Developer Engagement Representative in India

As an Manager - Legal & Compliance in the Legal Department, you will play a pivotal role in supporting the organization’s legal framework, ensuring compliance, mitigating risks, and enabling smooth business operations. This role offers a unique opportunity to grow within a globally reputed conglomerate known for its ethical standards, sustainability focus, and commitment to community development. You will be exposed to various legal disciplines including corporate law, contract management, regulatory compliance, and dispute resolution, allowing you to develop a well-rounded skill set and a deep understanding of the business landscape. Source: Adani Group | Job ID: 57020

About Paytm: 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: The Credit Risk Product Team is at the core of our lending operations, ensuring that our risk assessment models are efficient, scalable, and compliant with regulatory frameworks. The team collaborates closely with data scientists, engineers, and business stakeholders to develop and enhance credit risk models, decisioning frameworks, and risk mitigation strategies. By leveraging advanced analytics and machine learning, the team continuously refines underwriting processes to optimize loan performance and reduce defaults. About the Role: We are looking for a rockstar Senior Product Manager – Lending Risk to lead the Merchant Lending Risk charter at Paytm. You will own the risk product strategy that powers unsecured merchant loans, balancing aggressive growth with rock-solid credit quality and regulatory integrity, while partnering closely with Risk, Data Science, Engineering & Business. Key Responsibilities: * Define and drive the product roadmap for merchant lending risk. * Build and scale rule engines (BRE), decision engines, and model orchestration layers. * Implement audit-ready decision logs and explainability layers. * Build robust policy versioning and experimentation infrastructure. * Lead a team of credit risk analysts owning underwriting, risk, fraud, and monitoring. Requirements: * 5+ years of product management experience in the consumer or fintech industry. * Strong experience in unsecured merchant or SME lending preferred * Strong analytical and structured thinking ability. Why join us •A collaborative output driven program that brings cohesiveness across businesses through tech

About the Role: We are looking for an experienced Risk Management professional to lead and strengthen our Market Risk and Margin Trading Facility (MTF) risk functions. The role will be responsible for developing robust risk frameworks, monitoring trading and client exposures, ensuring regulatory compliance, and safeguarding the organization against market-related risks while enabling sustainable business growth. Key Responsibilities: Market Risk Management - - Develop, implement, and continuously enhance market risk management frameworks across Equity, Derivatives, and Margin Trading Funding (MTF) businesses. - Monitor and assess market risk exposures arising from cash equities, futures, options, and leveraged products. - Establish and review risk limits, exposure thresholds, concentration limits, and margin policies. - Track key risk indicators (KRIs) and ensure timely escalation of potential risk events. MTF & Exposure Risk Management: - Manage client-level and portfolio-level risks associated with Margin Trading Funding (MTF). - Define collateral eligibility, haircut frameworks, and funding exposure limits. - Monitor leveraged positions and ensure adequate margin coverage across client portfolios. - Evaluate concentration risks and implement preventive controls to minimize losses. Risk Analytics & Monitoring: - Conduct stress testing, scenario analysis, and sensitivity assessments under varying market conditions. - Develop risk models and analytical tools to evaluate portfolio resilience during periods of volatility. - Analyze trading patterns, market trends, and exposure data to identify emerging risks. - Drive automation and real-time risk monitoring capabilities across trading systems. Regulatory Compliance & Governance: - Ensure compliance with SEBI, NSE, BSE, Clearing Corporation, and other applicable regulatory requirements. - Oversee risk-related regulatory reporting, including exposure monitoring, margin compliance, and CTCL reporting. - Coordinate w

MongoDB is always developing and innovating — not only in our technology, but also in our sales go-to-market strategy. Our sales leadership is committed to building the best salesforce in technology. This means, inspiring and enabling success for everyone on the team. We not only equip you to be successful and close deals, but we want your feedback and input on how we can continue to “ Think Big and Go Far .” As a crucial part of the Sales team at MongoDB, you will have access to a lucrative market and learn how to sell from some of the most successful sales leaders in the software industry. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. What you’ll be doing Sales strategy and execution: Develop and implement strategic sales plan to achieve revenue goals in the Public Sector with strong focus in State Government Relationship management: Build and maintain strong, long-term relationships with key Government Stakeholders - Senior Government Officials, Consultants, GSIs and Partners Business development: Identify new opportunities, generate leads, and pursue new government clients while also expanding business with existing ones Tender and proposal management: Work closely with Government Departments to make sure MongoDB is part of Tech Stack in tenders. Also to Monitor and respond to government tenders, RFPs, and RFQs, coordinating with internal teams to ensure timely and accurate proposal submissions Sales cycle management: Lead the sales process from lead generation and qualification through to contract negotiation and closure Performance and reporting: Set sales targets, monitor sales performance metrics, analyse market trends, and provide regular reports on activities and forecasts to senior management Internal collaboration: Work with internal teams, such as solution architects and delivery teams, to ensure seamless execution from contract award to delivery Internal Development: Participate in our sales enablement tr

About Us: Paytm is India’s leading mobile payments and financial services distribution company. A pioneer of the mobile QR payments revolution, Paytm builds technology that enables small businesses and consumers to participate in the digital economy. Our mission is to serve half a billion Indians and bring them into the mainstream economy through technology. About the Team: The Credit Risk Product Team is at the core of our lending operations, ensuring that our risk assessment models are efficient, scalable, and compliant with regulatory frameworks. The team collaborates closely with data scientists, engineers, and business stakeholders to develop and enhance credit risk models, decisioning frameworks, and risk mitigation strategies. By leveraging advanced analytics and machine learning, the team continuously refines underwriting processes to optimize loan performance and reduce defaults. About the Role: We are seeking a detail-oriented Credit Analyst to join our risk management team. The ideal candidate will be responsible for implementing credit risk policies, optimizing risk policies, and ensuring compliance with regulatory requirements. You will work closely with data scientists, product managers, and credit teams to enhance our underwriting models and decisioning frameworks. Key Responsibilities: * Analyze credit risk across various products, including merchant and personal loans, postpaid. * Liaison with the business team to understand the credit risk policies and implement the same on platform. * Implement the credit risk policies on our proprietary platform. * Monitor performance of credit risk policies. Share feedback with product and Policy team what's working well and what needs improvement. * Utilize alternative data sources, machine learning models, and traditional credit assessment techniques to enhance risk evaluation. * Conduct testing and scenario analysis to measure policy resilience. * Monitor key risk indicators (KRIs) and provide actionable

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+ 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

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

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

Data Engineer Description - Key Roles Designs and establishes secure and performant data architectures, enhancements, updates, and programming changes for portions and subsystems of data pipelines, repositories or models for structured/unstructured data. Analyzes design and determines coding, programming, and integration activities required based on general objectives and knowledge of overall architecture of product or solution. Writes and executes complete testing plans, protocols, and documentation for assigned portion of data system or component; identifies and debugs, and creates solutions for issues with code and integration into data system architecture. Collaborates within a project team of other data engineers to develop reliable, cost effective and high-quality solutions for assigned data system, model, or component. Analyzes data inaccuracies, identifies opportunities and supports the development of automated solutions to enhance overall quality of the enterprise data. Identifies problematic areas and conducts research to determine the best course of action to correct the data; identifies, analyzes and interprets trends and patterns in complex datasets. Works cross-functionally with different departments to assess, define, and develop report deliverables. Represents the software data engineering team for all phases of larger and more-complex development projects. Provides guidance and mentoring to less experienced staff members. Education & Experience Recommended Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, Statistics/ Mathematics, or any other related di

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: <

NVIDIA's Deep Learning GPUs have ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company”. We are growing our company and the team with the smartest people in the world. We are looking for extraordinary Software Engineers to develop and productize NVIDIA's DRIVE OS software. As a member of NVIDIA's Solution Engineering team, you will adapt DRIVE OS solutions to various car platforms equipped with different sensors. We are looking to hire Senior System Software Engineer – AUTOSAR. Ideal candidate will have very strong programming skills, a good grasp of HW & SW Architectures, a solid exposure to AUTOSAR & related architecture, tools and frameworks. What you will be doing: Participate and provide inputs and recommendation into AUTOSAR Architecture evolution with design choices, tools and methodology Architectural explorations on both SW and HW fronts which include feasibility studies, quick prototyping, profiling, safety studies, data analysis and presentation of results Influence next-gen HW architectures and SW Architecture and design Drive complex technical issues to closure that may occur interacting with cross-teams What we need to see: BS/MS, or equivalent experience 5&#43; years of experience Strong programming skills in C/C&#43;&#43; and scripting skills in Perl, Python etc Good experience and com

We are seeking a qualified Senior Software Tools Development Engineer to join our GPU SWQA team. The successful candidate will have strong experience applying AI technologies to automate test cases and a deep understanding of Windows operating systems. Extensive knowledge of GPU, CPU, SoC, x86, and ARM architectures is required, along with expertise in PC I/O architecture and common bus interfaces such as PCIe, USB, and SATA. Familiarity with specifications for general PC architecture components is a plus. What you’ll be doing: Design and implement automated tests incorporating AI technologies for NVIDIA's device driver software and SDKs on windows platforms. Build tools/utility/framework in Python, C# or equivalent which would help automate and optimize the testing workflows in GPU domain. Develop and carry out automated and manual tests, analyze results, identify and report defects. Rigorously drive test automation initiative. Build innovative ways to automate and expand our software testing. Expose defects and constraints; Isolate and debug the issue(s) and find the root cause; Contribute to the solution and drive to closure. Measure code coverage for the software under test, analyze and drive code coverage enhancements. Develop applications and tools that accelerate development and test workflows and write fast, effective, maintainable, reliable and well documented code. Generate and test compatibility across a range of products and interfaces and validate different key software applications across a test matrix designed to test both breadth and depth. Provide peer code reviews including feedback on performance, scalability and correctness. Report test coverage and Go/No-Go status for deliverables, escalate critical issues, and drive them to closure. Participate in root cause analysis and corrective actions to continuo