Senior Engineer Mechanical in Bengaluru

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software, and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers, and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary Reporting to the Validation leadership team, the Senior Execution and Quality Validation Engineer will be responsible for executing validation plans, developing automation solutions, and improving product quality across Graphcore silicon and platform technologies. Working closely with architecture, design, verification, firmware, software, systems engineering, and validation teams, the successful candidate will contribute to scalable validation methodologies, improve test coverage and execution efficiency, and help ensure products meet high standards of functionality, reliability, and performance before customer deployment. The role requires strong technical skills, attention to detail, and a passion for improving validation quality through effective execution, automation, and continuous improvement. The Team The Validation Execution and Quality team sits within the Validation organisation and is responsible for improving validation effectiveness, test execution efficiency, product quality, and release readiness across Graphcore silicon and platform products. The team develops validation methodologies, automation

About Us Graphcore is a globally recognised leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data centre hardware that provide the specialised processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Job Summary Working within the logical design team, the silicon logical design engineer is responsible for a wide range of logical design tasks. The team is responsible for delivering the Microarchitecture and RTL design to implement the chip architecture specification for Graphcore Silicon, working closely with other engineers within the Silicon team. The successful candidate will be responsible for helping the team deliver high quality micro-architecture and RTL for Graphcore chips, working within the logical design team and with the broader Silicon team to ensure we meet the company objectives for Silicon delivery. Responsibilities and Duties Integrate IP and subsystems into top-level SoC designs Develop and maintain build and configuration environments Perform synthesis, linting, CDC/RDC, and timing checks at the SoC level Support verification and physical design teams through clean interface hand-offs Debug and resolve integration-related issues across multiple hierarchies Contribute to the continuous improvement of integration flows and automation Producing high quality microarchitecture and other documentation Ensure good communication between sites to maintain consistent working practises Candidate Profile Essential skills: Logical design experience in relevant industry Experience range 4-8 years in Semiconductor Industry/Product development exposure. Be highly motivated, a self-starter, and a team player Ability to work across teams and debugging issues seen to find root caus

We are seeking a highly skilled and experienced Staff Network Site Reliability Engineer (SRE) to join our Enterprise Network Operations and SRE team. In this role, you will be pivotal in implementing our vision for a reliable and efficient network infrastructure. The ideal candidate is passionate about network operations and committed to enhancing the user experience. You'll have the opportunity to solve complex network challenges using hands-on debugging and by focusing on network automation, observability, documentation, and operational excellence. This is a critical position focused on ensuring user satisfaction and brilliance in network operations. What you'll be doing: Owning the operational aspect of the network infrastructure, ensuring its high availability and reliability, actively working on network incidents and service requests. Partnering with architecture and deployment teams to guarantee that new implementations are supportable and align with production standards. Advocating for and implementing automation to reduce toil and improve operational efficiency. Minimizing manual operational tasks to achieve and maintain Service Level Objectives (SLOs). Monitoring network performance, identifying areas for improvement, and collaborating with relevant teams to implement refinements. Proactively identifying and mitigating network risks to promote continuous improvement. Collaborating with domain experts across functions to resolve production issues swiftly and effectively, ensuring customer happiness. Conducting blameless postmortems and following through on Root Cause Analyses (RCAs). Discovering opportunities for operational improvements and teaming up with colleagues to devise solutions that enhance excellence and sustainability in network operations. Developing knowledge base articles for automa

We are looking for a highly motivated AI/ML Software Engineer to join the Enterprise Agentic AI Platform team within IT. You will work closely with Business Analysts, and Engineering teams to design, develop, and deploy enterprise AI solutions that improve productivity and automate business workflows across Engineering, Operations, and Manufacturing. What you'll be doing: Design, develop, and deploy Agentic AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI orchestration frameworks. Build scalable AI services and reusable components integrated with enterprise applications such as PLM, SAP, and other business systems. Collaborate with business and IT teams to translate business requirements into AI-driven solutions. Develop secure, scalable APIs and enterprise integrations to enable intelligent workflows and automation. Improve AI solution quality, performance, and reliability through prompt engineering, evaluation, and continuous optimization. Partner with cross-functional teams throughout the Software Development Lifecycle (SDLC), from solution design through deployment and production support. What we need to see: Bachelor's or Master's degree in Computer Science, Information Technology, AI/ML, or a related field. 6+ years of software engineering experience with strong proficiency in Python and backend application development. Hands-on experience with Generative AI, LLMs, RAG, AI agents, REST APIs, and cloud-native application development. Experience integrating enterprise applications and building scalable, production-ready software solutions. Strong analytical, problem-solving, communicatio

Job Details: Job Description: In this role, you'll build software capabilities to automate the build, test, and deployment of Intel's Process Design Kit (PDK). A PDK is a collection of artifacts representing Intel's semiconductor process, used by product designers to model, implement, and verify Intel's mobile, desktop, and server products before manufacturing. You'll be a member of the Design Technology Platform organization, working closely with teams in the United States, Bangalore, and Penang to build world-class DevOps infrastructure that shapes the future of deploying PDKs to silicon product development teams at Intel. Qualifications: Bachelor's or Master's degree in Computer Science, Computer Engineering, or another closely related field. 7-12 years of experience with a Bachelor's degree or Master's degree in software development and engineering. Excellent Python programming skills. Expert-level knowledge of pytest concepts. Expert-level experience with GitHub-based Jenkins CI/CD deployment, enablement, and debugging. Proven knowledge of Agile software engineering practices, IT environments, and DevOps principles and processes. Excellent debugging and problem-solving skills. Excellent written and verbal communication skills; ability to present complex issues with clarity to drive decisions. Must have hands-on experience with AI tools and demonstrated experience building AI agents/tools. Exposure to VLSI PDK domain is preferred. Strong team player with proven ability to collaborate effectively across cross-functional and geographically distributed teams. Job Type: Experienced Hire Shift: Shift 1

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Smartsheet is hiring a Senior Machine Learning Operations Engineer to architect our machine learning production lifecycle. Your mission is to maintain and deploy ML models to a scalable, reliable, and secure production environment. You will design and maintain the infrastructure, automation, and monitoring systems that ensure our AI products are high-performing and cost-effective. You will report to our Director, Analytics Engineering & Data Governance and work from our Bangalore, India office. You Will: Model and Pipeline Automation Automate the deployment and retraining of ML models, from training through to production inference, by building and managing complete CI/CD/CT (Continuous Training) pipelines, adhering to MLOps best practices. Build, fine-tune, or use pre-trained LLMs, deep learning models or traditional machine learning models. Evaluate and recommend AI or ML solutions for the product using any combination of vendor solutions and/or custom-built models. Governance & Compliance Implement model versioning, lineage tracking, and auditing to ensure compliance with security and ethical standards. Performance Monitoring Continuously monitor the health and performance of production machine learning models, proactively identifying and correcting model drift, staleness, and performance degradation. Incorporate user feedback for iterative improvements and manage necessary model retraining cycles. Cross-Functional Collaboration Act as the "glue" between Data Scientists (who build models

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Job Description/ Responsibilities: Designing, developing and maintaining stable and reliable AI/ML Ops platforms / pipelines Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time. Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production. Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow. Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data Technology Eva

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Senior AI/ML Ops Engineers who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform. You Will: Designing, Developing and overseeing the strategy and architecture of scalable and reliable AI/ML Ops platforms / pipelines Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time. Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Senior AI/ML Ops Engineers who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform. You Will: Designing, Developing and overseeing the strategy and architecture of scalable and reliable AI/ML Ops platforms / pipelines Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time. Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with

Job Title Senior Software Technologist I - C++ Job Description Software Engineer II Your Role: • Design, develop, test, and maintain software components and applications using modern C++, C# in a Windows-based environment. • Participate in the full software development lifecycle including requirements analysis, design, implementation, testing, debugging, and maintenance. • Develop and maintain software applications using Visual Studio and associated C++, C# development tools. • Work with Windows operating system fundamentals including processes, services, registry, file system, User Account Control (UAC), and application configuration. • Create, enhance, and troubleshoot software modules while adhering to coding standards, design guidelines, and software development best practices. • Utilize GitHub for source control management including branching strategies, commits, pull requests, merges, rebasing, and code reviews. • Support and troubleshoot CI/CD pipeline issues using GitHub Actions and participate in continuous integration activities. • Manage software dependencies and package management using NuGet and Conan. • Configure and maintain build systems using CMake and Visual Studio project configurations. • Develop and execute unit tests using Google Test (GTest) to ensure software quality and reliability. • Perform debugging, root cause analysis, and defect resolution for software issues identified during development, testing, and field support activities. • Participate in peer code reviews and contribute to software quality, maintainability, and technical excellence. • Collaborate effectively with Software Verification, Product Management, DevOps, Architecture, and cross-functional teams to deliver high-quality software solutions. • Create and maintain

About Mixpanel Mixpanel is the leading product intelligence and analytics platform, trusted by more than 29,000 companies to help understand how people use the products they build. By combining powerful analytics with AI that knows your business, Mixpanel helps teams see what’s working, diagnose what’s not, and decide what to build next. Learn more at mixpanel.com . About the Team The Customer Value Architect (CVA) team sits inside Mixpanel's Revenue organization and owns the connection between what customers buy and what they actually get out of Mixpanel. You'll work alongside an Account Executive (AE), who owns growth, new business, and expansion; a Renewal Manager (RM), who owns the commercial renewal; and a Delivery Engineer (DE), who owns technical implementation and data health — each with a clear lane, converging on the same outcome for the customer. At this level, you'll also help shape how the wider CVA team operates. About the Role This is not a build role, but real comfort with data is required. As a Senior Customer Value Architect, you are accountable for adoption, value realization, and account health across a portfolio of Mixpanel's existing customers — including the most structurally complex accounts, such as those going through a platform migration, re-implementation, or major workflow change, where the value motion and a genuine cross-functional program have to run in parallel. You own the value case and the adoption evidence that underpins both the Account Executive's expansion motion and the Renewal Manager's renewal, without ever owning pricing or the commercial negotiation yourself. You're also expected to extend your impact beyond your own accounts: mentoring, sharpening team playbooks, and representing the Customer Value Architect function in cross-functional account strategy. Responsibilities • Own the onboarding outcome and time-to-value for your accounts, including the most complex accounts in the book: take the handoff from the Account Exe

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Role Overview & Key Responsibilities This is a high-leverage leadership role that spans architecture, execution, and org-building, and will shape the direction of our AI / ML initiatives at Ema. We are seeking an AI / ML technical leader who can take a vision and build it. As a Principal ML Engineer at Ema, you will be a senior technical leader responsible for shaping the machine learning roadmap, architecting large-scale ML systems, driving innovation, and ensuring our mixture of expert models (LLM + SLM + Custom Model) is accurate and performant at scale. You will collaborate across teams (research, product, infra, data, etc.), mentor senior engineers, and influence strategy and execution at company-wide levels. Responsibilities Lead the technical direction of GenAI and agentic ML systems that power enterprise-grade AI agents — spanning reasoning, retrieval, tool use, and integrations across various SaaS products. Architect, design, and implement scalable production pipelines for model training, fine-tuning, retrieval (RAG), agent orchestration, and evaluation — ensuring robustness, latency efficiency, and continuous learning. Define and own the multi-year ML roadmap for GenA

Position Overview We are looking for a Software Engineer II to build and deliver scalable software solutions across our products. You will work on modern web applications and cloud-based services using Node.js, React, TypeScript, AWS, PostgreSQL, MSSQL, and Docker, while contributing to AI-enabled features and integrations. You will collaborate closely with other engineers, product managers, and cross-functional teams to develop reliable, maintainable, and production-ready solutions. This role provides an opportunity to work with modern AI technologies including Python, AWS Bedrock, MCP, RAG, and agentic AI workflows while developing strong expertise in cloud-native software engineering. What You'll Do Develop and maintain scalable backend services and APIs using Node.js, TypeScript, and JavaScript. Build responsive and maintainable frontend applications using React. Design and implement integrations with AWS services and contribute to cloud-native application development. Develop and maintain applications using PostgreSQL and MSSQL, including writing efficient queries and working with database schemas. Build, test, and deploy applications using Docker and modern CI/CD practices. Contribute to AI-enabled product features using Python, AWS Bedrock, RAG, MCP, and AI integration patterns. Work with the team to integrate LLM capabilities, APIs, tools, and data sources into production applications. Write clean, maintainable, and well-tested code following established engineering practices. Participate in code reviews, technical discussions, debugging, and production issue resolution. Develop unit and integration tests and contribute to improving application quality and reliability. Monitor application performance and troubleshoot issues across development and production environments. Collaborate with senior engineers and architects to implement technical solutions aligned with product and engineering requirements. Stay current with emerging technologies, particularly in

Role Overview You’ll be the Principal Software Engineer driving the next generation of a large-scale enterprise SaaS platform. In this role, you combine deep hands-on engineering with high-impact technical leadership, shaping how cloud-native and AI-enabled products are designed and built. You’ll design and deliver secure, scalable, serverless systems on AWS using TypeScript and Node.js, modernize critical platform components, and set the technical direction for multiple teams. You’ll also lead how AI capabilities are integrated across the product ecosystem, ensuring they are transparent, observable, and compliant. If you enjoy system-level thinking, complex distributed architectures, and mentoring senior engineers while still staying close to the code, this role gives you company-wide impact and the opportunity to define the long-term technical vision. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead the architecture and delivery of secure, scalable, serverless applications on AWS using TypeScript/Node.js. Define and evolve the platform architecture, driving modernization, performance, resilience, and maintainability. Design and operate distributed, event-driven systems using services like Lambda, DynamoDB, Aurora, S3, and EventBridge. Shape and implement AI-enabled solutions, embedding governance, observability, and responsible AI practices into the platform. Own Infrastructure as Code (e.g., Terraform, AWS CDK, CloudFormation) to reliably provision and manage cloud infrastructure. Mentor senior engineers, influence technical decisions across teams, and clearly communicate complex concepts to diverse stakeholders. These are the essentials you’ll need to get an interview Extensive experience (typically 12+ years) building secure, production-grade software systems. Proven track record architecting and delivering cloud-native, serverless applications on AWS. Strong expertise in Node.js, TypeScript, REST API design, and at leas

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. About The Team Global Innovation Center SE team (Presales): Over the last 3 years, Okta in Bangalore has fueled our growth around the world. The Global Innovation Center Presales team has been a crucial part of this growth. We are expanding this team made up of exceptional high-performing individuals. In this team, you will focus on being a customer-facing solution engineer crafting identity and security solutions for commercial segments in the US, ranging from digitally native start-ups to scaling SMBs. As a Solutions Engineer you will: Support our customers along their sales journey by showing them the value of the Okta technology through live demonstrations and sales presentations. Sell directly to IT managers, developers, product managers, and occasionally more senior executives across various industries.. Have a focus on our Okta Workforce Identity solutions and be able to model how this solution will support their current architecture requirements and use cases Execute well-defined, outcome-focused POCs Maintain a broad and deep technical understanding of the Okta product line and the underlying technologies and protocols Occasionally participate in local and regional events evangelising Okta as a presenter and an attendee. We are looking for: Ability to work in the EST Time Zone A minimum of 5 years of working experience in IAM or a related SaaS field as a pre-sales engineer. Expertise or hands-on experience in IAM, single sign-on, multi-factor authe