Top Machine Learning Jobs in India

Develop statistically effective algorithms and apply machine learning, deep learning, and generative AI techniques to high-dimensional problems. Use hypothesis testing, data mining, and big-data tools to identify trends, build predictive models and recommender systems, collaborate with clients and stakeholders, and evaluate emerging datasets and technologies for scalable analytical solutions.

As a Staff Data Scientist, lead complex data science projects, define analytical frameworks, and mentor team members to improve healthcare outcomes using advanced models.

The Senior Technical Program Manager will drive execution across AI, data, and engineering initiatives, ensuring alignment, delivery rigor, and risk management.

Lead hands-on experimentation and prototype development for Generative and Agentic AI, focusing on LLMs, RAG, vector retrieval, and production-ready solution blueprints. Drive POCs to production by creating reusable prompts, architectures, evaluation frameworks, and implementation artifacts while partnering with engineering and product teams to ensure scalability, cost optimization, and responsible AI practices.

Lead Tier 2/3 diagnostics and resolution for cloud-native 4G/5G core outages, drive root-cause analyses and chronic-incident fixes, implement AI-driven monitoring, and provide technical guidance and training to the NOC to reduce MTTR and improve network stability.

The Engineering Manager will lead AI & ML initiatives focused on data collection, overseeing technical projects and developing a high-performing team. Responsibilities include providing technical direction, mentoring staff, ensuring system reliability, and maintaining data integrity and security. The role requires expertise in NLP and data processing with an emphasis on collaborative leadership and continuous innovation.

Join Celonis' 12-month Orbit Graduate Program as an Associate Value Engineer to support sales and customers by uncovering process problems, building proofs and AI prototypes on the Celonis platform, quantifying value, presenting to executives, driving change management, and feeding product insights back to engineering.

The Engineering Lead will design and implement technical features, work on ML pipelines, and mentor engineers while ensuring high-quality deliverables. This role requires collaborating with teams and managing the ML lifecycle for business value.

Develops and deploys machine learning algorithms, evaluates their accuracy, creates data pipelines, and contributes to innovations and technical documentation. Guides less experienced colleagues and collaborates across teams.

The Director of Data Platform Engineering will oversee the data infrastructure, manage relational databases, lead AI integration, and ensure data governance while fostering a collaborative team environment.

Lead end-to-end product development for AI-powered pricing and optimization solutions in manufacturing and distribution. Define roadmap, partner with data science and engineering to translate ML outputs into customer experiences, set metrics, and align stakeholders across sales, UX, and analytics.

Design, develop, deploy, and maintain AI/ML solutions (including LLMs and Generative AI) for healthcare. Lead chatbot and conversational AI initiatives, integrate AI into cloud architectures, ensure responsible and compliant AI practices, provide technical leadership, mentor team members, and drive operational excellence and alignment with enterprise AI strategy.

The role involves designing and maintaining data architectures, optimizing T-SQL code, conducting performance analyses, and ensuring data governance and quality.

Design and implement technical features, collaborate with clients, write production-ready code, ensure quality deliverables, mentor team members, and implement ML models on large scale.

Lead plant digital transformation by running pilot projects, evaluating disruptive technologies, partnering with startups, implementing MES/IIoT, and owning end-to-end product management and adoption to improve efficiency, quality, and sustainability.

Design and implement map and location quality testing end-to-end: statistical/experimental designs, sampling plans, ML models, metrics, and data/computing tools. Serve as SME, collaborate with stakeholders and customers, present findings, and lead quality strategy and implementation for map quality evaluation.

Lead development and deployment of scalable machine learning and analytics solutions for global map-making. Design process automation, build predictive and statistical models, lead modeling teams, collaborate with researchers, developers, architects, and customers, and work with big-data pipelines and point-cloud/computer-vision methods.

Perform static and dynamic malware analysis, develop detections and protections, analyze IOCs, validate AI/ML outputs, build automation tools, and publish threat research.

Design and deliver end-to-end packet core and 5G core solutions, optimize network performance, collaborate with product, R&D and customer teams, lead transformations, perform protocol and data analysis, and support deployment and knowledge transfer.

Lead the design and development of AI solutions for medical applications, focusing on NLP technologies and machine learning techniques for information extraction and synthesis.

Lead and manage a team of Machine Learning Engineers and Data Scientists to develop ML solutions that enhance user engagement and support business objectives in digital entertainment.

Lead the execution of data-driven modeling and analytics solutions for Technology Development, applying advanced data analysis and machine learning, while mentoring a team and collaborating cross-functionally.

Develop and optimize chemical processes for APIs, intermediates, and RSMs including literature review, lab feasibility, DoE, scale-up, technology transfer, impurity characterization, investigations, and compliance with cGMP and safety. Prepare protocols, reports, manage lab operations, equipment qualification, and lead/mentor lab staff. Preferred digital skills include Python, ML and AI.

The Senior AI Engineer will align AI solutions with business goals, support PoCs execution, collaborate on AI applications, and evaluate technologies in AI advancement.

Manage and grow a team responsible for observability, monitoring, and integrations across monetization systems. Improve reliability and data quality for billing, provisioning, subscriptions, and revenue-impacting workflows; define telemetry and integration strategies; implement anomaly detection and incident management; and partner with cross-functional stakeholders to ensure reliable customer and financial workflows.