Top Machine Learning Jobs in Hyderabad

Develop and implement numerical and computational models (structure, materials, process) to support DRAM and NAND node development. Collaborate with process and product teams, create modeling tools and algorithms, analyze results, and present insights to engineering teams and leaders for silicon implementation.

Develop and implement smart manufacturing and process control solutions for semiconductor assembly. Responsibilities include data analysis, process modeling, machine learning, closed-loop Run-to-Run control, system integration, requirements definition, technical support, mentorship, and training. The role collaborates with process teams to improve manufacturing capability, quality, and efficiency, while supporting network-wide implementation and AI-enabled predictive systems.

Develop scalable, secure, and maintainable cloud observability services using Golang. Build systems that ingest logs, traces, and metrics; create APIs for analytics; optimize performance; and integrate front-end features. Collaborate with DevOps and infrastructure teams on deployment and monitoring. Responsibilities span requirements analysis, design, development, testing, deployment, support, and maintenance. The role requires experience with Go tooling, Docker, Kubernetes, microservices, React, version control, and continuous integration.

Develop scalable, robust cloud observability services in Golang. Build systems that ingest logs, traces, and metrics; create analytics APIs; optimize performance; integrate front-end components; and support production deployment with DevOps teams. Responsibilities span requirements analysis, architecture, development, testing, deployment, maintenance, and secure solution design. The role requires strong Go expertise, containerization, orchestration, microservices, software testing, version control, and continuous integration experience.

Develop and customize mechanical design automation solutions for aerospace products, improving design cycle times and execution quality. Create template-based designs, product-level automations, CAD customizations, parametrized models, and drafting solutions using NX and Creo. Integrate Teamcenter and third-party applications, develop customizations, support analysis and simulation, and drive design improvements. Collaborate independently and cross-functionally while contributing to customer-focused design solutions, intellectual property, and process enhancements.

Develop centralized semiconductor quality screening and lot-disposition systems, assess wafer quality and reliability risks, analyze manufacturing data, and create statistical monitoring and automation solutions. The role supports defect containment, CAPA, global quality standardization, dashboards, AI and machine-learning initiatives, audits, and continuous improvement across Micron’s worldwide wafer-fabrication network.

Lead the design, development, and maintenance of scalable .NET microservices across Azure and AWS. Establish CI/CD, automated testing, infrastructure as code, and cloud optimization practices. Diagnose application issues, improve scalability and availability, and provide technical leadership through architecture, code reviews, design documentation, mentoring, and proof-of-concept development. Build solutions using Kubernetes, Cosmos DB, Azure services, modern front-end frameworks, AI tools, and RESTful APIs.

Manage verification for complex DRAM design projects, develop methodologies, lead teams, provide technical advice, and enhance AI-driven verification processes.

Develops and analyzes mechanical and thermal systems through dynamic and steady-state simulation. Writes system and simulation requirements, contributes to architecture, integration, controller design, and real-time measurement and control. Uses MATLAB, Simulink, and Simscape to model aerospace products, including valves, heat exchangers, air conditioning, and refrigeration systems. Collaborates globally, supports R&D and new product development, and applies analytical problem-solving to conceptualize and validate simulation models.

Leads a semiconductor RDA team focused on defect detection, process anomaly identification, inspection technology development, data analysis, and continuous improvement for NAND technology development. Partners with process integration, data science, yield analysis, suppliers, and global manufacturing teams to develop inspection roadmaps, improve detection techniques, manage projects, establish program metrics, and transfer best-known methods across sites. Mentors engineers and drives root-cause analysis, innovation, and technical problem solving.

Monitor inline defectivity, analyze process and defect data, investigate anomalies, and drive corrective actions and continuous improvement in semiconductor manufacturing. The role uses inspection and metrology tools, supports experimentation and baseline health monitoring, collaborates with global manufacturing and yield teams, and helps transfer technologies into production while improving process quality and yield.

Lead Windows device fundamentals engineering, defining strategy and roadmaps for reliability, compatibility, performance, battery life, and sustainability. Manage complex cross-stack initiatives spanning hardware, firmware, operating systems, services, and applications. Use telemetry, experimentation, debugging, and statistical analysis to guide decisions, while recruiting, coaching, and retaining engineers and partnering with OEMs, silicon vendors, and Windows teams.

Leads global commercial engineering strategy and the Hyderabad technology center for pharmaceutical commercialization platforms. Oversees software, platform, cloud, data, AI, integration, and quality engineering teams; drives secure, reliable, scalable delivery across CRM, customer engagement, marketing, analytics, and field-facing systems. Establishes architecture and engineering standards, develops technical leadership, manages workforce planning and budgets, insources capabilities, reduces technical debt, and partners with senior business leaders to deliver measurable commercial outcomes.

Designs, builds, scales, and operates cloud-native software platforms for deploying and securing AI agents across Microsoft Cloud. Responsibilities include coding, debugging, optimization, system design, dependency management, reliability engineering, monitoring, incident response, and cross-functional collaboration. The role requires C++ or C# development experience, familiarity with big data, ML, NLP, search, Azure, Microsoft Entra, and Microsoft 365, plus security practices such as threat analysis and penetration testing.

Designs, builds, scales, and maintains cloud-native AI agent platform services across Azure, Microsoft Entra, and Microsoft 365. Develops and optimizes C++ or C# code, collaborates with stakeholders, creates technical designs, supports releases, monitors production systems, and improves reliability, observability, security, and performance. The role involves big data, machine learning, NLP, search, threat analysis, penetration testing, customer engagement, and cross-functional collaboration.

Design, build, and configure Python applications aligned with business requirements. Lead software development, make team decisions, collaborate across teams, solve technical problems, mentor junior engineers, and ensure application quality through testing, debugging, optimization, and adherence to software development best practices.

Build and maintain production-ready Java full-stack software using AI-native engineering practices. Responsibilities include designing scalable web services, implementing and testing software, conducting architecture and code reviews, improving system quality, debugging distributed systems, supporting cloud SaaS infrastructure, mentoring developers, and collaborating cross-functionally. The role requires expertise in Java, cloud platforms, DevOps, CI/CD, testing, databases, and software architecture, with the ability to translate AI and LLM innovations into business impact.

Build and maintain production-ready Java full-stack software using AI-native engineering practices. Responsibilities include designing scalable web services, implementing and testing software, improving code quality, conducting architecture and code reviews, debugging distributed systems, supporting cloud SaaS infrastructure, and mentoring developers. The role leads technical direction, collaborates across functions, evaluates emerging technologies, and translates AI, automation, and LLM innovations into business and productivity improvements.

Build and ship production-ready software using AI throughout the engineering lifecycle. Lead architecture, design, implementation, testing, maintenance, and support of scalable Java-based web services and distributed systems. Drive cloud, DevOps, and AI modernization initiatives; improve code quality, security, performance, and operational practices. Collaborate across functions, conduct design and code reviews, mentor engineers, investigate emerging technologies, and translate AI innovations into business and productivity outcomes.

Leads the design, development, testing, deployment, and support of scalable Java full-stack software and distributed systems. Defines technical architecture, reviews requirements and code, improves system quality, mentors engineers, and guides cross-functional delivery. The role applies AI-native engineering practices, cloud infrastructure, DevOps, automation, LLMs, and modern software toolchains to build production-ready solutions and improve engineering productivity.

Build and ship production-ready software using AI-native engineering practices. Design, implement, test, maintain, and improve scalable Java full-stack applications and distributed systems. Lead architecture and code reviews, develop cloud-based SaaS solutions, improve quality and compliance, troubleshoot technical issues, mentor engineers, and collaborate with cross-functional teams. The role requires strong Java, cloud infrastructure, DevOps, testing, web services, database, and AI modernization experience.

Build and ship production-ready software using AI throughout the engineering lifecycle. Design, implement, test, maintain, and improve scalable Java full-stack applications and distributed cloud systems. Lead architecture and code reviews, troubleshoot technical issues, support CI/CD and DevOps practices, improve software quality, and mentor developers. Collaborate across teams, evaluate emerging technologies, and translate AI, automation, and LLM capabilities into business and productivity improvements.

Build, test, maintain, and enhance scalable Java full-stack software and distributed systems. Lead architecture, technical design, code reviews, cloud and DevOps initiatives, and quality improvements. Collaborate across teams, support customers, mentor developers, investigate emerging technologies, and apply AI-native practices, LLMs, automation, and modern engineering toolchains to improve software delivery and business outcomes.

Leads architecture, design, implementation, testing, maintenance, and support of scalable Java full-stack software and distributed systems. Develops cloud-based SaaS solutions using AWS or Azure, CI/CD, DevOps, automated testing, and AI-native engineering practices. Reviews code and designs, improves system quality, mentors developers, investigates new technologies, supports customers, and drives technical decisions across cross-functional teams. The role also requires expertise in large-scale web services, big data, security, and AI modernization initiatives.

Build and ship production-ready software using AI-native engineering practices. Design, implement, test, maintain, and improve scalable Java full-stack applications and web services. Lead architecture and code reviews, troubleshoot distributed systems, support CI/CD and cloud infrastructure, and ensure quality, security, and performance. The role also involves mentoring developers, collaborating across teams, evaluating new technologies, and translating AI, LLM, and automation capabilities into business and productivity improvements.