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Weekday (YC W21) is an India-focused recruitment platform in the HR technology and SaaS space. It combines AI-driven tools with a broad candidate database to help companies identify and engage talent through proactive outreach. The platform supports communication across email, WhatsApp, and phone, while also giving candidates a straightforward way to discover and apply for roles.
Senior Machine Learning Engineer - India Remote
Build healthcare-focused machine learning, LLM, and multi-agent systems for a Weekday client. Develop secure AI services and backend infrastructure that improve healthcare workflows.
India₹2,500,000 – ₹5,000,000 / year
RemoteFull-timeMiddleSeniorEnglish RequiredMachine Learning EngineerDescription
- Design, deploy, monitor, and maintain proprietary machine learning models, LLMs, and multi-agent AI systems for healthcare applications.
- Create 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 requirements.
- Develop prompting approaches that improve LLM performance across complex healthcare use cases.
- Build AI solutions for prior authorisation and other healthcare operational workflows.
- Develop scalable, secure, maintainable Python microservices with FastAPI.
- Design and implement RESTful APIs and backend services for ML and AI applications.
- Deploy and orchestrate services with Kubernetes, prioritising reliability, scalability, security, and operational performance.
- Use Google Cloud Platform infrastructure to deploy and manage production AI and ML workloads.
- Monitor model and service performance while improving reliability, latency, scalability, and resource utilisation.
- Investigate emerging AI and ML techniques for healthcare and apply relevant research to practical solutions.
- Carry out independent technical research and contribute to scientific publications and research papers.
- Develop intelligent simulation systems that emulate or automate service-led workflows to improve efficiency and reduce costs.
- Work with product, engineering, healthcare, and other stakeholders to turn requirements into effective AI solutions.
- Ensure AI systems meet ethical, privacy, security, and healthcare regulatory requirements.
- Maintain technical documentation and explain AI concepts, system capabilities, limitations, and outcomes to technical and non-technical stakeholders.
- Help improve AI engineering practices, model development processes, and production infrastructure.
Requirements
- Three to five years of experience building scalable ML systems, AI applications, and backend services.
- Bachelor’s degree in Computer Science, Engineering, or a related field, preferably from a Tier-I institution.
- Hands-on expertise with large language models, prompting, fine-tuning, and generative AI.
- Strong knowledge of machine learning concepts and practical experience with TensorFlow, PyTorch, or comparable frameworks.
- Experience developing, deploying, monitoring, and optimising production ML models.
- Advanced Python skills and practical experience building RESTful microservices with FastAPI.
- Experience with Kubernetes and containerised application deployment.
- Familiarity with Google Cloud Platform and cloud-based ML and 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 abilities, with the capacity to turn 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 audiences.
- 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.
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