Top Machine Learning Engineer Jobs in Mumbai

Lead the design, development, deployment, and operational excellence of enterprise identity and security platforms on AWS. Provide technical leadership, mentor engineers, influence architecture, and deliver secure, scalable cloud-native solutions. Champion DevSecOps, automation, testing, observability, governance, and continuous improvement across the software development lifecycle while collaborating with engineering and business stakeholders.

Performs independent validation of complex financial models across credit risk, lending, valuation, forecasting, and optimization. Evaluates model methodology, assumptions, documentation, performance, implementation, and governance controls. Prepares validation reports and recommendations for senior stakeholders, auditors, regulators, and governance committees. Partners with model owners and risk teams on regulatory examinations, audits, and model risk governance, while mentoring junior team members.

Leads global sales operations, strategy, go-to-market planning, governance, analytics, forecasting, incentive programs, and process improvement. The role drives sales digitalization, AI-powered efficiency initiatives, pipeline management, reporting, organizational transformations, and sales competency development across a global, matrixed organization.

Develops and integrates radiating components and passive radiation-pattern structures for multiband base-station antennas. Responsibilities include 3D and 2D electromagnetic simulation, prototype RF measurements, performance optimization, troubleshooting, technical documentation, and supporting the product lifecycle through mass production. The role collaborates with international cross-functional teams and requires relocation to Rosenheim, Germany.

Leads strategy, roadmap, lifecycle management, and execution for UPI payment products. Drives platform and API development, ecosystem adoption, AI-powered innovation, analytics, experimentation, governance, compliance, and stakeholder alignment across banks, fintechs, merchants, regulators, and technology teams.

Owns the strategy, architecture, development, and lifecycle management of RuPay card and device tokenization products. Leads payment-flow design across NFC, HCE, OEM Pay, and mobile-wallet ecosystems; defines APIs and integrations with technology teams; manages bank, fintech, network, and OEM stakeholders; ensures regulatory and security compliance; and improves product performance, transaction success, and customer experience.

SLB seeks graduate-level digital technology professionals for roles spanning artificial intelligence, software engineering, data engineering and science, machine learning, IIoT, high-performance computing, QA, software security, and UX design. Employees collaborate across disciplines in global technology centers, leveraging cloud computing, advanced data ecosystems, connectivity, and emerging technologies to develop solutions for the energy industry. The program includes training and professional development.

Lead cybersecurity trials and proof-of-concept engagements, translating technical findings into business value for executives and security teams. Research US regional cyber threats, create intelligence briefs and exposure reports, support partners with onboarding and co-selling, and contribute to thought leadership through events, webinars, workshops, and research-driven content. The role requires strong threat intelligence, offensive security, consulting, communication, presentation, collaboration, and self-direction skills.

Perform data collection, evaluation, annotation, pairwise comparisons, counting, and object tagging or labeling across audio, video, images, and other content to improve Telugu AI-generated content. This is a flexible, part-time, fully remote freelance role requiring native-level Telugu and advanced or fluent English proficiency.

Leads actuarial pricing initiatives for homeowners insurance, including rating plans, indication frameworks, advanced pricing models, segmentation strategies, regulatory filings, and model governance. Mentors actuarial analysts, investigates segmentation improvements, provides strategic recommendations to leadership, and collaborates with Product, Reserving, Data Science, Underwriting, Sales, and Claims. Requires advanced Excel, SQL, Python or R, insurance pricing experience, and progress toward actuarial credentials.

Supports MSCI Sustainability and Climate data product distribution across Snowflake, feeds, MCP, and portals. Enhances AI readiness through data quality, metadata enrichment, standardization, catalog development, and workflow improvements. Assists with sustainability data projects, client communications, and cross-functional coordination among Product, Research, Engineering, and Client Support teams.

Lead enterprise data science and analytics initiatives, including predictive and prescriptive modeling, AI/ML solution deployment, dashboards, forecasting, data governance, automation, and scalable data pipelines. Partner with business and technology leaders to translate business challenges into measurable analytical outcomes, drive digital transformation, and present insights to senior leadership.

Supports internal audits through data analytics, automation, continuous monitoring, and AI/ML model testing. Develops SQL and Python-based scripts, dashboards, exception reports, and automated testing routines; analyzes large datasets, validates findings, assesses controls and model performance, and communicates recommendations to audit and business stakeholders. The role also documents testing procedures, contributes to audit standards, resolves transactional issues, and partners with audit teams on complex engagements.

Designs and maintains ETL pipelines integrating banking-system data into analytics platforms; builds data models for reporting, analytics, and machine learning. Collaborates with analysts, data scientists, and stakeholders to define requirements and delivers insights across risk, credit, and liabilities. Ensures data quality, security, governance, and compliance while monitoring and troubleshooting workflows and infrastructure performance.

Conduct security research involving malware, threats, vulnerabilities, adversary tracking, threat intelligence, detection, remediation, and reverse engineering. Analyze threat trends, process intelligence reports, identify security defects, contribute code and automation, support incident response, and use research results to improve security products and services. The role focuses on cloud-scale threat detection using machine learning and behavioral profiling.

Develop, validate, deploy, and monitor machine learning models for enterprise business and operational use cases. Responsibilities include data preparation, feature engineering, model development, explainability, ML pipeline construction, model versioning, retraining, monitoring, workflow integration, documentation, and knowledge transfer. The role requires advanced Python, Azure Machine Learning, SQL, production ML Ops, and experience delivering end-to-end solutions onsite in Abu Dhabi.

Develop production-ready AI and machine learning applications using cloud AI services and generative AI. Responsibilities include building and maintaining LLM pipelines, supporting training and deployment, implementing observability, managing prompts and RAG workflows, automating validation and CI/CD, and ensuring security, compliance, and ethical model use. The role also requires optimizing machine learning models, collaborating across teams, monitoring project progress, and sharing technical knowledge.

Drive adoption and value realization of Neara’s digital-twin platform among Japanese utility customers. Responsibilities include customer engagement, platform enablement, training, ROI and business-case development, stakeholder management, solution expansion, and collaboration with Sales, Deployment, Product, and Engineering teams. The role requires translating customer strategic goals into technical solutions and measurable business outcomes, with regular customer and team travel in Japan and internationally.

Build and deploy engineering-grade digital models for Japanese utility clients by integrating GIS, LiDAR, and other data sources. Configure platform projects, create dashboards, resolve model inaccuracies, support technical delivery and pre-sales, and collaborate with product and engineering teams on platform improvements and Japanese localization. The role requires customer-facing communication in Japanese, global collaboration in English, mentoring, and occasional travel to customers and international offices.

Develop and lead production-ready AI and machine learning applications using NLP, generative AI, deep learning, neural networks, chatbots, and image processing. Design scalable cloud or on-premises pipelines, deploy and integrate models, optimize performance, and ensure maintainability. Serve as a subject matter expert, make team decisions, mentor engineers, collaborate across teams, and align AI solutions with stakeholder and business objectives.

Lead the architecture, development, deployment, and monitoring of production-grade machine learning systems for high-definition, ADAS, ISA, and IVI maps. Lead work across computer vision, NLP, deep learning, Generative AI, Agentic AI, MLOps, data ingestion, model training, inference, and scalable cloud or in-vehicle deployment. Provide technical leadership, conduct architecture and code reviews, integrate ML outputs with mapping workflows, and translate business requirements into reliable ML system designs.

Leads global AI-first MarTech engineering strategy, architecture, governance, compliance, and delivery. Oversees scalable digital platforms, public-facing properties, GenAI applications, R&D, proof-of-concepts, and automated compliance capabilities. Builds and mentors a global team of engineering and AI professionals, manages vendors, and partners with marketing, business, cloud, security, privacy, infrastructure, and legal stakeholders to deliver secure, high-performance digital experiences.

Design, clean, analyze, and visualize data using SQL and Python; build Tableau dashboards; apply statistics and basic ML/DS concepts; follow software/data-engineering practices (version control, unit testing, high-performance code); work with structured and unstructured data and cloud environments.

Lead product vision and discovery for a genomics-driven diagnostic and personalization platform. Validate hypotheses with patients, clinicians, and partners; translate research into product specs; coordinate labs and data providers; partner with engineers and researchers to build AI prototypes; shape data, regulatory, and GTM strategy while making core product and architectural decisions.

Build core components of a diagnostic and personalization platform: backend data pipelines, frontends, services for genomic data ingestion, ML model integration, APIs, and cloud infrastructure. Collaborate with product and ML teams, iterate on prototypes and MVPs, and make architectural decisions supporting scalability and reliability.