Manager Machine Learning

Talk to our team to build a custom IT, Cloud, or AI solution for your organization. Manager Machine Learning Location: Hyderabad Experience: 8+ years Mode of Work: 5 Days work from office Opportunity Overview As the Manager, Machine Learning Data Science, you will play a key role in building and scaling Cohere Health s AI capabilities in India. You ll lead a team of machine learning engineers and data scientists focused on developing and deploying models that automate and augment complex clinical and administrative workflows. This team is responsible for the full lifecycle of applied machine learning and data science from problem framing and experimentation to production model deployment and ongoing optimization. You ll work with structured and unstructured healthcare data to generate insights and power intelligent systems that improve prior authorization and broader clinical decision-making. As a player-coach, you ll combine hands-on technical contributions with team leadership, helping to establish best practices, mentor team members, and drive high-impact solutions in close partnership with Product, Engineering, Clinical, and Analytics stakeholders. This is an opportunity to shape both the technical direction and team culture within a growing global organization. What you ll do: Lead, mentor, and develop a team of machine learning engineers and data scientists, fostering a collaborative, high-performance environment Act as a hands-on contributor across the ML/DS lifecycle, including data exploration, feature engineering, model development, evaluation, and deployment Design, develop, and deploy machine learning models for retrieval, classification, and generative use cases across structured and unstructured data Translate complex business and clinical problems into scalable machine learning and data science solutions Establish and uphold best practices for experimentation, model validation, performance tracking, and reproducibility Partner cross-functionally with Product, Engineering, Clinical, and Analytics teams to align solutions with business priorities Guide the development of scalable data science and machine learning systems, including data preprocessing pipelines and production workflows Monitor model performance, identify opportunities for improvement, and drive continuous iteration and optimization Communicate technical concepts, methodologies, and insights clearly to both technical and non-technical stakeholders Contribute to hiring and scaling the team in India, including recruiting, onboarding, and coaching team members What you ll need: Must-haves Minimum 8+ years of experience in machine learning, data science, or applied AI roles, of those a minimum 2+ years of experience must be leading technical teams Strong hands-on experience building, evaluating, and deploying machine learning models in production Solid foundation in statistical methods, experimental design, and model evaluation Proficiency in Python and experience with ML frameworks (e.g., PyTorch, scikit-learn) Experience working with large, complex datasets (structured and/or unstructured) Strong problem-solving skills with the ability to translate business challenges into analytical solutions Excellent communication skills, with the ability to present complex concepts clearly to diverse stakeholders Experience working in fast-paced, evolving environments Nice-to-haves Experience in healthcare, particularly with payer, provider, or clinical data Experience with NLP, deep learning (e.g., transformers), or generative AI (e.g., RAG) Familiarity with MLOps practices and production ML systems Experience with Spark or large-scale data processing frameworks Exposure to cloud platforms (e.g., AWS, SageMaker) Experience working in a global or distributed team environment Prior experience in a GCC or building teams in India Job Category: Manager Machine Learning Job Type: Full Time Job Location: Hyderabad Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.