Top Machine Learning Jobs in Delhi

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.

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.

Lead and coordinate data, technology, cyber and privacy incident responses; manage crisis and regulatory notifications; run incident reviews, readiness testing, reporting, and remediation tracking across the enterprise.

Develop Python-based automation and reusable data workflows, build and deploy ML, NLP, OCR and Generative AI solutions, design ETL/ELT pipelines, implement AI assistants and RAG solutions, support cloud analytics on Azure/AWS/Microsoft Fabric, and collaborate with stakeholders using Git/Azure DevOps and Agile.

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.

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.

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.

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.

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

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.

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 analytics strategy across data collection, BI, ML and automated analytics to enable data-driven decisions. Set standards, solve complex business problems, influence senior stakeholders, drive product/process improvements, and guide organizational units to deliver measurable business value.

Lead statistical strategy and delivery for Phase I-IV clinical trials embedded with a pharmaceutical sponsor. Design analyses, support protocol and reporting activities, oversee programming/CRO work, apply SAS/R (R Shiny)/Python and ML/DL methods for analyses and automation, and mentor junior statisticians.

Lead the risk product suite roadmap and execution for merchant onboarding, fraud prevention, and credit risk. Manage a risk engineering and data science squad, build real-time risk engines and ML models, optimize KYC/KYB onboarding flows, and develop lending/settlement risk models to minimize financial loss while preserving merchant and buyer experience.

Work with Product, Business, and Engineering to collect, clean, analyze data, build Python and SQL automation, contribute to internal analytics platforms, assist cloud deployments, and document technical solutions to support decision-making.

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.

Lead backend architecture and engineering: design scalable APIs and services, mentor engineers, write complex code, enforce best practices for databases, testing, observability, and integrate ML/LLM workloads.

Lead forecasting, workforce and workload management for Trust & Safety contact center operations. Build BI dashboards and analyses, forecast volumes and BPO headcount, optimize staffing and SLAs, apply AI/ML and NoSQL data to drive operational improvements and mentor peers.

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.

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.