ML Engineer

𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟮𝟱𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟱𝟬𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟮𝟱-𝟱𝟬 𝗟𝗣𝗔)

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.