Machine Learning Engineer

What you can expect This role uniquely requires the intersection of time-series forecasting expertise and modern LLM capabilities, specifically applied to workforce management challenges. Join our Workforce Engagement Management (WEM) team to solve real-world challenges at scale using cutting-edge ML techniques. We're looking for a passionate and experienced ML engineer. You will play a key role in building GenAI-powered forecasting, scheduling, and adherence solutions. Drive the development of intelligent WEM systems by integrating LLMs, time-series models, and optimization engines to revolutionize how workforce operations are managed. Join a dynamic team dedicated to achieving groundbreaking results. About the Team Collaborate with cross-functional teams (product, ops, and engineering) to deliver seamless AI integrations. Fine-tune, prompt-engineer, and orchestrate LLM pipelines to solve real-world forecasting and adherence challenges. Develop smart forecasting and scheduling engines that can adapt and learn from operational data. What we’re looking for Bachelor’s/Master’s/PhD in Computer Science, Artificial Intelligence, Machine Learning, or related field. 4–6 years of hands-on experience in AI/ML engineering roles. Have programming skills in Python, with knowledge of software engineering best practices including data manipulation libraries like Pandas and NumPy for preprocessing and feature engineering. Have experience with ML frameworks - MXNet (but strongly recommend TensorFlow or PyTorch) . Solid understanding of time-series preprocessing, feature engineering, and forecasting algorithms ((Forecasting algorithms :Neural Forecast,N-BEATS, N-HiTS,Temporal Fusion Transformer, Darts ). Have experience with Production optimization tools like CP-SAT or Google OR-Tools.Background in NLP and transformer-based models. Have experience with LLMs, fine-tuning, Prompt engineering, Context engineering, MCP and Agentic AI frameworks (e.g., LangChain, CrewAI, LlamaIndex, PydanticAI, DSPy, AutoGen, Swarm, OpenAI Agents SDK. Experience with Git, CI/CD, and scalable deployment practices. Responsibilities Design and optimize AI/ML algorithms for WEM use cases. Leverage time-series analysis and optimization frameworks (e.g., CP-SAT) for forecasting and scheduling. Engineer and tune LLM prompts and workflows to enhance scheduling and forecasting insights. Develop evaluation frameworks and feedback loops to optimize ML model and agent performance. Build and optimize infrastructure for distributed model training across multi-node, multi-GPU clusters. Collaborate with teams for seamless integration of AI/ML features into production systems. Contribute to design reviews, technical discussions, and code quality standards. #Remote #Indiaonly #RemoteIndia Ways of Working Our structured hybrid approach is centered around our offices and remote work environments. The work style of each role, Hybrid, Remote, or In-Person is indicated in the job description/posting. Benefits As part of our award-winning workplace culture and commitment to delivering happiness, our benefits program offers a variety of perks, benefits, and options to help employees maintain their physical, mental, emotional, and financial health; support work-life balance; and contribute to their community in meaningful ways. Click Learn for more information. About Us Zoomies help people stay connected so they can get more done together. We set out to build the best collaboration platform for the enterprise, and today help people communicate better with products like Zoom Contact Center, Zoom Phone, Zoom Events, Zoom Apps, Zoom Rooms, and Zoom Webinars. We’re problem-solvers, working at a fast pace to design solutions with our customers and users in mind. Find room to grow with opportunities to stretch your skills and advance your career in a collaborative, growth-focused environment. Our Commitment​ At Zoom, we believe great work happens when people feel s ... (truncated, view full listing at source)