Top Machine Learning Jobs in India

Lead GBSC data engineering and analytics initiatives: design data/ETL infrastructure, implement automation, enable large-scale structured and unstructured data analysis, manage team delivery, and communicate insights to influence business decisions.

Lead end-to-end data science projects using machine learning and statistical modeling, develop predictive models, mentor junior scientists, and translate business needs into data-driven solutions to improve operations and customer experience.

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 Senior Software Engineer will develop AI agents, design data architectures, and ensure compliance with healthcare regulations while collaborating across teams.

Develop and deploy digital twins, multiphysics and structural models, and physics-informed AI to predict and optimize semiconductor process-structure-performance interactions. Apply computational materials science, ML, GenAI/LLMs, and sparse-data methods to accelerate technology development, yield, and reliability. Collaborate with global engineering teams to translate modeling insights into fab-technology co-optimization.

Design, implement, and support end-to-end platform features and complex user stories. Build reusable components, perform code reviews, create POCs, integrate systems, address non-functional requirements, troubleshoot cross-technology issues, and work with CI/CD and cloud (Azure) data processing pipelines.

Design and build scalable Amazon Connect digital-channel solutions and GenAI features. Develop backend services and orchestration using Python, AWS Lambda, Step Functions, and API Gateway. Implement GenAI/ML via Bedrock, Lex, and SageMaker, create reusable frameworks for migration from Genesys/LivePerson, and collaborate across product and architecture teams.

Lead the plant-level digital transformation by piloting and scaling digital technologies (MES, IIoT, APC, Digital Twin, AI/ML), developing roadmaps, delivering analytics and dashboards, managing stakeholders, driving change management, and improving efficiency, quality, and sustainability.

Design, build, and deploy advanced ML models (including LLMs) and statistical algorithms to personalize marketing content. Explore text and image opportunities, run A/B and multivariate experiments, collaborate across teams, present to stakeholders, and mentor ML team members.

Serve as the Palo Alto firewall subject-matter expert: audit and validate policies with AlgoSec/Firemon, apply AI/ML analytics for threat detection and automated response, mentor analysts, recommend security products, ensure compliance, and collaborate with leadership across US shift.

Lead large-scale digital transformation programs for supply chain and manufacturing clients using AI/ML, Industry 4.0/5.0, IoT/IIoT, cloud, and automation. Advise C-level stakeholders, architect digital solutions (digital twins, predictive analytics, MES/SCADA integrations), manage multi-geography teams, drive change management, and support pre-sales and practice growth.

Lead design, build, and scale cloud-native, AI-powered backend services and intelligent agents using Python. Drive architecture, mentor engineers, ensure high-quality, secure, and performant SaaS features, and support deployments and occasional off-hours maintenance.

Lead the Journals product area for BlackLine's AI-native finance platform: define roadmap, write PRDs/epics, run discovery, engage customers, partner with Engineering/Design/Data Science, and deliver reusable close services and journal capabilities to production.

Design, build, test, and deploy scalable backend and AI-powered services using Python and React. Collaborate with product and architecture teams, drive technical decisions, enforce quality/SDLC practices, mentor developers, support releases, and provide occasional off-hours support.

Lead a team to develop and apply next-generation defect detection equipment and processes, accelerate technology transfer, mentor staff, analyze experiments and defects, build detection techniques, manage cross-functional projects, define program health metrics, and collaborate globally to improve process yield. Data analysis, ML, and statistical modeling expertise is an advantage.

Lead design, build, and maintain secure, scalable software systems; write and review production-quality Python code; drive adoption and safe use of enterprise AI-assisted engineering tools; improve automation, resiliency, and operational stability; evaluate vendors and lead engineering communities of practice within Commercial and Investment Banking.

Lead and defend advanced statistical and machine learning models for credit and operational risk; implement, validate, monitor, and convert Python-based solutions in Big Data/HPC environments; collaborate with regulators/auditors, support production deployments, and drive process improvements across model lifecycle.

Manage Capital Markets data remediation and analytics projects: translate business questions into analytic requirements and user stories, design solutions, validate and reconcile multi-source data, build dashboards and repeatable pipelines, ensure data quality, track milestones, and support stakeholder engagement through project delivery.

Designs, develops, tests, and maintains secure, scalable software across the SDLC. Produces architecture artifacts, debugs complex systems, leverages AI-assisted development tools, analyzes large data sets to improve code and architecture, and contributes to engineering communities while promoting secure and resilient application practices.

Design, validate, and monitor fraud strategies using data analytics and ML. Build Looker dashboards and data pipelines, partner with Product/Tech/Operations, test controls, ensure compliance, and balance fraud mitigation with revenue, costs, and customer impact.

Lead design and delivery of production-grade ML and software solutions, partnering with product, engineering, data, and risk. Build, deploy, and monitor generative and other ML models, automate remediation and delivery, evaluate vendors, and mentor engineers to adopt scalable, secure, and responsible ML practices.

Manage risk and controls for wholesale lending product and technology changes. Assess emerging automation (AI/ML/LLMs), perform control reviews, lead remediation, track metrics, and advise product and technology teams to ensure compliant, controlled releases.

Lead design, implementation, and monitoring of control frameworks (CORE); drive automation, AI/ML and analytics for proactive risk identification; own RCSAs and control testing; partner with stakeholders to ensure regulatory compliance, streamline controls, and present findings to senior management.

Designs, implements, validates, and deploys machine learning models and data pipelines. Develops data ingest/validation/cleaning/monitoring, evaluates vendor solutions, authors technical documentation, and mentors junior engineers.

Design, build, deploy, and maintain AI/ML solutions (including LLMs and Generative AI) for healthcare. Provide technical leadership for chatbots, conversational AI, and NLP systems; ensure responsible AI, security, and operational excellence; mentor team members and collaborate with product and engineering to integrate AI in cloud modernization efforts.