Software Engineer Ml Inference Platform Salary India in United States

The ML Observability team builds cutting-edge tools to monitor, explain, and improve AI systems in production, particularly those leveraging Large Language Models (LLMs) and generative AI. We provide robust, scalable observability for AI workloads, including drift detection and model evaluation, and behavior tracing, enabling customers to ship AI with confidence. As a Staff Engineer, you’ll lead the development of new features and foundational capabilities within Datadog’s LLM Observability product. You will shape product direction, drive experimentation, and apply your deep understanding of both AI systems and software engineering to solve open-ended problems in the fast-moving AI landscape. Your work will directly impact how our customers monitor, troubleshoot, and optimize LLM-based applications in production. Join us in building the foundational tools that make AI systems observable, understandable, and reliable in the real world. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Drive design and implementation of LLM observability features. Ideate, prototype, and scale new product features to provide insights and drive improvements for generative AI systems Work cross-functionally with other eng teams, product, UX, and applied science to iterate fast and find product-market fit Develop and extend tools for tracing, evaluating, and debugging LLMs Influence architecture decisions and mentor engineers to build resilient, high-performance systems Stay close to customer pain points and use those insights to guide product and engineering priorities Stay current with industry trends and advancements in machine learning and observability, driving innovation within the team Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or r

We’re looking for a Staff Software Engineer with deep experience in GenAI/ML to join Datadog’s Application Performance Monitoring (APM) team. APM is a product which provides deep visibility into applications, enabling users to identify performance bottlenecks, troubleshoot issues, and optimize services. With distributed tracing, profiling, out-of-the-box dashboards, and seamless correlation with other telemetry data, Datadog APM provides some of the deepest and most structured visibility into the health and performance of applications. This context sets us up for an opportunity to be the world leaders in agentic investigations and incident troubleshooting. You’ll act as a technical leader within the APM group, focused on agentic workflows. You’ll lead efforts to design, train, evaluate, and deploy GenAI/ML models at scale. We’re looking for a product-minded ML engineer with strong technical expertise, excellent communication skills, and a track record of driving impactful initiatives end to end. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Act as a technical leader within the APM organization, driving GenAI/machine learning projects from concept to production. Build and benchmark GenAI/ML models using state-of-the-art techniques. Collaborate with cross-functional teams to build automated investigation and triaging tools. Influence product direction by bringing a strong product mindset to your work, always advocating for the end user. Guide teams through ambiguity, scaling challenges, and evolving requirements with clear technical direction. Actively mentor engineers and influence engineering culture through leadership in design reviews, technical talks, and working groups. Who You Are: You have a BS/MS/PhD in a scientific field or equiva

We’re looking for a Senior Staff Software Engineer with deep experience in GenAI/ML to join Datadog’s Application Performance Monitoring (APM) team. APM is a product which provides deep visibility into applications, enabling users to identify performance bottlenecks, troubleshoot issues, and optimize services. With distributed tracing, profiling, out-of-the-box dashboards, and seamless correlation with other telemetry data, Datadog APM provides some of the deepest and most structured visibility into the health and performance of applications. This context sets us up for an opportunity to be the world leaders in agentic investigations and incident troubleshooting. You’ll act as a technical leader within the APM group, focused on agentic workflows. You’ll lead efforts to design, train, evaluate, and deploy GenAI/ML models at scale. We’re looking for a product-minded ML engineer with strong technical expertise, excellent communication skills, and a track record of driving impactful initiatives end to end. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Serve as the technical owner for GenAI initiatives within APM, leading design, development, and deployment of ML/AI-powered features across multiple teams. Guide long-term strategy and technical direction for GenAI workflows across APM and related products. Build and benchmark GenAI/ML models using state-of-the-art techniques. Contribute to Datadog’s broader senior engineering community through thought leadership and collaboration on company-wide initiatives. Collaborate with cross-functional teams to build automated investigation and triaging tools. Influence product direction by bringing a strong product mindset to your work, always advocating for the end user. Guide teams through ambiguity, sc

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. Who We Are: Shape the future of Roblox’s virtual economy. The Economy ML team is building the machine learning backbone that powers Roblox’s Marketplace, Developer Monetization, and Payments ecosystems. From intelligent pricing and personalized storefronts to dynamic layout optimization and avatar understanding, we’re reimagining how the Roblox economy drives user engagement, monetization, and creator success at scale. As a Principal Software Engineer (Data Systems) , you will architect, build and deploy high-scale, reliable real-time and batch data systems for personalization, search and recommendation across various product surfaces in Marketplace, Developer Monetization and Payments. You will be involved in key data projects from architecting event taxonomies and logging interfaces to real-time feature serving across multiple search and recommendation surfaces. What You’ll Do Act as data engineering lead for Economy ML, setting standards for batch vs streaming feature pipelines, table design, observability, and documentation used across the Economy group. Work as a hands-on contributor on our data systems to power content recommendation, search and personalization across Economy product

About the Team: GTM Innovation is a product engineering team with a charter to automate 100% of digital knowledge work in OpenAI's GTM, so sellers spend more time directly with customers. AGI-level reasoning doesn’t mean organization-level transformation “just works” out of the box; orgs must be redesigned around abundant intelligence and persistent virtual coworkers. Our team builds and scales a fleet of virtual coworkers that operate as full-time members of the account team, and redefines how our human-first revenue organization interacts with their agentic teammates. About the Role We’re looking for backend software engineers with a product mindset to join the GTM Innovation team. You’ll help OpenAI meet the world at scale. You’ll partner closely with go-to-market teams to understand their workflows, identify leverage points, and ship novel solutions using OpenAI’s API platform. You’ll move quickly from prototype to production, and your work will directly shape how customers experience our technology in the field. This role is ideal for engineers who want to be close to users, own end-to-end outcomes, and help define entirely new categories of enterprise software. In this role, you will: Build high-impact applications and tools that accelerate OpenAI’s go-to-market efforts Work across the full product lifecycle for GTM: prototype, iterate, ship, and maintain Embed with Sales, Technical Success, and Revenue Operations to identify user needs and build for them Apply OpenAI’s models in novel ways to solve real-world customer and internal workflow problems Translate learnings into feedback for Applied and Research teams to inform product development You’ll thrive in this role if you: Have 4+ years of experience as a software/ML/product engineer working on user-facing systems Former founder, or early engineer at a startup who built a product from scratch is a plus Are fluent in Python or JavaScript and comfortable building full-stack applications Have built or prototy

About the Team: GTM Innovation is a product engineering team with a charter to automate 100% of digital knowledge work in OpenAI's GTM, so sellers spend more time directly with customers. AGI-level reasoning doesn’t mean organization-level transformation “just works” out of the box; orgs must be redesigned around abundant intelligence and persistent virtual coworkers. Our team builds and scales a fleet of virtual coworkers that operate as full-time members of the account team, and redefines how our human-first revenue organization interacts with their agentic teammates. About the Role We’re looking for Full Stack software engineers with a product mindset to join the GTM Innovation team. As a product engineer on this team, you’ll help OpenAI meet the world at scale. You’ll partner closely with go-to-market teams to understand their workflows, identify leverage points, and ship novel solutions using OpenAI’s API platform. You’ll move quickly from prototype to production, and your work will directly shape how customers experience our technology in the field. This role is ideal for engineers who want to be close to users, own end-to-end outcomes, and help define entirely new categories of enterprise software. In this role, you will: Build high-impact applications and tools that accelerate OpenAI’s go-to-market efforts Work across the full product lifecycle for GTM: prototype, iterate, ship, and maintain Embed with Sales, Technical Success, and Revenue Operations to identify user needs and build for them Apply OpenAI’s models in novel ways to solve real-world customer and internal workflow problems Translate learnings into feedback for Applied and Research teams to inform product development You’ll thrive in this role if you: Have 4+ years of experience as a software/ML/product engineer working on user-facing systems Former founder, or early engineer at a startup who built a product from scratch is a plus Are fluent in Python or JavaScript and comfortable building full-s

About the Team The OpenAI Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role As a Senior Software Engineer, ML Systems & Training Infrastructure, you will be a deeply hands-on engineering force multiplier for the robotics team. You will help keep the training framework and surrounding infrastructure healthy, review and improve code quickly, debug failures across ML systems and infrastructure, and unblock researchers and engineers when the path from idea to working training job gets rough. We’re looking for people who love writing, reading, reviewing, and fixing code; who can get productive quickly in unfamiliar systems; and who bring strong practical judgment without a lot of ego or process overhead. This role will be based in San Francisco, CA and be expected in office 5 days per week and offer relocation assistance to new employees. In this role, you will: Review, improve, and clean up code across training frameworks and adjacent infrastructure. Identify risky or low-quality changes before they land, and raise the code quality bar without slowing the team down. Debug issues across ML training systems, GPUs, clusters, networking, and related infrastructure. Help researchers and engineers unblock broken training jobs, flaky workflows, and brittle internal tooling. Improve the reliability, maintainability, and usability of the robotics team’s training framework. Move quickly on practical engineering problems that directly affect team velocity. You might thrive in this role if you: Have strong software engineering fundamentals and excellent code review judgment. Have experience with ML systems, training fr

About the Team The Monetization team is a new cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products—including next-generation ads experiences—that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to help build the machine learning infrastructure that powers OpenAI’s monetization and ads systems. In this foundational role, you’ll design and develop the platform layer that enables teams to build, train, deploy, serve, monitor, and continuously improve machine learning models used across advertising and monetization products. You’ll work across the full ML lifecycle, from large-scale data pipelines and feature infrastructure to training systems, model serving, experimentation platforms, and monitoring frameworks. The systems you build will support high-throughput, low-latency advertising workloads while maintaining strict standards for reliability, privacy, security, and performance. This role sits at the intersection of machine learning systems, distributed infrastructure, and monetization, offering the opportunity to shape the core platforms that help translate model innovation into m

About the Team The Support Automation team at OpenAI scales the organization by applying cutting-edge AI models to real-world challenges, automating and enhancing work across the organization. From customer operations to engineering, we develop an ecosystem of automation products that empower our colleagues and drive impact. We're passionate about crafting products that serve those around us, blending rapid prototyping with a focus on long-term quality and reliability. By creating reusable solutions, we create patterns that can be applied across diverse domains within OpenAI. TLDR: this team leverages OpenAI technology to improve OpenAI, and you’ll have the opportunity to leverage the full extent of our tech (both public and pre-released) to accomplish this mission. About the Role We’re looking for a Backend Software Engineer with experience working in ML/LLM-heavy domains to help to design and build an evals infrastructure that measures the quality of OpenAI’s support automation. This is a deeply technical and highly cross-functional role where you’ll build robust systems and backend services that serve as the foundation for how knowledge is created, accessed, and applied across OpenAI. The role will especially focus on working closely with Data Science and Research partners to design and build evals at scale. In this role, you will: Design eval pipelines that are reliable, reproducible, and extendable Build the infrastructure for continuous eval monitoring frameworks (regression/drift monitoring, building robust golden datasets) along with feedback loops that ultimately strengthen support automation Design, build, and maintain backend services and APIs to support intelligent automation and knowledge systems Integrate and structure data across internal platforms, transforming it into formats optimized for use by downstream systems and AI workflows. Collaborate closely with data, research, and engineering teams to integrate OpenAI models into high-leverage workflows

We are developing advanced multi-rack, multi-tenant AI/ML datacenters with NVIDIA GB200, and upcoming GB300 GPUs. NVIDIA seeks a Senior Software Engineer for our CSP (Cloud Service Provider) Engagements team to focus on the cloud-native stack for datacenter products like GB200. In this role, You will define customer workflows, prototype stack enhancements, and debug the toughest Kubernetes + Slurm issues in multi-rack, multi-tenant AI datacenters. You'll tackle complex scheduling challenges across racks, tenants, and clouds as part of the CSP engagements team. What you’ll be doing: Perform deep-dive debugging of multi-rack, multi-tenant clusters: scheduler behavior, container runtime issues, device-plugin crashes, RDMA/IB fabric anomalies, etc. Gather customer requirements and prototype feature extensions for Kubernetes operators, Slurm plugins, and custom micro-services that expose new GPU capabilities. Drive joint architecture reviews and “whiteboard” sessions with CSP and internal platform teams; convert findings into RFCs and upstream pull requests. Create reproducible testbeds (Helm/Ansible/Terraform) that mirror customer environments; automate validation and benchmark suites. Deliver technical collateral-design docs, how-to guides, demo scripts-and present at customer on-sites, KubeCon, and SlurmUG. Collaborate with AE, FAE, and Solution Architect teams to deliver integrated customer solutions and technical documentation. What we need to see: Strong source-level expertise in Kubernetes internals (scheduler, CRI/CNI/CSI, operators) and Slurm (federation, power-save, plugins). Hands-on experience integrating next-gen GPUs (Blackwell/GB200/GB300) or comparable accelerators into containerized clusters. Proven track record debugging large-scale, cloud-native stacks across ne

About the Team Data Platform at OpenAI owns the foundational data stack powering critical product, research, and analytics workflows. We operate some of the largest Spark compute fleets in production; design, and build data lakes and metadata systems on Iceberg and Delta with a vision toward exabyte-scale architecture; run high throughput streaming platforms on Kafka and Flink; provide orchestration with Airflow; and support ML feature engineering tooling such as Chronon. Our mission is to deliver reliable, secure, and efficient data access at scale and accelerate intelligent, AI assisted data workflows. Join us to build and operate these core platforms that underpin OpenAI products, research, and analytics. We’re not just scaling infrastructure – we’re redefining how people interact with data. Our vision includes intelligent interfaces and AI-assisted workflows that make working with data faster, more reliable, and more intuitive. About the Role This role focuses on building and operating data infrastructure that supports massive compute fleets and storage systems, designed for high performance and scalability. You’ll help design, build, and operate the next generation of data infrastructure at OpenAI. You will scale and harden big data compute and storage platforms, build and support high-throughput streaming systems, build and operate low latency data ingestions, enable secure and governed data access for ML and analytics, and design for reliability and performance at extreme scale. You will take full lifecycle ownership: architecture, implementation, production operations, and on-call participation. You’ve supported Spark, Kafka, Flink, Airflow, Trino, or Iceberg as platforms. You’re well-versed in infrastructure tooling like Terraform, experienced in debugging large-scale distributed systems, and excited about solving data infrastructure problems in the AI space. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per wee

About the Team OpenAI’s API Multicloud team is responsible for extending OpenAI’s API platform into strategic cloud environments, starting with AWS . The team’s mission is to distribute OpenAI’s API broadly and safely by enabling key API technologies in cloud-native environments, in close partnership with Amazon and internal teams across Codex, Research, Safety Systems, and Applied. The team is focused on bringing core developer and enterprise capabilities into cloud-native environments, including cloud-hosted Codex, model customization / post-training as a service, and new stateful runtime environments for agentic workloads. This work sits at the intersection of production ML systems, developer platforms, model behavior, and large-scale infrastructure. About the Role We’re looking for a backend engineer who can quickly understand OpenAI’s models, products, and systems, then adapt first-party deployments for other cloud platforms. You’ll build backend services, APIs, SDK integrations, authentication flows, and cloud service infrastructure that let developers use OpenAI capabilities in the cloud environments where they already build. This role involves working across teams, sometimes embedded with partner product groups, to ship products quickly and across multiple platforms at the same time. It’s a strong fit for engineers who have built developer tools, especially AI-powered tools, communicate clearly across technical boundaries, and can shape architectures that support different deployment models; experience building cloud services is a strong plus. In this role, you will: Build backend and infrastructure systems that extend OpenAI’s API platform into cloud-native environments, like AWS. Design and ship cloud-contained products that allow customers to use OpenAI capabilities while keeping workloads and data within cloud environments. Help stand up cloud-hosted Codex experiences powered by the OpenAI Responses API. Build the infrastructure and runtime abstractions

About the Team The Workload Networking team is responsible for the collective communication stack used in our largest training jobs. Using a combination of C++ and CUDA we work on novel collective communication techniques that enable efficient training of our flagship models on our largest custom built supercomputers. The models we train are key ingredients to the AI research progress at OpenAI and the field as a whole, and we continually incorporate learnings from our entire research org into our training platform. About the Role As a Software Engineer, Networking you will design and implement custom networking collectives that are tightly integrated into our training stack. We’re looking for people who have a background in low level performance critical software. Experience with collective communication is a bonus. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Collaborate closely with ML researchers to design and implement efficient collective operations in C++ and CUDA. Ensure that our largest training jobs take full advantage of the different network transports used in our supercomputers. Work on simulations to inform our future supercomputer network designs. You might thrive in this role if you: Have written distributed algorithms using RDMA in the past. Are comfortable writing low level performance sensitive CPU and/or GPU code. Are familiar with network simulation techniques. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voic

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 Data Clean Rooms team is Leading the market shift from traditional 2-party data sharing to multi-party collaboration hubs . Our vision is to provide a seamless, "safe-room" environment where enterprises can collaborate on shared datasets while maintaining absolute governance. We ensure that no party can exfiltrate another's underlying content, even while running complex joint workloads and getting high-value results. You will join a fast-paced, collaborative team of engineers on a journey to provide customers with an integrated set of innovative, AI-enabled capabilities to analyze data in a privacy-preserving way. You will have a real opportunity to impact and shape the future of secure data collaboration at Snowflake. AS A SOFTWARE ENGINEER IN DATA CLEAN ROOMS, YOU WILL: Architect and build highly scalable infrastructure that enables secure, multi-party collaboration. Design and implement core clean room features and services, intelligent agents, and robust developer APIs to expand platform capabilities and support custom AI/ML workflows. Partner closely with Product Management and cross-functional teams to drive complex projects from ideation and system design through to production deployment. Mentor peers and foster a warm, supportive culture of innovation, cross-tea

About the Team The Applied team works across research, engineering, product, and design to bring OpenAI’s technology to the world. We seek to learn from deployment and broadly distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. We aim to make our innovative tools globally accessible, transcending geographic, economic, or platform barriers. Our commitment is to facilitate the use of AI to enhance lives, fostered by rigorous insights into how people use our products. About the Role We are seeking Software Engineers (Emerging Talent) to join our Applied Engineering team. You’ll work in a highly iterative, collaborative, fast-paced environment to bring our technology to millions of users around the world, and ensure it’s delivered with safety and reliability in mind. We value engineers who are self-starters, care deeply about the end user experience, and take pride in building products to solve customer needs. In this role, you will: Own the development of new customer-facing ChatGPT and OpenAI API features and product experiences end-to-end Talk to users to understand their problems and design solutions to address them Collaborate with a cross-functional team of engineers, researchers, product managers, designers, and operations folks to create cutting-edge products Optimize applications for speed and scale Create a diverse and inclusive culture that makes all feel welcome. Your background looks something like: Bachelor's or Master’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 0-1 years of experience in software engineering or a relevant field Proficiency with JavaScript, React, and some backend languages (we use Python) Some experience with relational databases like Postgres/MySQL Interest in AI/ML (direct experience not required) Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadl