ML Engineer

This is a fully remote position, open to applicants in India.

📋 Description

• Design, develop, deploy, monitor, and maintain proprietary machine learning models, large language models (LLMs), and multi-agent AI systems for applications in healthcare.

• Create AI solutions aimed at enhancing healthcare operations, workflows, efficiency, and service delivery.

• Customize and optimize open-source LLMs while integrating enterprise LLM platforms to meet healthcare-specific needs.

• Formulate prompting strategies to enhance LLM performance across intricate healthcare scenarios.

• Develop AI solutions for processes such as prior authorization and various healthcare operational workflows.

• Create scalable, secure, and maintainable Python microservices utilizing FastAPI.

• Design and implement RESTful APIs and backend services that support machine learning and AI applications.

• Deploy and orchestrate services using Kubernetes, with an emphasis on reliability, scalability, security, and operational effectiveness.

• Utilize Google Cloud Platform (GCP) infrastructure to deploy and manage production-level AI and machine learning workloads.

• Monitor the performance of models and services, optimizing for reliability, latency, scalability, and resource utilization.

• Investigate emerging AI and machine learning techniques relevant to healthcare and adapt significant research into practical applications.

• Conduct independent technical research and contribute to scientific publications and research papers.

• Develop intelligent simulation systems to replicate or automate service-led workflows for improved efficiency and cost savings.

• Collaborate with product, engineering, healthcare, and other stakeholders to convert requirements into effective AI solutions.

• Ensure that AI systems comply with ethical standards, privacy, security, and healthcare regulatory requirements.

• Maintain technical documentation and effectively communicate AI concepts, system capabilities, limitations, and outcomes to both technical and non-technical audiences.

• Contribute to the ongoing enhancement of AI engineering practices, model development processes, and production infrastructure.

⛳️ Requirements

• 3–5 years of experience in building scalable machine learning systems, AI applications, and backend services.

• Bachelor's degree in Computer Science, Engineering, or a related field, preferably from a Tier-I institution.

• Strong practical expertise in Large Language Models (LLMs), prompting techniques, fine-tuning, and Generative AI.

• Solid understanding of machine learning principles and hands-on experience with TensorFlow, PyTorch, or similar frameworks.

• Experience in developing, deploying, monitoring, and optimizing production-level machine learning models.

• High proficiency in Python and practical experience with FastAPI for constructing RESTful microservices.

• Experience with Kubernetes and the deployment of containerized applications.

• Familiarity with Google Cloud Platform (GCP) and cloud-based ML/AI infrastructure.

• Proven experience in building scalable backend systems and production-grade AI services.

• Capability to conduct independent AI/ML research and contribute to scientific papers or technical publications.

• Strong analytical and problem-solving skills, with an ability to convert research findings into practical engineering solutions.

• Knowledge of AI ethics, healthcare data privacy, security, and regulatory considerations.

• Excellent written and verbal communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.

• Strong sense of ownership, collaboration, and execution abilities in dynamic, cross-functional environments.

• Willingness to travel to the Vadodara, Gujarat headquarters for approximately one week when necessary.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health insurance and wellness programs.

• Opportunities for professional development and continuous learning.

• Flexible working hours and remote work options.

• Supportive and innovative work environment.