Top Machine Learning Jobs in Hyderabad

Leads Salesforce and Oracle CPQ engineering teams and end-to-end Lead-to-Quote platform delivery. Oversees integrations, architecture, configuration, quoting workflows, release governance, SOX controls, and operational KPIs. Partners with Sales, Finance, Product, and Customer Success to improve deal execution and automation. Champions generative AI, intelligent approval routing, predictive insights, automated testing, and developer productivity across the engineering organization.

Lead architecture, development, and operation of scalable backend systems and distributed cloud-native applications. Build data pipelines, streaming analytics, APIs, and production AI/ML workflows while improving performance, reliability, security, and operational excellence. Decompose legacy systems into microservices, own major initiatives end to end, establish engineering standards, mentor engineers, and collaborate with product, data science, and engineering teams.

Leads a team building and operating Windows Fundamentals backend services, telemetry platforms, data pipelines, metrics, and diagnostic systems. Owns technical strategy, architecture, reliability, security, observability, and operational excellence while using large-scale telemetry and statistical analysis to improve Windows health. Responsibilities include hiring, coaching, roadmap ownership, cross-team collaboration, incident response, and applying automation and AI-assisted analysis to engineering workflows.

Owns the Project Intake platform for JLL’s Design and Construction Project Controls Program. Responsibilities include resolving customer issues, managing the product backlog, developing features and APIs, maintaining platform reliability, building QuickSight dashboards, improving data quality, applying AI-enabled automation, analyzing operational trends, and communicating releases. The role requires software development, data visualization, ticket management, customer engagement, and continuous process improvement across global regions.

Owns the Project Intake platform across development, customer issue resolution, product backlog management, platform reliability, APIs, dashboards, data quality, AI-assisted automation, and release communications. The role develops features, manages deployments and integrations, analyzes intake performance, builds QuickSight dashboards, improves workflows, and communicates changes to stakeholders across global regions.

Leads engineering strategy, architecture, technology delivery, innovation, and high-performing teams across regional and country platforms. Oversees scalable cloud solutions, legacy modernization, CI/CD, test automation, SRE adoption, security, and technical excellence. Partners with business, data, project management, vendors, and executives to deliver measurable outcomes, while developing talent and leveraging AI and emerging technologies.

Lead full-chip floor planning, custom analog and mixed-signal layout, physical implementation, verification signoff, and tape-out for advanced memory and high-speed interface designs. Own DRC, LVS, ERC, EMIR, reliability, and manufacturability closure. Define scalable layout methodologies, drive AI-enabled design automation, lead global cross-functional teams, mentor engineers, and deliver advanced-node semiconductor products.

Work in a cross-functional team to develop, implement, and apply numerical and multi-physics models for materials, structures, and processes supporting memory development. Use scientific computing, computational materials methodologies, and ML techniques to analyze results, report findings, and collaborate on next steps. Position is temporary (up to 12 months).

Leads and scales Regeneron’s G&A Digital & Technology organization in Hyderabad. Oversees enterprise application development, integration, testing, release management, production support, and operational excellence across HR, Finance, Legal, Compliance, Analytics, AI, and other corporate functions. Builds global delivery capabilities through hiring, organizational design, talent development, governance, vendor management, and succession planning. Partners with senior business and technology leaders to establish roadmaps, improve reliability and quality, manage risk, and advance AI-enabled automation.

Partners with enterprise customers to understand requirements, design AI solution architectures, and guide production deployments. Builds integrations, prototypes, reusable tools, and technical assets while troubleshooting complex issues. Leads technical workshops, collaborates with Product and Engineering teams, and shares customer feedback to improve the platform. The role combines software engineering, customer engagement, AI deployment, and scalable solution development.

Design and deploy scalable AI solutions for enterprise customers. Build integrations, prototypes, reusable tools, and production-grade applications; lead technical workshops; troubleshoot complex issues; document best practices; and collaborate with Product and Engineering teams to improve the platform based on customer feedback.

Lead a software engineering team developing Windows device optimizations across hardware, firmware, operating system, services, and applications. Set technical direction and roadmap, guide complex performance, reliability, debugging, power, and telemetry initiatives, and deliver reliable solutions at scale. Hire, coach, and retain engineers while collaborating with Windows teams, OEMs, silicon vendors, hardware partners, and senior stakeholders.

Lead technical vision and architecture for large-scale, low-latency data systems; contribute hands-on to core code and production support; drive cross-team alignment; mentor engineers; refine data pipelines and CI/CD; apply AI tools to improve workflows; collaborate with Ads and Bing to integrate shared infrastructure and deliver reliable, scalable platforms.

Leads the engineering organization responsible for Tide’s KYX onboarding, continuous due diligence, identity and access, risk scoring, and machine learning capabilities. Owns engineering strategy, distributed team leadership, model lifecycle management, agentic AI deployment, regulated workflow governance, and global platform execution. The role partners with operations, policy, risk, compliance, product, and regulators to improve onboarding conversion, due diligence quality, automation, and cost per member.

Develop and execute verification and validation strategies for embedded software, power-system protection and control products, and industrial communication protocols. Build Python-based automated test frameworks, simulators, and AI-assisted testing agents; perform interoperability, integration, regression, performance, and fault-injection testing. Analyze logs and network traces, troubleshoot firmware and system issues, and conduct root-cause analysis across relays, IEDs, RTUs, SCADA systems, and substations. Maintain CI/CT pipelines and ensure AI-driven testing remains traceable, explainable, repeatable, and human-validated.

Develop and ship Yahoo Mail mobile features for Android, owning projects from technical design through deployment, monitoring, and improvement. Build scalable solutions using Kotlin, Java, Android frameworks, Jetpack Compose, and React Native; integrate APIs; address performance, reliability, and usability challenges; conduct code reviews; collaborate cross-functionally; mentor teammates; and use AI development tools to improve engineering productivity while maintaining quality and security.

Lead Tide’s engineering organization for fraud, financial crime, and ongoing monitoring platforms. Set strategy across backend, frontend, data science, ML, and analytics engineering; own decisioning platforms and model lifecycles; scale agentic AI in regulated workflows; and align risk, compliance, operations, payments, and technology teams. The role is accountable for improving fraud detection, reducing losses and monitoring costs, increasing automation, and building globally scalable platforms that meet regulatory standards.

Build scalable, low-latency backend APIs, event-driven services, integration layers, and microservices supporting personalization and recommendation experiences. Partner with AI/ML and data engineers to deploy models, expose AI services, and develop React applications. Improve security, observability, reliability, performance, scalability, and operational efficiency while using AI-assisted engineering tools to enhance delivery and code quality.

Leads enterprise architecture for scalable, multi-tenant SaaS systems and cloud-native platforms. Owns AWS architecture, distributed data pipelines, cost optimization, security, governance, and architectural standards. Drives GenAI and machine learning adoption across the software development lifecycle, builds self-service capabilities, guides engineering teams, conducts prototypes, and leads architecture reviews. Requires deep hands-on cloud, distributed systems, coding, infrastructure automation, AI/ML, and strategic technology leadership experience.

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.

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.

Designs and documents scalable enterprise solutions, leads project architecture, guides engineering teams, and ensures integration, performance, quality, and compliance with enterprise standards. Collaborates across product, strategy, engineering, and architecture teams; evaluates SaaS vendors; contributes to technology roadmaps and reusable architecture patterns; and drives responsible AI and machine learning adoption within the domain.

Lead technical direction and delivery for a core NIRA backend domain: design and ship high-volume web APIs, own architecture for distributed and queue-based systems, drive complex initiatives, mentor engineers, lead incident response, champion AI dev tools, and align cross-functionally to simplify systems and influence roadmap.

Develop and maintain scalable Python backend applications using FastAPI, Django, APIs, microservices, databases, asynchronous processing, and event-driven architectures. Design efficient solutions, optimize performance, write automated tests, implement secure and maintainable code, and contribute to CI/CD deployments. Collaborate with product and engineering teams, participate in requirements gathering, analyze risks, estimate work, improve coding standards, and guide team members.

Lead a team to develop and apply next-generation defect detection equipment and processes, accelerate technology transfer, mentor staff, analyze experiments and defects, build detection techniques, manage cross-functional projects, define program health metrics, and collaborate globally to improve process yield. Data analysis, ML, and statistical modeling expertise is an advantage.