Deployment Strategist Lead in India

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 Data Scientist II Role Overview Build and productionize enterprise-grade AI and Generative AI solutions for Mastercard. This role combines strong software engineering with model fine-tuning, Databricks-based ML engineering, AWS deployment, and end-to-end MLOps. Key Responsibilities Design, develop, test, and maintain scalable AI/ML applications, APIs, and reusable engineering components. Fine-tune and evaluate foundation models using techniques such as LoRA, QLoRA, PEFT, and supervised fine-tuning. Build RAG solutions, embeddings workflows, vector-search applications, and AI agents. Create end-to-end ML pipelines for data preparation, training, evaluation, deployment, monitoring, and retraining. Use Databricks, PySpark, MLflow, Unity Catalog, Workflows, Vector Search, and Model Serving for governed model development and operations. Implement CI/CD, automated testing, observability, model monitoring, and production support practices. Partner with data science, engineering, product, security, privacy, and governance teams to deliver reliable and responsible AI solutions. Required Skills & Experience 3–4 years of experience in AI/ML engineering, software engineering, data science, or a related field. Strong Python, SQL, object-or

AI Tech Lead – Manager Experience- 8-12 years Job Overview: We are seeking a highly experienced AI Tech Lead to design, develop, and deliver scalable AI-driven applications while leading cross-functional teams. The role involves end-to-end ownership of AI solutions, including architecture design, deployment, and optimization, ensuring alignment with business objectives. The candidate will collaborate with stakeholders, data engineering teams, and product management to build enterprise-grade AI systems leveraging modern cloud and AI technologies. Key Responsibilities / (Person Specifications): Lead implementation and delivery of AI applications across teams. Design end-to-end AI architectures integrating open-source and enterprise tools. Translate business requirements into scalable AI solutions. Define architecture roadmaps and best practices. Build data pipelines, CI/CD, and monitoring systems. Deploy scalable systems using Docker and Kubernetes. Ensure performance, scalability, and security. Mentor teams and drive knowledge sharing. Key Skills / Job Specifications (Mandatory): AI frameworks: LangGraph, AutoGen, CrewAI. Strong Python with TensorFlow, PyTorch, Keras. Knowledge of NLP & Deep Learning (RNN, CNN, LSTM, Transformers). Cloud platforms: AWS / Azure / GCP. Docker, Kubernetes, CI/CD tools. Terraform / CloudFormation (IaC). SQL & NoSQL databases. Distributed systems, REST APIs, GraphQL, microservices.

NetSuite Consultant at Plative, you support SaaS customers through NetSuite ERP implementations and platform optimizations. You configure and deliver scalable solutions for subscription-based businesses, working alongside senior consultants and project managers. This role requires close collaboration with customer stakeholders, project managers, developers, and cross-functional teams. You'll contribute across the project lifecycle, from discovery through deployment and post-implementation support, on one or more customer engagements at a time. Key Responsibilities Customer Collaboration Support NetSuite engagements for SaaS and subscription-based organizations Participate in discovery sessions and workshops to understand business processes and requirements Apply best practices for subscription billing, revenue recognition, and services delivery Build strong working relationships with customer stakeholders Solution Design & Business Analysis Translate business requirements into NetSuite configurations Document functional specifications, process flows, and solution details Support demonstrations, process walkthroughs, and end-user training NetSuite Implementation & Delivery Configure and customize NetSuite modules, including: Financials Suite Billing Advanced Revenue Management Suite Projects (PSA) Multi-Book Accounting Support delivery across one or more customer engagements Execute testing activities, User Acceptance Testing (UAT), and go-live readiness Work with technical teams to deploy customizations, workflows, and automation Integrations & Data Migration Support integrations between NetSuite and external platforms, including Salesforce, HubSpot, and Avalara Contribute to data migration planning, validation, and reconciliation Work with developers on custom integrations Required Qualifications 3-5 years of experience implementing and configuring NetSuite ERP solutions Working knowledge of: SuiteBilling ASC 606 Revenue Recognition Advanced Revenue Man

Here at Appian, our values of Intensity and Excellence define who we are. We set high standards and live up to them, ensuring that everything we do is done with care and quality. We approach every challenge with ambition and commitment, holding ourselves and each other accountable to achieve the best results. When you join Appian, you’ll be part of a passionate team dedicated to accomplishing hard things, together. Location- Chennai Team: Engineering Enablement Group As a Senior Software Engineer in our Engineering Enablement Group, you will lead the re-design and evolution of our Mobile Branding framework — the system that enables customers to create custom-branded versions of the Appian mobile application for both iOS and Android. You will drive the architectural modernization of the end-to-end branding pipeline, from the customer-facing Forum application and provisioning tools to the backend build service running on Mac EC2 runners in AWS. By leveraging modern microservices, CI/CD automation, and cloud-native infrastructure, you will transform the current system into a more reliable, scalable, and maintainable platform that reduces manual intervention and accelerates customer delivery. We are looking for a technical leader who can bridge the gap between complex Ruby/Bash-based tooling, Appian process models, and AWS infrastructure to deliver a seamless mobile branding experience. Primary Qualifications: 6-9 Strong working experience with Android and iOS frameworks and mobile application development workflows. Familiarity with mobile build systems (Fastlane, Xcode, Gradle) and code-signing workflows. Experience with proficiency in Python, with experience in Ruby, Bash, or Go being a plus. Advanced experience with AWS infrastructure (S3, Lambda, EC2) and CI/CD pipeline design. Strong end-to-end knowledge of pipeline creation, deployment automation, and infrastructure-as-code (Terraform). Familiarity with monitoring, observability, and performanc

Role Purpose We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on ex

Machine Learning Engineer IV – (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Strong industry experience in Machine Learning, dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on exper

Role Purpose: At Jumio, you will work for one of the market leaders in the global identity verification space that is helping to make the digital world a safer place for everyone. As a Software Development Engineer in the MLOpsTeam, you will develop the blueprint for highly scalable and performant ML model serving. Role Value: As a Software Engineer (SDE III), you will drive the continuous improvement of the infrastructure and applications to manage the lifecycle of ML assets (data, models) to better developer experience and strengthen governance capabilities. Secondly, you will design and implement robust ML infrastructure for model deployment, serving, and optimization. You will work on efficient CI/CD pipelines for ML models and leverage advanced compilers or hardware optimization to maximize inference performance while optimizing costs. We welcome you to challenge us to impact our software development processes and tools. Example Responsibilities: Upgrade ML assets (models, data) management systems for better developer experience and robust governance capabilities Build and optimize model serving infrastructure with a focus on inference latency and cost optimization Architect efficient inference pipelines that balance latency, throughput, and cost across various acceleration options Implement cost-efficient, enterprise-scale solutions Collaborate in a cross-functional, distributed team for continuous system improvement Work with MLEs, QA Engineers, and DevOps Engineers Evaluate and implement new technologies and tools Contribute to architectural decisions for distributed ML systems Experience and Qualifications : 5+ years of experience in software engineering with Python Experience with model lifecycle management (MLFlow, Weights & Biases or equivalent) Experience with data management ecosystem (quality, transformation, catalog) Experience with ML frameworks, particularly PyTorch Experience optimizing ML models with hardwar

Own the architecture of Myntra’s new product platforms to drive business results Drive and own the architecture and design of some of the most advanced & complex software systems / products in the industry to create company wide impact Help build, mentor and coach a team of very talented Engineers, Architects, Quality engineers, System Operation Engineers and DevOps engineers in architectural and design best practices Experience in distributed systems, cloud service development, deployment and delivery Accountable for the design, for the ease of evolution, quality of the systems, performance, scaling, and availability characteristics and limitations of the systems Envision and develop the long-term architectural direction, with emphasis on platforms/ reusable components while adopting an agile delivery process. Establish structures and processes that ensure a high level of quality and reliability and extensibility of deliverables Drive the creation of next generation extensible web, mobile and fashion commerce platforms, security protocols, customisation and tools to support continuous scaling, internationalisation and platform extensions Drive code and design reviews of components / systems / products in scope and drives the architectural governance for them Set directional paths for the teams/department for adoption of new technology stacks for solving business problems Represent multiple technology domains and Myntra in external technical forums Work with product management, business stakeholders and other engineering leaders to help define mid-term, long-term roadmaps and shape business directions Initiate and deliver leadership training within the engineering organisation, including training new managers, and drive the growth of leaders to create a strong leadership bench. Qualifications & Experience 8+ years of experience in software product development Must have a degree in Computer Science o

Roles and Responsibilities Own the architecture of Myntra’s new product platforms to drive business results Drive and own the architecture and design of some of the most advanced & complex software systems / products in the industry to create company wide impact Help build, mentor and coach a team of very talented Engineers, Architects, Quality engineers, System Operation Engineers and DevOps engineers in architectural and design best practices Experience in distributed systems, cloud service development, deployment and delivery Accountable for the design, for the ease of evolution, quality of the systems, performance, scaling, and availability characteristics and limitations of the systems Envision and develop the long-term architectural direction, with emphasis on platforms/ reusable components while adopting an agile delivery process. Establish structures and processes that ensure a high level of quality and reliability and extensibility of deliverables Drive the creation of next generation extensible web, mobile and fashion commerce platforms, security protocols, customisation and tools to support continuous scaling, internationalisation and platform extensions Drive code and design reviews of components / systems / products in scope and drives the architectural governance for them Set directional paths for the teams/department for adoption of new technology stacks for solving business problems Represent multiple technology domains and Myntra in external technical forums Work with product management, business stakeholders and other engineering leaders to help define mid-term, long-term roadmaps and shape business directions Initiate and deliver leadership training within the engineering organisation, including training new managers, and drive the growth of leaders to create a strong leadership bench. Qualifications & Experience 8+ years of experience in software product development Must have a d

About the Role REMOTE IN INDIA We're looking for a software engineer to build the Kubernetes-native control plane that provisions and runs our GPU inference fleet. You'll design a manifest-driven API where the inference team declares what they need, whether that's a cluster, a model deployment, or a capacity change, and our controllers handle the reconciliation, provider/runtime selection, and lifecycle management underneath, so the inference team never has to know or care which specific serving stack, scheduler, or hardware pool is doing the work. You'll also build the systems that keep the fleet efficient, not just running, including defragmentation and rebalancing logic that consolidates scattered workloads back into contiguous capacity, and scheduling/bin-packing improvements that push GPU utilization up without hurting latency. The core value we're after is decoupling the people building on top of the platform from the operational and runtime complexity underneath, while squeezing more usable capacity out of the same hardware. You'll build the controllers, reconciliation loops, and self-service surface (API/CLI, not tickets) that make that decoupling real, plus the event-driven health, remediation, and utilization systems that keep it running and efficient without a human in the loop. Strong candidates have hands-on experience with Kubernetes controller/CRD patterns, have built or operated a platform API that abstracts multiple backends behind one interface, understand GPU scheduling and capacity efficiency (fragmentation, bin-packing, right-sizing), and think about GPU infrastructure as software to be engineered. A product mindset - you've built internal platforms or APIs consumed by other engineering teams and care about the developer experience of what you ship. You build it, you own it. You are not only responsible for delivering the software but also for operating and supporting it in production. Responsibilities Build the provisioning state machine

About the Role At Together AI, you’ll build and operate one of the world’s largest GPU fleets used for frontier model training and inference. This isn’t a traditional infrastructure role—we’re looking for engineers who love building systems, automating everything, and solving problems at massive scale. If you enjoy writing software more than clicking dashboards, obsess over eliminating manual work, and want to build infrastructure that manages tens of thousands of GPUs autonomously, we’d love to talk. Responsibilities Design and build fleet automation systems that provision, validate, deploy, upgrade, repair, and retire GPU clusters with minimal human intervention. Build AI Infrastructure Agents that automate deployment, root-cause failures, incident triage, and autonomous remediation. Develop Fleet Intelligence platforms that continuously monitor hardware health, firmware, networking, storage, thermals, and workload performance to predict failures before they impact customers. Build software that maximizes GPU availability, utilization, performance, and reliability across thousands of accelerators. Create automated validation systems for GPUs, InfiniBand/RoCE fabrics, NVLink/NVSwitch, storage, and distributed AI workloads. Build internal platforms and developer tools that allow infrastructure to be managed through software—not manual operations. Continuously improve deployment velocity, reliability, and operational efficiency through automation. Partner closely with hardware, networking, platform, and AI teams to push the limits of AI infrastructure. Requirements 3+ years building distributed systems, infrastructure platforms, or large-scale backend software. Strong software engineering skills in Python, Go, or Rust . Experience building platforms, automation systems, or developer infrastructure. Experience with Linux, Kubernetes, Terraform, Ansible, or similar infrastructure technologies. Strong systems thinking with the ability to understand problems across hardw

Role: Senior AI Engineer Location: Hyderabad, India (Hybrid) Department: Product Development About the Role GHX is building a cutting-edge LLM-powered document understanding platform focused on classification, structured data extraction, and intelligent orchestration at scale. This is a high-impact AI engineering role where you will own the full lifecycle—from problem framing to production deployment . Initially, you will focus on prompt engineering and evaluation systems , building the quality foundation for AI performance. Over time, the role expands into agent orchestration, system architecture, and migration of rule-based systems to LLM-driven pipelines . A strong foundation in software engineering (5+ years) is essential. This role demands engineering rigor across both traditional system design and AI system behavior . Core Responsibilities 1. Prompt Engineering Design prompts for diverse document classification and extraction tasks Treat prompts as formal specifications (precise, structured, and edge-case-aware) Develop few-shot, chain-of-thought, and structured output templates Manage prompt lifecycle: versioning, testing, and rollback 2. LLM Output Evaluation Create and maintain ground truth datasets Build automated evaluation pipelines (precision, recall, field-level accuracy) Identify and resolve conceptually incorrect outputs despite surface correctness 3. AI Agent Orchestration Design multi-agent workflows for document processing Implement tool-use patterns and integrate MCP servers Optimize orchestration for scale and efficiency 4. Software Engineering Develop production-grade APIs and backend services Apply Clean Architecture / DDD principles Write maintainable, testable Python code Contribute to CI/CD, deployment, and observability systems 5. Stakeholder Collaboration Act as a bridge between business stakeholders and AI systems Translate product requirements into technical architectures Communicate system behavior, limitations, and quality

Description: Graviton Research Capital LLP, Gurgaon is looking to hire Software Engineers for our Core Technology team which has some of the best programmers in India working on cutting edge technologies to build a super fast and robust trading infrastructure handling millions of dollars worth of trading transactions every day. As a Senior Software Engineer with Graviton your responsibilities will include: Designing and implementing a high-frequency automated trading system, that trades on multiple exchanges Building live reporting and administration tools for the trading system Performance optimization and improving the overall latency of systems, through algorithm research and using cutting edge tools and techniques End-to-end ownership of modules, including designing, development, deployment and support Growing the team through involvement in the regular hiring process and occasional campus recruitments Requirements : The ideal requirements for our candidates are: A degree in Computer Science 3-5 yrs Experience with C/C++ and object-oriented programming Experience in HFT industry Expertise in algorithms and data structures Excellent problem solving skills Strong communication skills A working knowledge of Linux systems Any of the following is a plus: A good understanding of TCP/IP and Ethernet Knowledge of any other programming language e.g. Java, Scala, Python, bash, Lisp, etc. Familiarity with parallel programming models and parallel algorithms Experience with big data environments e.g. Hadoop, Spark etc. Benefits: Our open and collaborative work culture gives you the freedom to innovate and experiment. Our cubicle free offices, non-hierarchical work culture and insistence to hire the very best creates a melting pot for great ideas and technological innovations. Everyone on the team is approachable, there is nothing better than working with friends! Our perks have you covered. Competitive compensation Annual international team outing Fully covered commuti

Role Overview Build reliable software services that power products, platforms, and business decisions. As a Senior Software Developer, you’ll design and deliver scalable applications, backend services, and integrations that perform well in production and evolve with changing business needs. You’ll apply strong software engineering practices across APIs, data-intensive applications, cloud services, AI-enabled solutions, and deployment pipelines. You’ll help shape technical solutions, improve system reliability, and contribute to a high-quality engineering culture. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Design and develop scalable backend services and applications using Python or TypeScript. Lead the development of APIs, integrations, reusable software components, and AI-enabled features. Build reliable solutions for data ingestion, manipulation, service-to-service communication, and intelligent automation. Apply AI technologies and modern software engineering practices to improve product capabilities, developer productivity, and operational efficiency. Make sound technical decisions around architecture, performance, security, scalability, and maintainability. Deploy and operate applications using AWS services and CI/CD practices while improving testing, monitoring, documentation, and delivery standards. These are the essentials you’ll need to get an interview 5+ years of professional experience developing and delivering production software. Strong hands-on experience with Python; TypeScript or similar languages is also valuable. Proven experience building backend services, APIs, integrations, and service-oriented applications. Experience applying AI technologies, such as generative AI, machine learning services, intelligent automation, or AI-enabled application features. Strong understanding of software design principles, testing, debugging, performance optimization, and secure development. Experience working with cloud platfor

Here's a summary of the role: Do you love building scalable cloud platforms and solving complex engineering problems with modern technologies? As a Senior Software Engineer at Diligent, you'll design and deliver high-performing , serverless applications that power our global SaaS platform. You'll work extensively with TypeScript, Node.js, AWS, and event-driven microservices, owning services from design to deployment and production monitoring. This is an opportunity to influence technical decisions, mentor engineers, and explore how AI can transform software development and engineering productivity. If you're passionate about cloud-native architectures, distributed systems, and building software that scales to millions of users, we'd love to meet you. Here's a breakdown of what you'll do (not all of it, just the important stuff): Design and build scalable backend services and event-driven microservices using TypeScript and AWS. Develop secure APIs and integrations that power reporting, analytics, and dashboard experiences. Build and maintain serverless solutions using AWS services such as Lambda, EventBridge , SQS, and DynamoDB. Drive engineering excellence through testing, observability, automation, and production readiness practices. Contribute to infrastructure-as-code and CI/CD pipelines using AWS CDK and modern DevOps practices. Mentor engineers, participate in architecture discussions, and champion the use of AI tools to improve development efficiency. These are the essentials you'll need to get an interview: 6-8 years of professional software engineering experience. Strong experience with TypeScript, Node.js, and modern backend development patterns. Hands-on experience building cloud-native applications on AWS. Strong understanding of serverless architectures and event-driven microserv