Senior Ai Ml Architect in India

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who you are You are an experienced Infrastructure Engineer Engineer who owns backend infrastructure end to end. You design multi-tenant, microservices-based systems that other engineering teams build on, and you make deliberate architectural tradeoffs around consistency, latency, scale, and cost. You are comfortable going deep — service mesh internals, database internals, distributed-systems failure modes — and equally comfortable defining the reliability and security contracts an enterprise AI platform depends on. Responsibilities Design, own, and evolve scalable microservices architectures on Kubernetes across GCP, Azure, and AWS, including multi-tenant isolation (namespaces, network policies, per-tenant resource quotas and RBAC). Build core platform and data-plane components in Golang and Python — data ingestion, knowledge-base indexing and vector/graph search, application connectivity, workflow automation, and ML operations — against explicit latency and throughput SLOs. Own service-to-service communication: gRPC/protobuf API contracts, service mesh (Istio/Linkerd), load balancing, retries, timeouts, and circuit breaking. Make and document architectural tradeoffs — partitioning

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. The Customer Experience Engineering Team builds the internal and external technologies that scale Snowflake’s global support and sales organizations. We empower our technical experts by providing the advanced tools they need to resolve complex issues and drive customer success. Our team specializes in software engineering, data-driven decisions, ML, and LLM-based solutions . We build production-grade systems to automate manual processes and augment the capabilities of our technical staff. Our current focus includes: LLMs : Developing and deploying LLM and agent-based architectures for streamlining troubleshooting Scalable Evaluations : Implementing large-scale evaluations to ensure the quality and reliability of our internal and external tools Process Automation : Designing intelligent workflows that eliminate bottlenecks and allow our experts to focus on the most technical aspects of the Snowflake platform Incident discovery: using embeddings, LLMs, clustering, and agents to detect potential widespread issues more quickly Now, the team is growing, and we are looking for a Software Engineer to join us. In this role, you will work closely with the state of the art LLM models, fine-tune them, develop agents, apply various clusterings, summarizations, embeddings, and so on. Ev

Bloomreach is building the world’s premier agentic platform for personalization .We’re revolutionizing how businesses connect with their customers, building and deploying AI agents to personalize the entire customer journey. We're taking autonomous search mainstream, making product discovery more intuitive and conversational for customers, and more profitable for businesses. We’re making conversational shopping a reality, connecting every shopper with tailored guidance and product expertise — available on demand, at every touchpoint in their journey. We're designing the future of autonomous marketing , taking the work out of workflows, and reclaiming the creative, strategic, and customer-first work marketers were always meant to do. And we're building all of that on the intelligence of a single AI engine — Loomi — so that personalization isn't only autonomous…it's also consistent.From retail to financial services, hospitality to gaming, businesses use Bloomreach to drive higher growth and lasting loyalty. We power personalization for more than 1,400 global brands, including American Eagle, Sonepar, and Pandora. About the Team: AI Search The AI Search team owns Bloomreach’s core search platform, serving hundreds of millions of queries per day across enterprise customers. We build and operate highly scalable, low-latency systems that combine traditional information retrieval with modern ML-driven ranking and semantic understanding — all in production at scale. This team sits at the intersection of systems engineering, search relevance, and applied ML , with direct impact on customer revenue and experience. The Role: As a Senior Staff Engineer , you will be a technical leader responsible for shaping the architecture and long-term evolution of Bloomreach’s Search platform. You will lead complex initiatives, set technical direction, and mentor engineers, while remaining deeply hands-on. This role is ideal for someone

Senior Machine Learning Engineer Description - We are looking for a Senior MLOps Engineer to design, build, and operate the infrastructure that enables machine learning models and large language models to be deployed safely, reliably, and at scale. In this role, you will create the end-to-end capabilities required to move models from experimentation into production, expose them through secure and highly available endpoints, and enable users and applications to interact with AI-powered services. You will work across AWS and Databricks to establish robust CI/CD pipelines, model-serving infrastructure, observability, governance, rollback mechanisms, and operational standards. You will partner closely with data scientists, machine learning engineers, software engineers, security teams, and platform engineers. The ideal candidate combines strong cloud and DevOps engineering skills with a practical understanding of machine learning systems, LLM deployment patterns, and production reliability. Key Responsibilities MLOps Platform and Architecture Design and implement a scalable MLOps platform using AWS and Databricks. Define reference architectures and reusable deployment patterns for traditional machine learning models, deep learning models, and large language models. Build standardized workflows that move models from development and validation into staging and production. Develop self-service capabilities that allow data scientists and ML engineers to deploy models without manually managing infrastructure. Establish clear separation between development, testing, staging, and production environments. Design multi-region or multi-availability-zone architectures where required by business continuity and availability objectives. CI/CD and

Backend Engineer (Senior Level) - SDE IV We're looking for a Senior Backend Engineer to lead the architecture and evolution of backend services that deploy and serve machine learning models in production. You'll work closely with ML Engineers, Platform, and Product teams to build scalable, reliable systems and drive technical direction across multiple teams. What You’ll Do Design and drive the long-term architecture of backend services for biometrics and ML model serving. Collaborate with core platform and backend teams on organization-wide architectural initiatives. Partner with business and engineering teams to design and deliver cross-cutting platform capabilities. Lead architectural reviews, mentor engineers, and promote engineering best practices. Build and maintain backend services for deploying and serving ML models Monitor service reliability, performance, and scalability in production Deploy and operate services on AWS using ECS + Fargate, SageMaker, or EC2 + Kubernetes Support real-time and batch inference workflows Contribute to CI/CD pipelines and deployment automation What We’re Looking For Strong expertise in backend development using Java and working knowledge of Python. Experience mentoring engineers and driving architectural decisions. Working knowledge of Python, especially for ML-related workflows Hands-on experience with AWS (e.g., DynamoDB, ECS, EC2, Redis, S3, SageMaker) Familiarity with Terraform or other infrastructure-as-code tools, and experience with CI/CD and production monitoring Experience with observability tools (Datadog, New Relic, etc.) Experience with containers and orchestration (Docker, ECS, etc.) Understanding of how ML models are deployed and served in production Experience with Kubernetes Nice to Have Experience with MLOps or ML platform engineering. Experience with asynchronous programming and event-driven systems. Jumio Values: IDEAL: Integrity, Diversity, Empowerment, Accountability, Leading Innovation Equal Opportunities :

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

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Smartsheet is looking for a Sr. Principal Data Scientist to set the technical direction for the ML models and AI sub-agents that drive growth, monetization, efficiency, and retention across the customer lifecycle. You’ll architect the systems, define the modeling and evaluation standards, and shape the roadmap for how Smartsheet uses applied ML and agentic AI to serve millions of customers. The data is unusually rich: petabyte-scale execution data spanning two decades of how real work gets done. You are a recognized technical leader who moves fluidly between architecture, prototype, and production; raises the bar for the data scientists around you; and partners with senior product and engineering leaders to make decisions that compound across the org. You will work primarily with Product and Engineering and will be a part of Smartsheet’s Business Intelligence team. This full-time position reports to the Director of Data Science and is based in Smartsheet’s Bengaluru, India office. You Will: Set the technical direction for how Smartsheet uses applied ML and agentic AI across the customer lifecycle — what gets built, what doesn’t, and what good looks like Architect the systems behind the sub-agents: how they ground themselves in evidence, how risk and confidence are calibrated, how decisions are evaluated, and how all of it stays safe and trustworthy at scale Define the modeling, evaluation, and experimentation standards the team follows — from offline metrics to online rollout to production monitoring Personally ship the

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Smartsheet is hiring a Senior Analytics Engineer to lead the way in data-driven decision-making. You will be responsible for the creation and maintenance of a governed, reliable, and scalable analytics system, transforming raw data into usable datasets for DS/ML, analytics, and reporting. A key aspect of this role is leading the architecture and implementation of efficient data transformation systems within Snowflake, fostering data democratization and impacting business outcomes. Working closely with BI analysts and Data scientists, you will ensure data accessibility and drive activation on critical customer-facing platforms. This full-time position reports to the Director of Analytics Engineering and is based in Smartsheet’s corporate offices in Bengaluru, India. You Will: Leading the implementation of efficient and scalable systems that optimize data transformations from our data lake in Snowflake into clean, documented data products. Contribute to the design standards and architectural principle standards, designs and processes. Build and maintain a governed, robust, reliable, and scalable analytics system (DW/DV). Collaborating with BI analysts and data scientists to provide proper data accessibility guidelines. Foster data democratization via activation of data on critical platforms like Smartsheet platform, Amplitude, Thoughtspot , Gainsight. Create and contribute to frameworks that improve data quality and observability to identify and resolve issues faster. Create and implement data testing plans, en

Want to be a bswifter? At bswift we’ve been transforming benefits administration since 1996, making it simpler, smarter, and more human. Our state-of-the-art, cloud-based technology and services empower employees to understand, manage, and love their benefits. From downtown Chicago, and remotely across the country, we serve thousands of companies and millions of people nationwide, reducing administrative burdens and freeing HR teams to focus on creating thriving, people-first workplaces. We’re looking for motivated and goal-driven individuals who share our passion for delivering excellence and creating solutions that make a difference. The reward is a fun, flexible and creative environment with ample opportunity for professional and personal growth. If you love the bswift values of pursue excellence, embrace accountability, deliver superior service, and be a great place to work, we want to hear from you! About the Role We are looking for an AI Engineer II to design, build, and deploy cutting-edge generative AI applications , including agentic workflows and intelligent chat experiences , that transform how employees interact with their benefits. This role goes beyond individual contribution—you will own complex AI features end-to-end , influence architecture decisions around LLMs and agent systems , and mentor junior engineers . You will play a key role in bringing secure, scalable, and high-performance AI solutions to production using AWS cloud technologies. You will collaborate closely with software engineers, architects, product managers, and cross-functional teams to deliver seamless and impactful user experiences Key Responsibilities 1. Solution Design & Development Lead the design and development of scalable, secure, and high-performance applications . Architect robust backend systems and integrate them with frontend applications and third-party services. Drive technical decisions and participate in design reviews alongside senio

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

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

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Build the future of AI and data-driven marketing. Join the Snowflake team. At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset and who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how PMM gets done. We’re at the forefront of the data revolution, building the world’s greatest data, applications and AI/ML platform. Our get it done culture empowers everyone at Snowflake to innovate, create work with lasting impact, and thrive in a collaborative environment. Snowflake EMEA product marketers conceive of and execute go-to-market plans that drive awareness, adoption and drive success for our customers. We are looking for a Senior Product Marketing Manager to orchestrate go-to-market execution targeting AI dec

Join Delphi - Where Innovation meets transformation At Delphi, we believe in creating an environment where our people thrive. Our hybrid work model empowers you to choose where you work—whether it's from the office, your home, or a mix of both—so you can prioritize what matters most. We are committed to supporting your personal goals, family, and overall well-being while driving transformative results for our clients. We welcome exceptional talent from anywhere across the globe. Interviews and onboarding are conducted virtually, reflecting our digital-first mindset. Rooted in the region, we specialize in delivering tailored, impactful solutions in Data, Advanced Analytics and AI, Infrastructure, Cloud Security, and Application Modernization. Whether it’s enabling predictive analytics , transforming operations with automation, or driving customer engagement with intelligent platforms, we are the trusted partner for organizations ready to embrace a smarter, more efficient future. We are looking for a hands-on Senior QA Consultant to lead end-to-end testing of AI and Generative AI applications across enterprise environments. This role combines strong expertise in traditional QA engineering with modern AI evaluation and validation practices. The ideal candidate will drive quality assurance initiatives for RAG pipelines, multi-agent systems, OCR and Speech-to-Text solutions while ensuring production grade quality outcomes in regulated industries such as Finance, Healthcare, and Insurance. The successful candidate will lead a small QA pod, collaborate closely with engineering, AI/ML, product, and business teams, and act as the client-facing QA owner for enterprise AI engagements. This role requires strong technical leadership, automation expertise, AI evaluation capabilities, and excellent stakeholder management skills. Experience Requirements • 7–10 years of experien

Who We Are Simpplr is the AI-powered intranet for unifying the digital workplace. It brings people, trusted knowledge, apps, and agents into a coherent digital experience. Powered by a proprietary EX Knowledge Graph, Simpplr synthesizes signals and context across connected systems to deliver personalized information and actions. The platform serves as a digital hub supporting communications, engagement, employee services, and work. With low-code extensibility and enterprise-grade security and governance, Simpplr enables confident operation at scale. More than 1,000 organizations — including AAA, the NHS, Penske, and Moderna — trust Simpplr to keep their workforce informed, aligned, and productive. Learn more at simpplr.com . The Opportunity We're looking for a highly skilled Senior Product Manager – Enterprise Search to join our Product Management team . In this role, you'll own the strategy, definition, and execution of enterprise search across Simpplr — powering both Magnus (our AI assistant) and the Simpplr platform. You'll shape how employees find the right knowledge, content, and answers across the entire enterprise, quickly, accurately, and securely. Search is the connective tissue of the employee experience: it is what makes Magnus's answers trustworthy and what makes the Simpplr platform feel intelligent. You'll be responsible for the end-to-end search experience — from how content is ingested, chunked, and indexed, to how it is retrieved, ranked, and grounded into high-quality, permission-aware answers via retrieval-augmented generation (RAG). You'll work closely with AI engineers, search/ML engineers, data scientists, designers, and cross-functional teams to deliver a search foundation that is fast, relevant, and enterprise-grade. This role requires strong technical fluency in modern search and AI concepts — indexing, chunking, embeddings, vector and hybrid retrieval, ranking, and RAG — along with the product judgment to translate them into measurabl