Performance Fitter in India

Location Details: At GoDaddy the future of work looks different for each team. Some teams work in the office full-time, others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely. Hybrid: This is a hybrid position. You’ll divide your time between working remotely from your home and an office, so you should live within commuting distance. Hybrid teams may work in-office as much as a few times a week or as little as once a month or quarter, as decided by leadership. The hiring manager can share more about what hybrid work might look like for this team. Join our team Join a high-impact team supporting GoDaddy’s global Salesforce ecosystem. You will play a key role in delivering scalable CRM solutions while partnering with engineering, product, and operations teams. This position offers the opportunity to work on complex challenges, mentor others, and continuously improve platform performance and user experience. What you'll get to do... Manage and support GoDaddy’s Salesforce CRM platform Partner with engineering, product, and operations teams to deliver solutions Solve complex technical issues and improve system performance Support onboarding of teams to Salesforce Mentor junior team members and share best practices Configure users, roles, permissions, objects, and layouts Build reports, dashboards, and automation (Flows) Manage data quality, imports/exports, and system monitoring Provide user support, training, and documentation Develop solutions using Apex and Lightning Web Components (LWC)Build integrations using REST/SOAP APIs Automate processes using Flows, Process Builder, and Triggers Customise applications to meet business requirements Support testing, code reviews, and deployments Your experience should include... 3+ years of experience as a Salesforce Administrator and Release Engineer Experience working with Sales, Service, and Experience Cloud Strong knowledge of Salesforce configurati

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. As a Quality Analyst, you will support the Quality Manager and the broader team in maintaining quality controls, executing calibration reviews, and ensuring smooth auditing operations with our vendor partners. You will play a crucial role in validating audit accuracy, analysing performance trends, and identifying grading discrepancies, helping to safeguard platform integrity and streamline vendor quality processes. You Will: Assist in executing regular quality compliance reviews and operational audits to ensure vendors adhere to established grading rubrics. Conduct daily audits of vendor customer service and moderation audits to verify accuracy and policy alignment. Gather, format, and maintain quality performance metrics and audit data to highlight recurring errors or vendor grading drift. Support the Lead in coordinating with Moderation, Customer Support, and Global Scaled Operations teams to resolve quality disputes. Participate in calibration sessions to ensure consistent interpretation of trust and safety policies across all vendor sites. Help test and implement new quality automation tools or auditing platforms introduced by the technical and leadership teams. You Have: 3-5 years of e

We are looking for a talented Senior System Software Engineer to help build NVIDIA Halos, our full-stack safety critical platform for physical AI: autonomous vehicles, humanoids, industrial robots, and intelligent machines that sense, decide, and act in the real world. This role is equally grounded in ISO 26262 functional safety engineering and embedded systems, rich operating systems, virtualization, accelerated computing. If you have a good understanding of System Software development on Real Time OS (RTOS), ARM architecture, Virtualization, and experience with ISO 26262 safety lifecycle, we want to hear from you! We are a leading artificial intelligence computing company and are paving the way with innovations in gaming, visualization, supercomputing, and autonomous vehicle and robotics safety platforms. NVIDIA gives automakers, tier-1 suppliers, automotive research institutions, and startups the power and flexibility to develop and deploy breakthrough artificial intelligence systems for autonomous vehicles. Our unified computing architecture makes it possible to train deep neural networks in the data center on the NVIDIA DGX™, and then seamlessly run them on NVIDIA's Halos platform inside the vehicle. Leading vehicle manufacturers, tier 1 suppliers, mapping and simulation companies, software and sensor providers, and startups around the world are developing on the NVIDIA Halos® platform to deliver the best solutions for the new world of mobility. As a System Software Engineer, you will get an opportunity to work on high-performance NVIDIA edge AI platforms running complex mixed-criticality software stacks across QNX, Linux, hypervisors, safety partitions, accelerators, and real-time AI workloads, and work alongside industry experts in diverse teams and projects. <

At Franklin Templeton, we believe success is built through powerful partnerships. As a forward‑thinking asset manager, we build dynamic relationships with clients, understand their goals, and navigate complex markets together. We leverage cutting‑edge strategies and deep insights to unlock opportunities for long‑term wealth creation. Our talented, global teams bring expertise that is both broad and unique. From our welcoming, inclusive, and supportive culture to our globally diverse business, we offer opportunities not only to help you reach your potential, but also to contribute to our clients’ success. About the Department: The FTT – Operations group develops and supports products that power the daily operations of the Middle and Back Office. The team collaborates closely across functions to deliver reliable, scalable solutions that drive business efficiency. Joining this group means working in a dynamic, technically driven environment where innovation and teamwork are valued, and your contributions directly impact operational success. How You Will Add Value? Core Responsibilities: You will design and build software solutions with product owners to meet business needs. You will manage product backlogs and prioritize development tasks. You will participate in sprint and release planning activities. You will develop, test, and maintain high-quality code. You will conduct code reviews and ensure adherence to standards. You will support deployments and optimize performance. You will build full-stack applications across services, APIs, and infrastructure. You will collaborate with analysts

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

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. With data and analytics at the center of our people strategy, we are seeking a People Analytics Consultant to join our People Analytics team. In this role, you will support the delivery of workforce insights across the employee lifecycle by analyzing people data, developing dashboards, and identifying trends that help inform business decisions. You will partner with stakeholders across HR, Talent Acquisition, Finance, IT, and Legal to deliver accurate, timely, and actionable analytics. This role is ideal for an analytical professional who enjoys working with data, solving business problems, and applying modern analytics techniques to improve workforce outcomes. Essential Duties and Responsibilities People Analytics & Reporting Analyze employee lifecycle data, including hiring, onboarding, engagement, performance, promotions, compensation, headcount, and attrition. Develop and maintain dashboards, scorecards, and recurring reports that provide meaningful workforce insights. Respond to ad hoc analytics requests and translate business questions into data-driven recommendations. Partner with People Business Partners and HR Centers of Excellence to support workforce planning, talent reviews, and organizational health discussions. Validate data accuracy and collaborate with HR Technology and data teams to improve data quality and reporting consistency. Present findings through clear visualizations and concise business summaries. Workforce Analytics Perform st

Job Details: Job Description: We are seeking an experienced Analog Design and Infrastructure DA Manager to lead the development, deployment, and governance of analog/mixed-signal design environments and CAD infrastructure. This role owns EDA tool ecosystems, PDK integration, compute infrastructure, design data governance, and tapeout manifest management to ensure high productivity, reproducibility, and audit readiness across silicon programs..The ideal candidate combines deep analog/mixed-signal design flow and e-test structure development expertise with strong infrastructure leadership and disciplined configuration/data management practices. Key Responsibilities-1. Analog Design Environment and Flow Management-Own and maintain analog and mixed-signal design flows using platforms such as Virtuoso ,Develop and maintain schematic, layout, verification, and extraction flows (LVS, DRC).Support simulation environments including HSPICE, Corner analysis.Drive automation and methodology improvements to reduce turnaround time and increase design robustness. 2. Infrastructure and Compute Management Oversee Linux-based DA infrastructure including compute farms, storage systems, and license servers (FlexLM). Manage LSF/grid environments and job scheduling systems. Ensure scalability, system monitoring, high availability, and performance optimization. Partner with IT on hardware lifecycle planning, cloud integration, and disaster recovery. Maintain secure, access-controlled design environments aligned with IP protection policies. 3. Design Data, Manifest and Configuration Management Design Data Governance Manage large-scale analog design libraries, hierarchical database structures, and technology libraries. Define backup, archival, and retention policies for tapeout-critical data. Implement data integrity validation and corruption prevention controls. Oversee distributed stor

NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for more than 25 years. Today, we are tapping into the unlimited potential of AI to define the next era of computing. As an NVIDIAN, you will address challenges spanning architecture, silicon, firmware, software, and production — and excellent judgment matters as much as technical depth! We are the Silicon Power Team within the Silicon Co-Design Group. We architect and deliver groundbreaking solutions for productizing NVIDIA's chips across consumer, professional, server, embedded, mobile, and automotive markets. Silicon characterization, correlation to arch and design expectations, product spec finalization, and productization techniques and infrastructure are our day-to-day work — always on the bleeding edge of the industry. Small decisions here have outsized impact on performance, efficiency, reliability, bring-up speed, and ultimately what the product delivers in the field. We are hiring a Senior Silicon Power Engineer to own power-feature productization on a flagship silicon program. This is not a coordination role, and it is not a compliance role — it is the seat where power features either work at scale or become the reason a program slips. The two highest-leverage problems in this seat: Close the hardest multi-functional power failures before they gate a program. Take ambiguous, cross-boundary issues across architecture, firmware, validation, and platform to root-cause closure — with productized fixes and reusable methodology the next program can inherit. Build AI-enabled characterization as a real capability, not a demo. Every bring-up generates terabytes of characterization, shmoo, and telemetry data. Deploy AI workflows for data analysis, metric extraction, trend detection, and cross-bring-up correlation — with the guardrails and validation discipline to make them trustworthy enough to gate production decisions! <

We are seeking a Senior Software Engineer with strong infrastructure expertise to design, build, and operate the next generation of our enterprise Observability, Automation, and AI-driven Reliability Platform. This role will build highly scalable distributed systems and platform services spanning Storage, Compute, Network, VMware, OpenShift, and bare-metal infrastructure. The engineer will help transform infrastructure operations from reactive monitoring and manual remediation to proactive, predictive, and AI-driven autonomous operations. What You Will Be Doing: Design, build, and operate distributed software platforms for enterprise observability, telemetry, automation, and infrastructure reliability at large scale. Develop reusable platform services, APIs, automation frameworks, and control planes that enable self-service, reduce operational toil, and automate infrastructure operations across multiple engineering teams. Build scalable telemetry and event-processing systems spanning metrics, logs, traces, events, topology, and alerts, with the performance and efficiency to process billions of infrastructure signals. Build intelligent and AI-native reliability capabilities, including agentic workflows for anomaly detection, forecasting, root-cause analysis, automated debugging, and closed-loop remediation. Drive technical architecture and engineering direction across Storage, Compute, Network, and Platform domains, solving complex and ambiguous problems that span multiple teams. Engineer for production at scale, with strong focus on software quality, scalability, security, performance, observability, maintainability, and operational readiness. Provide technical leadership and mentorship, influence engineerin

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

At Franklin Templeton, we believe success is built through powerful partnerships. As a forward‑thinking asset manager, we build dynamic relationships with clients, understand their goals, and navigate complex markets together. We leverage cutting‑edge strategies and deep insights to unlock opportunities for long‑term wealth creation. Our talented, global teams bring expertise that is both broad and unique. From our welcoming, inclusive, and supportive culture to our globally diverse business, we offer opportunities not only to help you reach your potential, but also to contribute to our clients’ success. About Enterprise Vendor Management The Enterprise Vendor Management team drives firm-wide strategic sourcing and vendor optimization to support Franklin Templeton’s global investment operations. We partner with technology, business, legal, and risk teams to secure high‑quality vendor services while managing cost, risk, and performance. Team members collaborate across regions, work on high‑value commercial initiatives, and gain exposure to complex negotiations and global sourcing strategy. Joining this team provideas hands‑on experience with high‑impact negotiation, supplier management, and enterprise‑wide transformation initiatives. How will you add value? Core Responsibilities: Manage a large technology spend portfolio Partner with technology and business teams to understand requirements. Lead & Drive Strategic Sourcing initiatives with key stakeholders. Manage assigned technology spending, including software and services. Lead & Oversee end‑to‑end supplier relationships. Review

About Paytm Paytm, a pioneer of digital payments in India, enables 450 Mn+ consumers & 49 Mn+ merchants to make and accept digital payments, alongside Financial & Commerce services. This scale is built on proprietary, full-stack technology that drives continuous innovation in India's digital economy. Paytm's model has proven successful at acquiring customers and merchants on payments, then cross-selling them financial services. Paytm plans to build on this success to expand internationally, leveraging its proprietary merchant acquiring stack, payment acceptance device, and SME Credit platform. About the Team The international team evaluates, plans, and executes market entry strategy in key international markets, with direct ownership of local execution and operations. Key activities include market research, forming and managing strategic partnerships, liaising with regulators and government authorities, working with consultants and experts, and driving AOP delivery - including launch readiness, operational roll-out, and day-to-day performance management of the local business. About the Role Paytm is looking for an experienced Senior Manager to own and drive its international expansion - from market entry strategy through to on-ground execution. Key Requirements 1. Market Research: Assess market and industry landscape — competitive positioning, pricing, commercial structures, distribution, and operating models — via primary and secondary research, translating findings into actionable market-entry and operating plans. 2. Partner Relationships: Identify and engage potential partners, shape collaboration models, lead negotiations, and close agreements within targeted timelines. 3. Business Plan: Co-develop financial/commercial models and strategic business plans with partners, and own delivery against plan once operations go live. 4. Project Management: Track international projects and AOP delivery, oversee the partner business, take corrective action as neede

NVIDIA pioneers computer graphics, gaming, AI, and accelerated computing. We are looking for a Senior Solution Architect with full-stack software engineering experience to join our team and play an important role in developing Sales AI applications. This position offers the opportunity to design, build, and evolve solutions that bring generative AI and intelligent workflows into everyday sales experiences. You will work across the application stack and collaborate with Product, AI and machine learning, Data, Security, Solution Architecture, and Engineering teams to deliver secure, reliable, and scalable solutions used globally. What you’ll be doing: Collaborate with application teams to design, develop, and maintain scalable full-stack solutions for enterprise sales workflows. Guide technical solutions across front-end, back-end, APIs, data services, integrations, and cloud infrastructure. Translate product requirements and business needs into secure, maintainable solutions and intuitive user experiences. Integrate generative AI models, AI services, APIs, retrieval systems, and agentic workflows into production applications. Design application architectures that support performance, availability, observability, security, scalability, and long-term maintainability. Lead technical design discussions, compare implementation approaches, make informed architecture decisions, and evaluate emerging technologies. Improve engineering practices for testing, code quality, continuous integration and delivery, monitoring, documentation, and production readiness. Investigate complex issues and develop solutions that improve reliability and user experience. Mentor engineers, share technical knowledge, and contribute to engineering standards and collaborative team practices. What we need to see: <