Top Machine Learning Jobs in Pune

Develop statistically effective algorithms and apply machine learning, deep learning, and generative AI techniques to high-dimensional problems. Use hypothesis testing, data mining, and big-data tools to identify trends, build predictive models and recommender systems, collaborate with clients and stakeholders, and evaluate emerging datasets and technologies for scalable analytical solutions.

The Engineering Lead will design and implement technical features, work on ML pipelines, and mentor engineers while ensuring high-quality deliverables. This role requires collaborating with teams and managing the ML lifecycle for business value.

The Director of Data Platform Engineering will oversee the data infrastructure, manage relational databases, lead AI integration, and ensure data governance while fostering a collaborative team environment.

Design and implement technical features, collaborate with clients, write production-ready code, ensure quality deliverables, mentor team members, and implement ML models on large scale.

Perform static and dynamic malware analysis, develop detections and protections, analyze IOCs, validate AI/ML outputs, build automation tools, and publish threat research.

Manage and grow a team responsible for observability, monitoring, and integrations across monetization systems. Improve reliability and data quality for billing, provisioning, subscriptions, and revenue-impacting workflows; define telemetry and integration strategies; implement anomaly detection and incident management; and partner with cross-functional stakeholders to ensure reliable customer and financial workflows.

Design and own end-to-end solution architectures, translate requirements into technical designs, evaluate technologies, define integrations, guide development and DevOps teams, conduct reviews and POCs, support pre-sales, and ensure compliance with ISO standards.

Drive sales of CCTech digital transformation solutions to AEC, construction, and infrastructure clients. Prospect and manage pipeline, conduct discovery and solution positioning, support pre-sales workshops and proposals, collaborate with engineering teams, and develop strategic accounts focused on BIM, digital twin, automation, analytics, and enterprise integrations.

Lead data stewardship for CDD/financial crime data: investigate data quality, lineage, and controls; design ETL pipelines; apply advanced analytics and ML to large datasets; build dashboards and automated reports; translate insights into actionable business and compliance recommendations; advise stakeholders and support governance, risk mitigation, and regulatory readiness.

Partner with business units to implement data and records governance, ensure data quality and lineage, monitor metrics, drive remediation and controls, support regulatory reporting, and deliver data-driven improvements across BAU and change programs.

Validate and test models across credit risk, marketing, fraud, and account management; use GCP to automate workflows; execute AI validation projects; collaborate cross-functionally; contribute to AI/model risk management policies and maintain regulatory best practices.

Advise clients on developing and implementing data governance strategies. Design policies, frameworks, and practices for data quality, privacy, metadata management, and security. Deliver governance projects, build capability with frameworks and accelerators, and promote governance awareness across stakeholders and committees.

The Solution Architect will design, develop and implement cloud-native platforms for fraud detection, balancing technology risks and business needs, while collaborating with stakeholders and ensuring compliance with governance processes.

Lead data architecture, governance and pipelines for HR transformation programs; perform advanced analytics and ML-driven insights; design dashboards and automate reporting; advise stakeholders, manage data quality, lineage, migration, risk and controls, and drive strategic improvements.

Perform data quality investigations, build and automate data pipelines, apply advanced analytics and ML, create dashboards and reports, and translate findings into actionable business recommendations while improving governance, lineage, and controls across HR transformation programmes.

As an ML Engineer, you will design, experiment, and deploy AI/ML models, evaluate their performance, and leverage Python and SQL.

Analyze and model customer data using classical ML and NLP techniques, select algorithms, perform data wrangling and visualization, deploy models on cloud/big-data platforms, and communicate technical findings to non-technical stakeholders.

Assess and test the bank's internal control framework, identify and investigate control weaknesses, document findings, recommend remediation, and report to stakeholders. Execute control reviews aligned to policies and the Barclays Controls Framework, collaborate with business stakeholders, and apply data analytics and Python tooling to support control activities and automation.

Design, develop and deliver scalable, secure software and large-scale automations (primarily UiPath). Collaborate with product, design, and engineering teams, lead or mentor mid-size technical teams, perform code reviews, enforce secure coding and unit testing, integrate REST/SOAP/web services, manage versioning and releases, and support infrastructure including VMs, credential vaults and Active Directory.

Lead design and implementation of ML tools for scenario classification, anomaly detection, sensor data quality, behavior analytics, and automated reporting. Build scalable pipelines and automated data curation for camera, radar, and LiDAR; create SIL/HIL replay interfaces, ground-truthing and annotation tools, and offline benchmarking. Integrate ML modules into simulation, HIL/SIL, and CI/CD ecosystems, implement reproducible workflows (Docker, CI/CD, artifact versioning, automated tests), monitor model/data quality and mentor junior engineers while collaborating with verification and perception teams.

Lead design and implementation of ServiceNow ITOM Event Management and Dynatrace observability to reduce alert noise, automate incident correlation and remediation, implement observability-as-code via APIs/CI-CD/Terraform, leverage AI/ML for root-cause and predictive monitoring, and track KPIs like MTTR and alert reduction.

Design, develop, and deploy AI/ML solutions for marketing, pricing, and customer insights. Build predictive models, perform feature engineering and statistical analysis, create scalable model APIs, ensure data quality and governance, collaborate with IT and stakeholders, and support the full AI lifecycle including deployment, monitoring, and model performance reporting.

Lead requirements gathering, process analysis, and documentation for Legal IT systems. Support design, testing, training, stakeholder communication, and project delivery. Identify automation/AI opportunities and monitor KPIs to improve contract lifecycle efficiency and compliance.

Lead a Pune-based analytics team to deliver and govern finance BI reporting and AI/ML analytics. Manage intake, prioritize initiatives, build standardized dashboards and KPIs, ensure data governance and model lifecycle practices, champion ML/LLM automation, reduce manual work, and drive decision-ready insights for global finance stakeholders.

Develop, validate, and optimize electrical models and HIL simulations (OPAL-RT) for power management products using Matlab/Simulink. Build reusable HIL/SIL solutions, validate against prototypes, support product design teams and customers, implement control algorithms (C/C++), document results, and improve simulation capabilities.