# Machine Learning Engineer > Weekday AI · India (Remote) · Full-time · Posted 2026-09-23 **Salary:** INR 4,000,000–5,000,000 **Workplace:** remote **Department:** Weekday's Client via platform ## Description **This role is for one of Weekday’s clients Salary range: Rs 4000000 - Rs 5000000 (ie INR 40 - 50 LPA)** Min Experience: 3+ years Location: Remote (India) JobType: full-time We are looking for a hands-on **Machine Learning Engineer** to design, develop, deploy, and scale AI/ML systems, with a strong focus on **Large Language Models (LLMs), Generative AI, and production-grade AI applications**. The ideal candidate will have strong Python engineering skills and experience building AI applications using modern frameworks and infrastructure. This role is suited for someone comfortable working in a fast-paced, high-ownership environment where requirements may evolve quickly and engineers are expected to take broad ownership from experimentation through production deployment. You will work on advanced AI systems involving LLMs, multi-agent architectures, intelligent automation, and real-world business workflows. ## Requirements Key Responsibilities - Design, develop, and deploy production-grade machine learning and Generative AI applications. - Build and integrate **LLM-powered applications, intelligent agents, and AI automation workflows**. - Develop scalable backend services and APIs using **Python and FastAPI**. - Work with modern ML frameworks and technologies to develop, evaluate, and improve AI systems. - Design and implement AI/ML pipelines covering experimentation, evaluation, deployment, monitoring, and optimization. - Integrate foundation models and LLM APIs into production applications. - Build reliable AI systems capable of handling complex, multi-step workflows. - Work with cloud infrastructure and containerized environments to deploy and scale ML applications. - Collaborate with engineering and product teams to translate business problems into practical AI solutions. - Evaluate model performance, identify failure modes, and continuously improve accuracy, reliability, latency, and cost. - Contribute to technical architecture decisions across ML systems, APIs, infrastructure, and deployment. - Work effectively in ambiguous environments and take ownership across the complete development lifecycle. Technical Requirements - Strong proficiency in **Python** and experience building production software. - Strong understanding of **Large Language Models (LLMs) and Generative AI**. - Hands-on experience with **FastAPI** or similar Python-based backend frameworks. - Experience building and deploying production AI/ML applications. - Understanding of machine learning fundamentals, model development, evaluation, and deployment. - Experience working with APIs, data pipelines, and scalable backend systems. - Strong software engineering practices, including testing, debugging, version control, and production deployment. Infrastructure & ML Stack - Experience with **Kubernetes** and containerized application deployment. - Experience with **Google Cloud Platform (GCP)** or comparable cloud environments. - Experience with **PyTorch** or other modern deep learning frameworks. - Familiarity with production ML infrastructure, monitoring, and deployment practices is preferred. Experience - **3–5 years of relevant professional experience** in Machine Learning, AI Engineering, Software Engineering, or a closely related field. - Demonstrated experience taking AI/ML solutions from experimentation or prototype through production. - Experience working on LLM, GenAI, agentic AI, or intelligent automation systems is strongly preferred. Candidate Profile - Comfortable working in an early-stage or high-growth environment with broad ownership. - Strong problem-solving and analytical abilities. - Able to operate effectively with ambiguity and changing requirements. - Strong communication and cross-functional collaboration skills. - Demonstrated ability to take ownership of technical problems and deliver production-ready solutions. - Founding engineer or startup experience is preferred. - Experience contributing to published research or open-source LLM/agent projects is a strong plus. - Healthcare or healthcare-AI domain exposure is beneficial but not mandatory. Education A Bachelor's degree in Computer Science, Engineering, Machine Learning, Artificial Intelligence, or a related discipline is preferred. Equivalent practical experience, strong production engineering experience, significant open-source contributions, research work, or startup/founding experience may also be considered. Candidate Preferences - **Gender:** No preference. - **Notice Period:** Candidates with a notice period of **30–45 days or less** are preferred. - **Current Industry:** No specific current-industry requirement. Candidates from AI, ML, software engineering, SaaS, technology, research, or other relevant domains are welcome. Additional Preferred Criteria - Founding engineer or startup background with demonstrated ability to take broad ownership. - Published research, technical publications, or meaningful open-source contributions in LLMs, GenAI, agents, or machine learning. - Experience working on complex AI workflows or multi-agent systems. - Exposure to healthcare or other highly regulated domains is an advantage. Must-Have Skills - **Python** - **Large Language Models (LLMs)** - **FastAPI** - Machine Learning - Generative AI Good-to-Have Skills - **Kubernetes** - **GCP** - **PyTorch** - LLM/Agent Frameworks - Production ML Deployment - MLOps - Open-Source AI/ML Contributions - Healthcare AI ## Apply [Apply at Weekday AI](https://apply.workable.com/weekday-1/j/05EEEF6AFC/apply) --- Powered by [Workable](https://www.workable.com)