Top Machine Learning Jobs in Delhi

Designs, audits, and optimizes telecom networks across RAN, Transport, Core, OM and Services. Supports pre-sales with technical analysis, proposes scopes and estimates costs, documents service offerings, and applies automation and ML analytics to drive network performance and efficiency while managing stakeholder and financial aspects.

Sell SailPoint's IGA identity security SaaS to $5B+ enterprises by engaging C-level stakeholders, managing long sales cycles with POCs/RFPs, collaborating with GSIs and channel partners, developing account and opportunity plans, and meeting quota using Challenger methodology.

Lead scientific and strategic AI efforts for Vaccines Medical: define AI vision and roadmap, govern responsible AI standards, prioritize and deliver validated AI-enabled solutions, partner cross-functionally, oversee deployment and adoption, manage budget and vendors, and ensure regulatory, ethical, and scientific compliance across global medical affairs.

Design and implement scalable backend services, lead full software lifecycle, write design docs, mentor engineers, collaborate cross-functionally, improve performance and quality, and integrate AI tools to boost development productivity.

Lead design and implementation of autonomy and edge-AI software for air, land, and sea platforms. Develop tactical autonomy algorithms, integrate software with hardware, deploy and field-test capabilities, analyze mission data, mentor teammates, collaborate cross-functionally, and support customers and defense programs.

Design, build, and maintain backend APIs and services for a real-time supply chain visibility platform. Own system architecture, real-time event ingestion, data normalization, ML integration, monitoring, and production debugging while collaborating with Product and Data Science to deliver scalable, high-availability features.

Lead and manage client engagements end-to-end: scope, align, translate operational problems into technical briefs, track delivery, manage expectations, drive resolution, develop pipeline and grow account relationships while partnering with deployment and engineering teams.

Lead presales Solution Architect for UiPath Intelligent Automation. Run discovery workshops, design scalable enterprise automation, deliver demos/PoCs, produce technical proposals, define governance and integrations, and mentor teams while driving CoE and adoption.

Pravāh seeks candidates able to propose their own roles to contribute to AI solutions for electric grid management and operations, focusing on high agency, ownership, and strategic thinking.

Perform remote, part-time data tasks to improve AI content in Marathi, including data collection, annotation, pairwise comparisons, counting, and object tagging across audio, video, images, and collected data.

Build data-driven solutions and BI using Python, Power BI, and SQL. Implement DevOps pipelines with GitHub Actions/Azure DevOps, deploy on Azure/AWS, integrate APIs, apply unit testing and automation, and collaborate in Agile/Scrum with global teams. Support solution design, effort estimates, and use ML/DL/LLMs for intelligent features.

Lead AI R&D: design, develop, deploy scalable AI/ML and deep learning solutions for structured and unstructured data in BFSI product areas. Manage technical teams, mentor staff, integrate AI into products, ensure model scalability and production-readiness, and monitor AI trends and methodologies.

The AI Data Specialist will perform data collection, evaluation, annotation, and labeling tasks for AI-generated content in Tamil.

Perform data collection, evaluation, and annotation to improve AI-generated Kannada content. Tasks include pairwise comparisons, counting, object tagging and labeling across audio, video, images, and other data types.

Perform remote part-time data tasks to improve AI-generated Telugu content: collect, evaluate, and annotate data; conduct pairwise comparisons, counting tasks, and object tagging/labeling across audio, video, images. Flexible schedule, 10+ hours/week.

The consultant helps in AI project scoping, requirement gathering, business process analysis, and ensures alignment of AI projects with strategic objectives and user needs.

Lead business analysis and product requirements for Learning & Talent platforms. Capture and groom epics, features, and user stories; develop process and data models; liaise with stakeholders, delivery, and data engineering teams to ensure value-driven, compliant agile delivery.

Lead design, development, testing, debugging, and maintenance of mainframe applications using COBOL, JCL, VSAM, DB2, IMS, Assembler and CICS. Implement DevOps, CI/CD, automation, unit/integration testing, performance tuning, documentation, and modern IDE workflows (VS Code + mainframe extensions). Champion source control (Endevor and Git) and leverage modern tools and AI for optimization and transformation.

Perform satellite image classification and time-series analysis using Sentinel and PlanetScope data; build and optimize ML classification pipelines; develop Google Earth Engine apps and geospatial tools; apply advanced geospatial and hydrological modelling; coordinate ground-truth collection; produce reports, research papers, and decision-support dashboards; support stakeholder engagement.

Design and build machine learning systems for Coinbase, responsibly use generative AI tools and copilots, apply human-in-the-loop practices, and deliver measurable efficiency, cost, and quality improvements while collaborating in a remote-first environment with periodic in-person surges.

Lead strategy and execution for fraud risk management across the platform. Develop detection and prevention frameworks, optimize transaction screening, partner with Compliance, Data Science, Engineering and Product, oversee KPIs and vendor costs, lead a risk strategy team, and pilot AI/LLM-driven tools to enhance detection while enabling business growth and regulatory alignment.

Own data quality and root-cause analysis for prediction issues: detect anomalies, trace sources, fix processes, automate QA/reporting with Python and SQL, maintain dashboards, and partner with Data Science, Engineering, Product, and Commercial teams to improve prediction performance and customer-facing analytics.

Lead enterprise AI strategy and execution, build and mentor AI/ML teams, oversee end-to-end model lifecycle and MLOps, drive AI adoption across products and operations, establish governance and responsible AI practices, define AI architecture and standards, evaluate emerging technologies, and communicate impact to executive leadership.

Build and deploy machine learning models on large healthcare datasets, extract actionable insights, develop scalable data processing systems, collaborate with cross-functional teams, and communicate findings to stakeholders to improve patient outcomes.

Develop, train, evaluate, and optimize ML solutions and data pipelines; translate business requirements into production-ready ML code; perform feature engineering, model selection, and evaluation; document work, participate in code reviews, and support testing and data issue resolution.