Top Machine Learning Jobs in India

Leads a digital consultancy practice by partnering with sales, developing client relationships, overseeing strategic technology programs, and expanding innovative offerings. The Director provides thought leadership, manages engagement profitability and delivery quality, develops business cases and technical roadmaps, and mentors consultants, project managers, and architects. Responsibilities also include recruiting, performance management, client presentations, proposal development, and guiding complex enterprise solution implementations.

Leads the architecture, development, and deployment of scalable predictive machine learning and generative AI systems for fraud mitigation, risk scoring, and loss prevention. Builds RAG applications, autonomous agents, semantic search, model pipelines, APIs, microservices, and MLOps platforms using Python and cloud technologies. Partners with risk and compliance teams, ensures regulatory and explainability standards, mentors engineers, and drives technical roadmaps and innovation.

Lead the architecture, development, deployment, and operation of AI/ML solutions for identity and access security. Build scalable pipelines, inference services, monitoring, and MLOps capabilities using cloud platforms. Integrate anomaly detection and behavioral analytics into IAM, PAM, and secrets-management workflows. Partner with cybersecurity and engineering teams, establish applied AI security standards, influence technical roadmaps, and mentor junior engineers.

Develop and deploy machine-learning solutions for optical transceiver calibration, production testing, yield improvement, anomaly detection, and test optimization. Build production-grade data and MLOps pipelines, integrate ML services with test software and APIs, monitor model performance, and analyze manufacturing data. Collaborate with engineering and manufacturing teams, validate operational impact, document results, and mentor junior engineers.

Train and deploy small, task-specific ML models for realtime English conversational-skill applications. Create datasets and task-specific evaluations, improve internal SOTA, develop ASR and speech-feedback metrics, iterate experiments, ship production systems, and collaborate cross-functionally while helping hire as the team grows.

Build and maintain AI/ML applications, LLM-powered solutions, AI agents, agentic workflows, and Model Context Protocol integrations. Develop prompt, retrieval, tool-calling, and workflow automation systems; evaluate model quality, safety, and reliability; and support production deployment, monitoring, and continuous improvement. Collaborate with product, engineering, and business teams, while documenting architectures and implementation details.

Build and maintain scalable batch and real-time data pipelines for IoT and application data. Develop ETL/ELT processes, ingestion frameworks, data models, storage solutions, and datasets supporting analytics and AI workloads. Ensure data quality, reliability, security, and performance while monitoring production pipelines and troubleshooting issues. Collaborate with AI, backend, product, and platform teams, contribute to architecture discussions and code reviews, and apply data governance and modern software development practices.

Develop machine-learning and analytical solutions for loyalty programs, including segmentation, propensity, recommendation, uplift, optimization, experimentation, and causal-impact measurement. Translate business questions into actionable recommendations, establish success metrics, partner cross-functionally on production-ready solutions, and support loyalty data platforms and products. Ensure data quality, reproducibility, governance, and responsible customer-data use while communicating findings to technical and executive audiences.

Build and own production-grade machine learning and generative AI systems, including LLM applications, RAG pipelines, conversational AI, agentic workflows, personalization, recommendations, and memory systems. Develop retrieval and orchestration workflows, evaluation frameworks, scalable APIs, and backend integrations. Optimize deployed systems for quality, latency, cost, reliability, and scalability while supporting experimentation, monitoring, and continuous improvement.

Investigate AML alerts, enhanced monitoring reviews, and potentially suspicious activity requiring SAR/STR filings. Conduct screening and adverse media checks, support law enforcement and banking partner requests, ensure regulatory compliance, and manage time-sensitive workflows. Analyze transaction data and blockchain activity, identify financial crime trends, improve detection models and typology coverage, and collaborate with policy, legal, compliance, data, and technology teams. The role may also provide training and feedback to transaction monitoring analysts.

Design and implement measurement frameworks, statistical analyses, and ML solutions to extract insights from customer support and conversational data. Build scalable metrics, dashboards (Power BI), and collaborate with Data Engineering to enable analytics and AI-driven automation. Mentor junior data scientists and communicate findings to business stakeholders to improve customer journeys and operational outcomes.

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 technical pre-sales and customer solutioning for AI and process intelligence initiatives. Translate business challenges into AI use cases, build ROI cases, prototype LLM and agentic systems, and execute proof-of-value projects. Design secure, scalable systems using RAG, tools, guardrails, and enterprise integrations. Present solutions to executives, support implementation and adoption, and specialize in business domains or industries.

Conduct independent research on frontier AI evaluation and auditing. Design rigorous evaluations, audit methods, and reproducible experimental pipelines; analyze model capabilities, risks, robustness, and alignment-relevant behavior. Produce audit reports, recommendations, publications, tools, and presentations while collaborating with technical, policy, engineering, and standards teams. The role requires careful handling of confidential information and may involve pilot audits with frontier AI companies.

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.

Develop and validate process, structure, and materials models using numerical methods and machine learning to enable predictive and prescriptive analytics for memory development and manufacturing. Implement and code multi-physics and process models, analyze results, present findings, and collaborate with cross-functional teams to drive decision support and automation.

Owns sales reporting, dashboards, forecasting, pipeline analytics, and advanced data science solutions. Develops predictive models, AI-enabled insights, scoring, segmentation, and automation to improve revenue performance. Partners with Sales, Finance, and Operations, enhances data quality and governance, translates complex analyses into business recommendations, and mentors analysts.

Lead targeted, end-to-end recruitment for niche Data, AI, Machine Learning, and Data Science roles. Responsibilities include technical headhunting, passive candidate engagement, talent mapping, digital sourcing, market intelligence, stakeholder partnership with technology executives, candidate management, and offer negotiation. The role requires strong technical recruiting expertise, familiarity with modern data and cloud technologies, advanced search capabilities, and the ability to distinguish specialized technical skill sets.

Supports commercial growth through business analysis, reporting, dashboards, performance monitoring, leadership presentations, and ad hoc data support. Applies predictive and prescriptive analytics, AI, and machine learning to identify insights, automate workflows, and improve decision-making. Partners with technology teams on AI use cases, prepares data for modeling, monitors model performance, and supports responsible AI governance, explainability, and bias awareness.

Design, train, fine-tune, validate, and optimize machine learning and deep learning models for ADAS and automotive validation. Build reproducible end-to-end pipelines for large-scale vehicle and sensor datasets, including data acquisition, labeling, preprocessing, feature engineering, evaluation, and quality analysis. Develop distributed training workflows across cloud and HPC environments, investigate model failures, support vehicle testing and data collection, and collaborate with algorithm, systems, and validation teams on deployment readiness and robustness.

Designs, develops, deploys, and supports Tungsten TotalAgility solutions for intelligent document processing and business process automation. Responsibilities include configuring document classification, extraction, OCR, workflows, forms, queues, and business rules; developing integrations, scripts, and connectors; troubleshooting production issues; supporting testing and releases; and collaborating with stakeholders. The role also contributes to AI, machine learning, and automation initiatives.

Conduct wind turbine testing and measurement services, including structural loads, power performance, electrical characteristics, Lidar verification, and acoustics. Install, operate, maintain, and manage measurement equipment; analyze large datasets; develop statistical models and data tools; and report findings. The role also includes project and customer coordination, workshop management, service improvements, innovation and R&D participation, mentoring, technical publications, and travel, including physically demanding turbine and met-mast work.

Own the vision, strategy, roadmap, backlog, and delivery of analytical, machine learning, and GenAI products. Translate business needs into requirements, lead Agile ceremonies, coordinate cross-functional teams, and guide products from discovery through production and adoption. Partner with data science, engineering, architecture, security, governance, and business stakeholders. Define success metrics, monitor performance and adoption, communicate progress and risks, and ensure responsible AI, privacy, security, and business-value considerations.

Manages a team of residential mortgage underwriters and QC analysts, overseeing loan underwriting, post-closing quality control, compliance, escalations, staffing, training, and performance. Reviews complex VA, FHA, and Conventional loans; ensures adherence to agency, investor, and regulatory guidelines; leads root-cause analysis and CAPA initiatives; tracks quality, turnaround, productivity, and defect metrics; and supports internal, investor, HUD, and VA audits.

Develop and productionize computer vision and machine learning models for large-scale geospatial and satellite imagery applications. Own projects end to end, including dataset creation, experimentation, model training, evaluation, deployment, and monitoring. Work with Python, PyTorch, distributed training infrastructure, and large data pipelines while collaborating with MLOps, platform, product, and geospatial teams.