI systems that improve healthcare operations and workflows.

The role combines machine learning engineering, generative AI, backend development, cloud infrastructure, and AI research . The ideal candidate will have strong hands-on experience building scalable ML systems, developing LLM-based solutions, and deploying production-grade AI services in secure and reliable cloud environments.

Requirements

Key Responsibilities

• •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 effective 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 , with a strong focus 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 continuously 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 appropriate 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.

What Makes You a Great Fit

• •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.