ML Engineer

🔥 14 hours ago

🇮🇳 India – Remote

💵 ₹2.5M - ₹5M / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 20%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Weekday (YC W21)

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2021

💼 Consulting

👥 HR Tech

☁️ SaaS

Consulting • HR Tech • SaaS

Weekday is a modern recruitment platform that combines AI technologies with a vast database of potential candidates, aiming to streamline the hiring process for companies in India. They offer various services, including a proactive outreach approach that helps employers connect with top talent, as well as tools for candidates to easily apply for jobs. Weekday's emphasis on candidate engagement through multiple channels, including email, WhatsApp, and phone calls, sets it apart in the competitive landscape of recruitment agencies.

📋 Description

• 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

• 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