On Page Seo in India

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As Director of Recruiting, Engineering and Information Technology, you’ll lead GitLab’s India-based recruiting efforts for Engineering and IT while helping shape technical hiring across the broader Asia-Pacific region. You’ll lead recruiting managers and their teams, set the regional talent strategy, and maintain direct ownership of senior and executive-level searches. Reporting to the Vice President of Talent Acquisition or an equivalent senior Talent Acquisition leader, you’ll help GitLab build exceptional technical teams in high-growth markets and create a scalable, well-documented recruiting model. Yo

Location Details: Gurgaon, India 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.​ 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 GoDaddy is empowering everyday entrepreneurs around the world by providing all of the help and tools to succeed online. GoDaddy is the place people come to name their idea, build a professional website, attract customers, sell their products and services, and manage their work. Our mission is to give our customers the tools, insights and the people to transform their ideas and personal initiative into success. Our Identity team is looking for a Software Engineer to join us in building and maintaining GoDaddy's customer identity platform. As a software engineer on our team, you will work in an Agile scrum environment, contributing to the development and maintenance of mission-critical services that serve as the authoritative source of truth for all GoDaddy customer profiles, identity verification, and consent management. You'll be working with modern cloud-native architectures, handling billions of requests, and ensuring the highest standards of security and compliance for customer data. What you'll get to do... Design, develop, and maintain backend services and RESTful APIs using Java and Spring Boot for GoDaddy's customer profile and identity platform Build scalable, event-driven microservices on AWS (DynamoDB, Kinesis, Lambda, ECS/Fargate, S3, OpenSearch), including real-time integrations with internal systems and third-party vendor

Location Details: India, Remote 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.​ This is a remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings. Join our team… We’re a high-impact, collaborative Order to Cash Revenue team that sits at the intersection of key teams within GoDaddy (Finance, Accounting, and Technology). Our mission is to ensure accurate, timely, and compliant revenue recognition while optimizing the end-to-end Order-to-Cash process to support GoDaddy’s global financial operations and enable informed business decisions. We support innovation by bridging the gap between technical capabilities and accounting requirements, enabling our teams to make data-driven decisions with confidence. Join us to make an impact! What you’ll get to do… Contribute to month-end close by preparing journal entries, account reconciliations, and account analysis in a timely manner. Support global billing for corporate customers, and perform research on billing discrepancies. Identify and actively provide solutions for automation and process improvement while ensuring daily responsibilities are completed with detail, accuracy, and timeliness. Support audit activities by maintaining and improving SOX compliance for accounting functions and participating in SOX documentation and testing. Partner with Accounting, Engineering, and Finance stakeholders across the globe to support system implementations and improvements across ERP, billing and revenue systems. Your experience should include… 3-5 years of relevant accounting experience. Bachelor’s degree or equivalent experience in Accounting, Finance, or a related field. Foundational understanding of accounting theory, knowledge of US GAAP and willingnes

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Lead Software Engineer Overview MasterCard is seeking talented individuals to join our Emerging Payments Technology team in Pune, India. MasterCard is researching and developing the next generation of products and services to enable consumers to securely, efficiently, and intelligently conduct transactions regardless of channel. Whether through traditional retail, mobile, or e-commerce, MasterCard innovation is leading the digital convergence of traditional and emerging payments technologies across a wide variety of new devices and services. Join our team and help shape the future of connected commerce! Role The Consultant, Software Engineering is a hands-on developer specializing in Java development with a particular focus producing software development kits (SDKs) and API services in support of MasterPass, our digital wallet solution. As a Consultant on the Digital Payments Technology team, you will be responsible for helping design and implement SDKs and API services across multiple products and services. You’ll work closely with other team technical leads and with our Product Management team, and other stakeholders. Working within an agile development methodology, you will collaborate with and mentor other engineers and with other technical delivery teams, implement solid, robust solutions f

Our Purpose Mastercard powers economies and empowers people in 200&#43; countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Senior Software Engineer Overview Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all. Role All staff at Mastercard are expected to demonstrate 'Mastercard Way' cultural values every day - own it, simplify it, sense of urgency, thoughtful risk-taking, unlock potential, and be inclusive – with a relentless focus on our customers. As a Software Development Engineer II at Mastercard, you are expected to perform the following general duties: • Own tasks (dev, test, deployment) at an application/software component level • Able to troubleshoot and refactor existing code • Adopt new languages and architecture patterns needed for the work • Influence the decisions made by the team <

We are seeking a Front-End Integration Engineer for the NIC Silicon group. Join our team at NVIDIA's Networking business unit and be part of the innovative build and implementation of the next generation Network Adapter Silicon chips. Contribute to the development of powerful communication devices. What You'll Be Doing: Own and maintain Continuous Integration pipelines. Monitor, complete, and fix daily and nightly CI flows in front-end build areas. These include Lint, Synthesis, Equivalence Checking and Simulation. Automate EDA Flows: Build, develop, and maintain robust automation scripts using Python, Tcl scripting, and Shell to integrate EDA tools (Synopsys, Cadence) into automated build pipelines. Manage Perforce Integration: Maintain multi-IP branch/stream strategies, manage workspace specs, complete hardware build drops, and handle release labels/tags in Perforce (Helix Core). Support Engineering Teams: Act as the primary point of contact for RTL and verification engineers to debug flow crashes, bottlenecks, environment setups, and CI failure reports. Enforce Quality Gates: Implement automated check-in and change list triggers to run sanity checks, linting, and style enforcement before code is committed to main streams. Optimize Infrastructure: Monitor compute farm resources (LSF) and storage usage to reduce pipeline runtime and improve overall execution efficiency. What We Need to See: Experience: 2&#43; years of hands-on industry experience in ASIC/SoC front-end integration, CAD, or EDA flow automation. Education: Bachelor’s degree or Master’s degree or equivalent experience in Electrical Engineering, Computer Engineering, Computer Science, or a related field. Perforce Expertise: Strong hands-on experience managing Perforce (P4 / Helix Core) streams, workspace specs, c

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

Product Management Intern- Paytm Gold About Us: Paytm is India's leading mobile payments and financial services distribution company. Pioneer of the mobile QR payments revolution in India, Paytm builds technologies that help small businesses with payments and commerce. Paytm’s mission is to serve half a billion Indians and bring them to the mainstream economy with the help of technology. About the Team: - Paytm Gold is a prominent digital gold vertical within the Paytm ecosystem, integrated seamlessly into both consumer and business applications. ⁠ - This platform empowers users to initiate and cultivate a gold savings habit with investments starting from as low as ₹9.⁠ - The Paytm Gold team comprises seasoned professionals with extensive experience in developing and scaling successful gold-based consumer products. Key Responsibilities: - Contribute to product development and strategy for the Gold Team. - Assist in market research and competitive analysis. - Support cross-functional teams in product-related initiatives. Qualifications: - Strong analytical and problem-solving skills. - Excellent communication and collaboration abilities. Why join us 1. A collaborative output-driven program that brings cohesiveness across businesses through technology 2. Improve the average revenue per use by increasing the cross-sell opportunities 3. A solid 360 feedback from your peer teams on your support of their goals4. Respect, that is earned, not demanded from your peers and manager

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

Job Details: Job Description: • Domain knowledge in Product Data Management, concept of Item/Bom, Change Management are essential. • Deep understanding of business processes related to product lifecycle management, including design, development, manufacturing, and support for any works to automate the product data management. • Ability to map business requirements and problems to technical solutions and identify opportunities for process improvement. • Ability to design and architect comprehensive solutions that integrate various components of the PLM system with other enterprise systems. • Experience in creating scalable and sustainable architectures that address current and future business needs and ensuring the a quality delivery of the solution • AI knowledge that can help to optimize the process of automating data entry and validation, and workflow will be an added advantage. • Full-stack software solutions experiences to address customer needs • Web/Windows technology development in .NET, NET Core, ASP.NET C#, node.js • Front End framework in React/Jquery/Javascript • Integration technology, for eg. SSIS. Mulesoft. • Strong skillsets in SQL, relatiotional DB, MSSQL, Postgrep • Strong foundation on HTML, CSS, understanding of old technology in asp, vbscript • Knowledge in cloud technology, container as a service, docker images. • Experience developing containerized applications and services using tools such as Docker and Kubernetes. • Experience using git for code repository management, CI/CD workflow with tools such as GitHub Actions or similar. Qualifications: Required skill set: Domain knowledge in Product Data Management, concept of Item/Bom, Change Management are essential. Experience 3-7yrs with BE/BTech background Full-stack software

This is where your work makes a difference. At Baxter, we believe every person—regardless of who they are or where they are from—deserves a chance to live a healthy life. It was our founding belief in 1931 and continues to be our guiding principle. We are redefining healthcare delivery to make a greater impact today, tomorrow, and beyond. Our Baxter colleagues are united by our Mission to Save and Sustain Lives. Together, our community is driven by a culture of courage, trust, and collaboration. Every individual is empowered to take ownership and make a meaningful impact. We strive for efficient and effective operations, and we hold each other accountable for delivering exceptional results. Here, you will find more than just a job—you will find purpose and pride. Perform development work and technical support related to our data transformation and ETL jobs in support of a global data warehouse. Can communicate results with internal customers. Requires the ability to work independently, as well as in cooperation with a variety of customers and other technical professionals. What you'll be doing Development of new ETL/data transformation jobs, using PySpark and IBM DataStage in AWS. Enhancement and support on existing ETL/data transformation jobs. Can explain technical solutions and resolutions with internal customers and communicate feedback to the ETL team. Perform technical code reviews for peers moving code into production. Perform and review integration testing before production migrations. Provide high level of technical support, and perform root cause analysis for problems experienced within area of

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