Top Machine Learning Jobs in Delhi

Design and build scalable data and AI infrastructure for production LLM applications. Responsibilities include developing RAG systems, embedding and vector retrieval pipelines, AI agents, LLM evaluation and observability frameworks, and batch or streaming data platforms using Databricks, Spark, Snowflake, Delta Lake, and Airflow. The role also involves optimizing distributed workloads, establishing data governance and quality practices, and partnering with engineering and product teams to productionize AI capabilities.

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.

Drive enterprise sales growth for Akamai Cloud Infrastructure Services by developing new accounts, building strategic account plans, advising executive stakeholders, and identifying cloud, compute, and AI workload opportunities. Lead consultative cross-selling and upselling, manage complex infrastructure deals, forecast pipelines, negotiate contracts, and coordinate enterprise sales teams and technical specialists through close and adoption.

Evaluate and author high-quality computer science content to improve AI model reasoning and accuracy. Analyze complex CS problems, create scenarios/datasets, review AI outputs for correctness, and collaborate remotely to refine guidelines and documentation.

Build enterprise AI agents using Microsoft Copilot Studio and Azure AI Foundry. Develop topics, triggers, routing, fallback handling, generative answers, RAG, knowledge grounding, citations, metadata-based retrieval, multilingual capabilities, and prompts. Integrate agents with Power Automate, SharePoint, Dataverse, Teams, Azure AI Search, and Azure OpenAI or Foundry models. Support troubleshooting, security, environments, ALM, and DEV/UAT/PROD deployments.

Design, prototype, and deliver agentic AI solutions using ML and generative models. Partner with product, engineering, and delivery teams to build, evaluate, and deploy LLM-based solutions, run experiments and POCs, and communicate technical recommendations to stakeholders.

Evaluate AI-generated technical content, craft and answer advanced ML/AI prompts, assess model responses for accuracy, relevance, and clarity, identify errors or hallucinations, and provide feedback to improve AI systems.

Lead the product strategy and execution for an AI-first Email Marketing platform. Own Email Builder UX, AI-native content generation, Sequence AI, delivery/automation, experimentation, reporting, consent management, and cross-functional alignment to drive adoption, engagement, and revenue.

Own end-to-end enterprise sales across Southeast Asia: prospecting, partner-led growth, channel management, demos, negotiation, forecasting, and closing. Build territory and partner plans, hit revenue quotas, represent CloudSEK to CISOs, collaborate with engineering, marketing and customer success, and manage onboarding and contract negotiations.

We are seeking a Director/VP of Sales for the USA market to develop sales strategies, lead a team, drive revenue, and build customer relationships in the cybersecurity sector.

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.

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.

Own the production lifecycle for traditional ML and generative AI systems, including deployment pipelines, model registries, monitoring, retraining, governance, and incident response. Build reliable AWS-based infrastructure for LLM and agentic applications, establish observability and cost controls, and create operational standards, runbooks, and documentation. Partner with U.S.-based Data Science, Data Engineering, and Product teams while independently managing production workloads during India operating hours.

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.

Build governed Databricks Lakehouse foundations and productionize machine learning and GenAI solutions, including forecasting, anomaly detection, NLP, RAG, and predictive analytics. Develop reliable batch and streaming workflows, CI/CD, monitoring, governance, security, lineage, and semantic models. Collaborate with product, data, platform, and domain teams to deliver measurable customer value while meeting reliability, compliance, cost, and operational objectives.

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.

Develop, deploy, and maintain machine learning and AI solutions, including predictive models, NLP applications, chatbots, LLMs, and agentic AI systems. Build scalable data and ETL pipelines using cloud platforms, big data technologies, and databases. Apply TensorFlow, PyTorch, Hugging Face, and cloud AI services while creating data visualizations and optimizing analytics workflows.

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 an RPA team to design, develop, test, deploy, and maintain scalable automation bots (UiPath/AA/Blue Prism). Collaborate with stakeholders to assess processes, manage projects, mentor developers, troubleshoot bots, and report progress to senior management.

Design, build, and deploy conversational AI/chatbot solutions on the Kore.AI platform. Create intents, entities, dialog flows, integrate backend systems and REST APIs, and develop responsive user interfaces with ReactJS while collaborating with UI/UX designers.

Analyze e-commerce, finance, growth, and operational performance to deliver actionable insights. Build forecasting and predictive models, evaluate projects and KPIs, support stakeholder decision-making, and foster a data-driven culture to improve business performance across departments.

The AI Lead will design, develop, and implement AI solutions to enhance the SDLC stages, mentor teams, and ensure responsible AI practices.

As a Senior Impact Analyst, you will analyze sustainability challenges, design and manage interventions, and work closely with smallholder communities, emphasizing rigorous research and collaboration.

The Staff Engineer in Machine Learning will guide teams, solve client challenges, and enhance solutions leveraging their technical expertise.