Software Engineer Ml Infrastructure in Bengaluru

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 Minimum experience of 4-6 Years required in AI ML Ops 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

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. About Okta Okta is an enterprise grade identity management service, built from the ground up in the cloud and delivered with an unwavering focus on customer success. With Okta you can manage access across any application, person, or device. Whether the people are employees, partners, or customers, or the applications are in the cloud, on premises, or on a mobile device, Okta helps you become more secure, make people more productive, and maintain compliance. The Okta service provides directory services, single sign-on, strong authentication, provisioning, workflow, and built in reporting. It runs in the cloud on a secure, reliable, extensively audited platform and integrates deeply with on premises applications, directories, and identity management systems. About the Team The Data Platform team is responsible for the foundational data services, systems, and data products for Okta that benefit our users. Today, the Data Platform team solves challenges and enables: Streaming analytics Interactive end-user reporting Data and ML platform for Okta to scale Telemetry of our products and data Our elite team is fast, creative and flexible. We encourage ownership. We expect great things from our engineers and reward them with stimulating new projects, new technologies and the chance to have significant equity in a company. Okta is about to change the cloud computing landscape forever. About the Position This is an opportunity for experienced Softwa

Position Overview: We are looking for a Senior Software Engineer to drive technical excellence, architect complex systems, and elevate our engineering team. You will own critical technical decisions, lead major initiatives from conception to delivery, and set the standard for engineering quality across our products. As a senior engineer, you will architect and lead the development of sophisticated AI-enabled features and infrastructure. This includes designing MCP server architectures, building advanced RAG systems, implementing agentic AI workflows, and establishing patterns that scale across our product portfolio. You will combine deep technical expertise in both traditional software engineering and AI/ML to deliver production-grade solutions. What You'll Do Lead the design and implementation of AI integration infrastructure (MCP servers, orchestration layers, API gateways) Build sophisticated AI features including advanced RAG systems, agentic workflows, and multi-step reasoning Establish AI engineering best practices, security patterns, and quality standards Lead technical initiatives from requirements through production deployment Make critical architectural decisions balancing performance, scalability, cost, and maintainability Design AI evaluation frameworks and implement quality benchmarks Debug and resolve complex production issues across traditional and AI systems Required Qualifications Tech Stack Core: Node.js, React, TypeScript, AWS, PostgreSQL, MSSQL, Docker AI & Integration: Python, MCP, AWS Bedrock, LangGraph/Semantic Kernel, Vector Databases, RAG Core Technical Skills 5+ years professional development with proven track record of delivering complex systems Strong Node.js and JavaScript/TypeScript expertise Advanced React and frontend architecture skills Extensive AWS architecture experience Expert PostgreSQL database design, optimization, and performance tuning Deep understanding of microservices, distributed systems, and

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

A Career with Point72's Technology Team As Point72 reimagines the future of investing, our Technology group is constantly improving our company’s IT infrastructure, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts experimenting, discovering new ways to harness the power of open source solutions, and embracing enterprise agile methodology. We encourage professional development to ensure you bring innovative ideas to our products while satisfying your own intellectual curiosity. What you'll do Lead the design, development, and operation of scalable, enterprise-grade AI/ML architectures and systems with a strong emphasis on reliability, availability, and performance. Lead and mentor a team of engineers, driving technical direction, code quality, and iterative delivery of large-scale solutions. Partner closely with data scientists, engineers, product teams, and compliance to integrate AI/ML solutions into existing and new products. Own the end-to-end lifecycle of GenAI services, including LLM inference, model serving, and proxy/gateway layers that support multiple downstream applications. Define and uphold engineering best practices around observability, scalability, security, and cost efficiency for AI/ML platforms. Evaluate tools, technologies, and processes to ensure the highest quality and performance of AI/ML systems. Stay abreast of the latest advancements in AI/ML technologies and methodologies, and translate them into pragmatic solutions for the business. Ensure compliance with industry standards and best practices in AI/ML. What's required Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 10+ years of experience in software/AI/ML engineering, with a proven track record of successful delivery of complex, production-grade systems. Demonstrated experience building large-scale enterprise-grade services with high reliability, availability, and observability (SLO/SLA-driven en

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

AI/ML – Investment Services A Career with Point72's AI/ML – Investment Services Team The AI/ML – Investment Services team at Point72 spearheads the development of cutting-edge AI solutions that seek to transform our business processes and enhance enterprise intelligence. The team aims to bridge the gap between business challenges and technological innovation, collaborating with stakeholders across the firm and leveraging expertise in generative AI, data engineering, and machine learning. WHAT YOU'LL DO Build and scale core backend services and platforms that power generative AI applications and data infrastructure used across the firm’s investment workflows Design and implement high-throughput, low-latency data pipelines to ingest, normalize, and serve both structured and unstructured data Develop robust APIs and microservices to support model inference, feature serving, and downstream applications Integrate generative AI tools and model-serving workflows into production, including embedding stores, retrieval components, and fine-tuning pipelines Optimize system performance, cost, and reliability through profiling, capacity planning, and architectural improvements Implement automated testing, continuous delivery pipelines, monitoring, and incident response practices to maintain production health Partner with data scientists, AI engineers, product owners, and operations to translate models and prototypes into scalable, production-grade solutions Mentor engineers, lead code reviews, and establish engineering best practices for maintainability, security, and observability Own end-to-end delivery, operational runbooks, and metrics-driven measurement of feature impact and system reliability WHAT'S REQUIRED Bachelor’s degree in computer science, software engineering, or a related technical field Minimum 5+ years of professional experience building backend systems and production services Demonstrated experience designing and operating large-scale data engineering pipelines

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

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

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! Every major NVIDIA silicon product family—from the chips powering AI and datacentre systems to gaming, professional, embedded, and automotive platforms—passes through our productization work on its way to production. NVIDIA’s Silicon Co-Design Productization team works from pre-silicon strategy and feature development through bring-up, characterization, correlation, and optimization. Our charter spans power & performance modelling, bring up & tuning of low-power features, power & thermal controllers , and system-level optimization that ultimately shape how NVIDIA products are configured, binned, specified, and shipped. What you'll be doing Drive silicon power productization from pre-silicon planning through bring-up and production, including test strategy, feature readiness, characterization, and optimization. Partner with architecture and design teams to identify improvements, validate features, and help translate them into production-ready solutions. Correlate measured silicon behaviour with pre-silicon expectations, investigate gaps, and drive complex issues to root cause. Build power and performance models and characterization methodologies that decide silicon binning, product specifications, productization decisions, and customer guidance. Use AI/ML and data-driven methods to analyse characterization & telemetry data, identify anomalies & trends , and accelerate issue debug across silicon, board, power delivery, firmware,

Title: Senior AI QA Engineer Location: Bengaluru (Bangalore) Opportunity: As a Senior AI QA Engineer for our Precision Patient Care Pipeline , you will go beyond traditional functional testing. You will be responsible for building the framework that ensures our clinical insights are accurate, safe, and reliable. This role requires a unique blend of high-level software testing and data engineering to validate complex, non-deterministic medical outputs using a hybrid of automated grading methodologies . Key Responsibilities: Architect Multi-Layered Validation Frameworks: Design and implement structured testing strategies that combine deterministic checks, semantic similarity metrics, and model-based evaluations. Automated Model Grading: Develop systems to evaluate clinical pipeline outputs for faithfulness, safety, and hallucination detection using various automated scoring techniques (e.g., BERTScore, ROUGE, or custom heuristics). Vibe-Driven Development: Leverage agentic AI tools to rapidly prototype complex test harnesses, "red-team" clinical logic, and build internal validation utilities at high velocity. Data Pipeline Integrity: Execute integration and regression tests for data-heavy backend processes, ensuring medical data remains consistent from ingestion to insight generation. Collaborative Strategy: Work closely with Data Scientists and Product Managers to define "Ground Truth" datasets and clinical evaluation rubrics. Root Cause Analysis: Deep-dive into complex system failures to identify whether issues stem from code logic, data drift, or model behavior. Requirements: 6+ years of technical experience in Quality Assurance, with a strong focus on system architecture and backend data validation. Advanced Python Proficiency: Expert-level skills in Python for building custom test scripts and working within AI/ML ecosystems. AI/ML Validation Experience: Proven experience testing model outputs using diverse metrics (e.g., Semantic Similarity, NLP metrics, an

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! You will join the team as a Software Developer , responsible for designing, building, and maintaining scalable backend systems and APIs that power web and mobile applications. The role requires proficiency in backend engineering, cloud services (preferably AWS), databases , and developing secure, high-performance systems . You’ll work closely with software developers, product managers, and cross-functional teams to deliver reliable, secure, and performant services that enable seamless user experiences 1. Solution Design & Development Design, develop, and maintain innovative, customer-centric, high-performance, secure, and robust applications. Build and integrate scalable backend services with responsive frontend interfaces. Work with architects and other software engineers to develop scalable solutions 2. System Decomposition & Iterative Delivery Break down large, complex systems into smaller, manageable implementation slices. Use prototypes and iterative delivery to de-risk unknowns and validate assumptions. 3.

Position Overview We are looking for a Software Engineer II to build and deliver scalable software solutions across our products. You will work on modern web applications and cloud-based services using Node.js, React, TypeScript, AWS, PostgreSQL, MSSQL, and Docker, while contributing to AI-enabled features and integrations. You will collaborate closely with other engineers, product managers, and cross-functional teams to develop reliable, maintainable, and production-ready solutions. This role provides an opportunity to work with modern AI technologies including Python, AWS Bedrock, MCP, RAG, and agentic AI workflows while developing strong expertise in cloud-native software engineering. What You'll Do Develop and maintain scalable backend services and APIs using Node.js, TypeScript, and JavaScript. Build responsive and maintainable frontend applications using React. Design and implement integrations with AWS services and contribute to cloud-native application development. Develop and maintain applications using PostgreSQL and MSSQL, including writing efficient queries and working with database schemas. Build, test, and deploy applications using Docker and modern CI/CD practices. Contribute to AI-enabled product features using Python, AWS Bedrock, RAG, MCP, and AI integration patterns. Work with the team to integrate LLM capabilities, APIs, tools, and data sources into production applications. Write clean, maintainable, and well-tested code following established engineering practices. Participate in code reviews, technical discussions, debugging, and production issue resolution. Develop unit and integration tests and contribute to improving application quality and reliability. Monitor application performance and troubleshoot issues across development and production environments. Collaborate with senior engineers and architects to implement technical solutions aligned with product and engineering requirements. Stay current with emerging technologies, particularly in

Required Skills: Core Java: Strong understanding of Java SE, including OOP concepts, data structures, and algorithms. Frameworks: Experience with popular Java frameworks such as Spring and Hibernate. Web Technologies: Knowledge of web technologies including JSP, Servlets, HTML, CSS, and JavaScript. Database Management: Proficiency in working with relational databases like MySQL, PostgreSQL, or Oracle, including SQL queries and optimization. Version Control: Experience with version control systems like Git, including branching, merging, and pull requests. Build Tools: Familiarity with build tools like Maven or Gradle. RESTful Services: Ability to design and consume RESTful web services and APIs. Testing: Experience with unit testing frameworks like JUnit or TestNG. Problem-Solving: Strong analytical and problem-solving skills with the ability to troubleshoot and resolve complex issues. Preferred Skills: Spring Boot: Experience with Spring Boot for creating microservices. ORM: Proficiency with Object-Relational Mapping (ORM) tools like Hibernate or JPA. Frontend Technologies: Basic knowledge of frontend frameworks like Angular, React, or Vue.js. Cloud Platforms: Experience with cloud platforms such as AWS, Azure, or Google Cloud. Continuous Integration/Deployment (CI/CD): Familiarity with CI/CD tools such as Jenkins or GitLab CI. Microservices Architecture: Understanding of microservices architecture and containerization with Docker. Qualifications: Education: Bachelor’s degree in Computer Science, Information Technology, or a related field. Experience: 2-4 years of professional experience in Java development. Personal Attributes: Team Player: Ability to work collaboratively in a team environment. Communication: Strong verbal and written communication skills. Attention to Detail: High attention to detail and a commitment to delivering high-quality software. Adaptability: Ability to adapt to new technologies and changing requirements.

Technical Skills: Java Programming: Solid understanding of core Java concepts such as OOP (Object-Oriented Programming), data structures, exception handling, multithreading, and collections. Java Frameworks: Basic experience with popular Java frameworks like Spring and Hibernate. Familiarity with Spring Boot for developing microservices is a plus. Web Technologies: Basic knowledge of web development technologies including HTML, CSS, and JavaScript. Exposure to frontend frameworks like Angular or React is advantageous. Databases: Understanding of relational database concepts and basic SQL. Experience with databases such as MySQL or PostgreSQL. Version Control: Familiarity with Git and basic version control concepts, such as branching and merging. Build Tools: Experience with build tools like Maven or Gradle for project management and dependencies. Integrated Development Environment (IDE): Proficiency in using IDEs like IntelliJ IDEA, Eclipse, or NetBeans for Java development. RESTful Web Services: Basic understanding of RESTful services and APIs. Experience in creating simple RESTful APIs is beneficial. Testing: Exposure to unit testing frameworks like JUnit or TestNG. Understanding of basic test-driven development (TDD) practices. Agile Methodology: Basic understanding of Agile software development practices, including working within a team using Scrum or Kanban. Soft Skills: Problem-Solving: Ability to analyze problems and develop logical solutions, with a willingness to learn and adapt to new challenges. Communication: Good verbal and written communication skills, with the ability to articulate technical concepts to both technical and non-technical audiences. Team Collaboration: Experience working in a team environment, contributing to collaborative projects, and participating in code reviews. Time Management: Ability to manage time effectively, prioritize tasks, and meet deadlines. Attention to Detail: Strong attention to detail, ensuring code quality and