Model Behavior Engineer Jobs

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you'll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads — LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You're helping teams reach outcomes most engineers can't on their own. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and optimize production AI workloads

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. You'll build the agentic AI system that powers creation for millions of Roblox creators. The Assistant team is converging Studio Assistant (desktop) and Build (mobile) into a single cloud-native architecture — one harness, one tool set, one eval framework. You'll work across the full stack: cloud orchestration, LLM integration and model routing, tool/skill execution, and the creator-facing client. The system orchestrates multi-step creation workflows end-to-end: planning, code generation, asset creation, and automated testing. You Will: Help and understand the needs of the community that uses our software, from beginning artists to professional scripters and designers. Take ownership and responsibility for designing, building, testing, and deploying services within the Roblox ecosystem. Work on a variety of unique technical challenges within complex systems. Be a technical bar-raiser for high code quality, architectural designs, and long-term planning. Develop fellow engineers on the team. You Have: 5+ years of experience shipping high-complexity software and supporting mission-critical applications at scale. Experience architecting, designing, and leading implementation across a wide range

We are looking to speak to candidates who are based in Gurugram for our hybrid working model. About the Role We are looking for a Staff Integration Engineer (Workato & API Integration) to join our GTMTech team. This strategic role will lead the design, implementation, and governance of enterprise-grade integrations that power our core business processes across GTM systems, with a primary focus on Workato-based integrations and modern API management patterns. You will own the architecture for critical integration domains such as Quote-to-Cash and other high-impact GTMTech programs, ensuring our integration landscape is scalable, secure, observable, and aligned with best practices for event-driven and API-first designs. You will partner with engineering, architecture, security, and business stakeholders to define standards, mentor other integration engineers, and drive continuous improvement in how we connect systems and data. The GTMTech team is focused on high-impact, large-scale technology programs, such as Quote-to-Cash. Our mission is to enhance company efficiency, boost profitability, and enable data-driven decision-making by streamlining systems, optimizing processes, and minimizing manual, low-value work through automation and AI. Key Responsibilities Lead the end-to-end architecture, design, and implementation of Workato-based integrations and APIs across GTM systems (e.g., Salesforce, NetSuite, HRIS, Google Workspace) with a focus on scalability, reliability, and security Define and evolve integration standards, patterns, and best practices, including canonical integration patterns, error-handling strategies, observability, and operational runbooks Design and review complex, event-driven integration workflows leveraging technologies such as Kafka or equivalent messaging platforms, ensuring robust handling of topics, producers/consumers, durability, and retry mechanisms Drive API-first and MCP-native design for GTM integrations, leveraging RESTful APIs al

MongoDB is seeking a Senior Director to provide global program leadership across our PoD Program — the operating model supporting our most strategic global accounts as well as to lead global program management for our AI, Digital Native, and Acquisition account segments. This is a highly cross-functional, strategic role at the intersection of sales strategy, revenue operations, and go-to-market execution. The ideal candidate is a systems thinker who can architect scalable program frameworks, translate data into actionable whitespace and account strategy, and align Product, Services, Sales, and Partner organizations around a shared playbook for growth in our highest-priority accounts and fastest-growing segments. You will operate as the connective tissue between field sales leadership, account teams, and corporate functions — ensuring our most important customers and our highest-growth segments receive consistent, best-in-class coverage models, sizing, and go-to-market motions. We are interested in speaking with candidates who are based out of Austin, New York, and San Francisco Role Responsibilities Strategic Account Program Leadership (PoD) Own the end-to-end operating cadence for the PoD program covering MongoDB's most strategic global accounts Partner with global account leaders to ensure consistent program governance, executive reporting, and cross-regional alignment Serve as the central point of coordination for account planning cycles, QBRs, and executive engagement across PoD accounts Segmentation Design and continuously refine global account segmentation frameworks across strategic, AI/Digital Native, and Acquisition accounts Ensure segmentation logic reflects growth potential, product fit, and strategic value, and is consistently applied across regions Whitespace Analysis Build repeatable whitespace analysis methodologies to identify expansion opportunities within existing accounts and adjacent buying centers Partner with sales and analytics teams to operat

We are looking to speak to candidates who are based in Gurugram for our hybrid working model. About the Role We are looking for a Senior Workato Integration Engineer to join our GTMTech team. This critical role involves developing, deploying, and supporting GTMTech’s integrations, which are essential for core business operations. The GTMTech team is focused on high-impact, large-scale technology programs, such as Quote-to-Cash. Our mission is to enhance company efficiency, boost profitability, and enable data-driven decision-making by streamlining systems, optimizing processes, and minimizing manual, low-value work through automation and AI. Key Responsibilities Automate, develop, and support integrations across various business systems, platforms, and tools Work closely with different business units and technical teams to gather requirements and design solutions Use your integration expertise to create scalable solutions and operationalize integrations. Implement and promote integration best practices Participate in on-call support rotation Champion and role model MongoDB’s culture principles—Think Big, Make it Happen, Build Together, and Be Intellectually Honest—as we scale globally and grow our presence in new regions and offices Qualifications Bachelor's or Masters in Computer Science, Engineering or related field with 5+ years of enterprise integration experience At least 3 years of experience in integration development using platforms such as Workato, Mulesoft, Boomi, etc Deep understanding of enterprise integration design patterns, messaging, and event-driven architectures and Workato concepts like callable recipes, event streams, task optimization etc Proficient with various Workato connectors (but not limited to) like Salesforce, Netsuite, HRIS and Google AppSuite along with expertise in Python/Ruby scripting skills Strong development experience implementing Workato at scale - including automation, observability/monitoring, debugging skills in complex envir

We are looking to speak to candidates who are based in Gurugram for our hybrid working model. About MongoDB The database market is massive, and MongoDB is at the head of its disruption. The MongoDB community is transforming industries and empowering developers to build amazing applications that people use every day. We are the leading modern data platform and continue to innovate at scale to support our customers and internal teams with world-class systems and experiences. About Team IT SaaS Engineering Team plays a critical role in optimizing MongoDB sales processes, streamlining customer interactions, and maximizing the efficiency of our sales efforts. By leveraging Salesforce, the team ensures that business users have the tools, automation, security, and governance needed to effectively manage customer relationships, support operational processes, and drive business growth. With deep expertise in Salesforce administration, platform governance, automation, and system operations, the team continuously enhances the Salesforce CRM platform to meet evolving business needs. The team partners closely with stakeholders across Sales Operations, Revenue Operations, Security, Compliance, and Engineering to deliver scalable, secure, and reliable Salesforce solutions. What you’ll do We are looking for a Senior Salesforce Administrator to manage and enhance the Salesforce CRM system supporting MongoDB’s Sales organization. Effectively work both autonomously and collaboratively across Salesforce platform administration, configuration, release support, security, and audit-related activities. Work closely with Tech Leads, Program Managers, Developers, DevOps teams, and Business Stakeholders to understand requirements and deliver scalable declarative solutions. Contribute across multiple functions including platform administration, CI/CD participation, release support, access governance, security improvements, and audit readiness. Ensure appropriate controls, documentation, and go

We are looking to speak to candidates who are based in Seoul for our hybrid working model. About the role MongoDB Engagement Managers are quota-carrying Professional Services Sales roles. Engagement managers utilize customer-facing sales, technical, consulting, and commercial experience to scope, negotiate and close Professional Services opportunities to accelerate and de-risk the adoption of MongoDB by our customers. As an Engagement Manager, you will be a key leader within the PS team and work cross-functionally with the Sales, Professional Services, and Customer Success organizations to drive professional services sales. Here are a few informative blogs about the Engagement Management role: https://www.mongodb.com/blog/post/engagement-management-mongodb-meet-lalitesh-pal https://www.mongodb.com/blog/post/how-engagement-managers-help-customers-succeed What you will be doing Understand customers’ overall portfolio of applications and datasets, IT and business priorities and success measures to adapt, develop and design specific digital transformation approaches involving MongoDB technologies Help transform companies by translating their use-cases, pains, and needs into scoped projects and statements of work Partner with a best-in-class sales organization and work effectively as a part of a larger team to develop account strategies and plans for the successful adoption, growth, and utilization of MongoDB Have a solid sense of ownership, driving all deals or technical scopings from inception to closure Manage the Professional Services pipeline for bookings and revenue forecasts for your region Expertly articulate the business value of professional services, talking knowledgeably and credibly about service delivery issues, challenges, strategies, approaches, and mitigating risks Work with our practice team to propagate internal skills and experience through the development of repeatable assets (estimates, proposals, SOWs, templates, tools, case studies etc.) Wor

We are looking to speak to candidates who are based in Bengaluru for our hybrid working model. Why MongoDB is a fantastic place to work and build your career Be a part of the company that’s reinventing the database, focused on innovation and speed Enjoy a fun, inspiring culture that is engineering focused Work with talented people around the globe Learn, contribute, and make an impact on the product and community Cool things you’ll do Our Cloud Associate TSE 1’s form the front line of our cloud support team, directly responding to questions from our customers on areas such as connectivity, the availability of the Atlas service and questions about the UI or platform features. You will also be working with our engineering teams to escalate more complex customer problems. It's crucial that you ensure that questions are answered quickly and accurately and that our customers get the help they need, regardless of who provides the answers in the end. Our team combines their MongoDB expertise with passion, initiative, teamwork and a great sense of humour to help our customers to be successful with MongoDB around the globe. If you’re passionate about the opportunity to get comfortable working with the cloud every single day and be part of a team that works at the frontier of SaaS services and database systems, this is the role for you. Responsibilities Associate TSE 1’s will be successful in this role when they can execute the following strategic tasks/responsibilities Customer Service: Provide an unparalleled customer experience Investigate customer’s technical issues to find solutions, discover and report bugs Review and test new features before they are publicly available Following the successful completion of the probationary period, the candidate ​may be required to work a Tuesday-to-Saturday schedule, with Sundays and Mondays designated as weekly days off. What we’re looking for We consider all candidates with an eye for those who are self taught, curious, and multi-fa

About the Team The Recursive Self-Improvement (RSI) team works across research, engineering, product, and infrastructure to build AI systems that accelerate and ultimately conduct high-quality research at OpenAI. We work to automate real research workflows and improve research productivity by building systems and feedback loops, designing evaluations, and training models to develop missing capabilities. Our work spans the full lifecycle of model training, evaluation, and deployment to help researchers move faster and tackle increasingly ambitious problems. About the Role We’re hiring research scientists , research engineers , and AI systems engineers to work on automating research at OpenAI. This role is based in San Francisco, CA. In this role, you will: Design evaluations for research judgment, hypothesis generation and testing, and long-horizon experiment execution. Turn real research workflows and model failures into data and evaluation flywheels. Improve model research capabilities through agent harnesses, synthetic data, RL environments, and model training. Build and maintain safe, reliable integrations between our models and OpenAI’s research infrastructure. Develop research agents, experiment-orchestration systems, and sandboxed runtimes that support real research workflows. Create metrics and economic models to understand RSI’s current and future effects on research productivity, model capabilities, and the safety of internal deployments. This is a high-ownership role for researchers and engineers who thrive in ambiguity, move fluidly between research and implementation, and turn emerging opportunities into rigorous, reliable, scalable results. You might thrive in this role if you: Have research or engineering experience across LLM training, model evaluations, agent systems, synthetic data, research infrastructure, or large-scale distributed systems. Are a strong generalist who can move between open-ended research and practical implementation, turning ambig

Overview: The Data Acquisition team within the Foundations organization at OpenAI is responsible for all aspects of data collection to support our model training operations. Our team manages web crawling and GPTBot services and works closely with Data Processing, Architecture, and Scaling teams. We are looking for a skilled Software Engineer to join our Data Acquisition team. Responsibilities: Own and lead engineering projects in the area of data acquisition including web crawling, data ingestion, and search. Collaborate with other sub-teams, such as Data Processing, Architecture, and Scaling, to ensure smooth data flow and system operability. Work closely with the legal team to handle any compliance or data privacy-related matters. Develop and deploy highly scalable distributed systems capable of handling petabytes of data. Architect and implement algorithms for data indexing and search capabilities. Build and maintain backend services for data storage, including work with key-value databases and synchronization. Deploy solutions in a Kubernetes Infrastructure-as-Code environment and perform routine system checks. Conduct and analyze experiments on data to provide insights into system performance. Qualifications: BS/MS/PhD in Computer Science or a related field. 4+ years of industry experience in software development. Experience with large web crawlers a plus Strong expertise in large stateful distributed systems and data processing. Proficiency in Kubernetes, and Infrastructure-as-Code concepts. Willingness and enthusiasm for trying new approaches and technologies. Ability to handle multiple tasks and adapt to changing priorities. Strong communication skills, both written and verbal. 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

About the Team Training Runtime designs the core distributed machine-learning training runtime that powers everything from early research experiments to frontier-scale model runs. With a dual mandate to accelerate researchers and enable frontier scale, we’re building a unified, modular runtime that meets researchers where they are and moves with them up the scaling curve. Our work focuses on three pillars: high-performance, asynchronous, zero-copy tensor and optimizer-state-aware data movement; performant, high-uptime, fault-tolerant training frameworks (training loop, state management, resilient checkpointing, deterministic orchestration, and observability); and distributed process management for long-lived, job-specific and user-provided processes. We integrate proven large-scale capabilities into a composable, developer-facing runtime so teams can iterate quickly and run reliably at any scale, partnering closely with model-stack, research, and platform teams. Success for us is measured by raising both training throughput (how fast models train) and researcher throughput (how fast ideas become experiments and products). About the Role As a Training: ML Framework Engineer, you will work on improving the training throughput for our internal training framework, while enabling researchers to experiment with new ideas. This requires good engineering (for example designing, implementing, and optimizing state-of-the-art AI models), writing bug-free machine learning code (surprisingly difficult!), and acquiring deep knowledge of the performance of supercomputers. In all the projects this role pursues, the ultimate goal is to push the field forward. We’re looking for people who love optimizing performance, understanding distributed systems, and who cannot stand having bugs in their code. Since our training framework is used for large runs with massive numbers of GPUs, performance improvements here will have a large impact. This role is based in San Francisco, CA. We use a

Overview: The Data Acquisition team within the Foundations organization at OpenAI is responsible for all aspects of data collection to support our model training operations. Our team manages web crawling and GPTBot services and works closely with Data Processing, Architecture, and Scaling teams. We are looking for a skilled Full-Stack Engineer to join our Data Acquisition team to build and optimize the interfaces and tools that power our data infrastructure. Responsibilities: Develop and maintain full-stack applications that support data acquisition, including internal tools and dashboards. Collaborate closely with cross-functional teams, including Data Processing, Architecture, and Scaling, to ensure seamless data ingestion and workflow management. Design and implement APIs to facilitate data interactions between internal services and external data sources. Enhance user experience by developing intuitive web-based interfaces for managing and monitoring data pipelines. Optimize backend services for performance, scalability, and security in a distributed computing environment. Work with legal and compliance teams to ensure our data acquisition processes adhere to privacy regulations and best practices. Deploy and maintain infrastructure using Kubernetes and Infrastructure-as-Code (IaC) methodologies. Analyze system performance, conduct experiments, and improve data workflows to maximize efficiency. Qualifications: BS/MS/PhD in Computer Science or a related field. 4+ years of industry experience in full-stack development. Proficiency in frontend frameworks (React, Vue, or similar) and backend technologies such as Python, Node.js, or Go. Strong expertise in RESTful APIs, GraphQL, and database design (SQL and NoSQL). Experience building data-intensive applications that handle large-scale datasets. Familiarity with cloud platforms (AWS, GCP, or Azure) and container orchestration (Kubernetes, Docker). Prior experience with web crawling and large-scale data processing is a

About the Team OpenAI's Training team is responsible for producing the large language models that power our research, our products, and ultimately bring us closer to AGI. Achieving this goal requires combining deep research into improving our current architecture, datasets and optimization techniques, alongside long-term bets aimed at improving the efficiency and capability of future generations of models. We are responsible for integrating these techniques and producing model artifacts used by the rest of the company, and ensuring that these models are world-class in every respect. Recent examples of artifacts with major contributions from our team include GPT4-Turbo, GPT-4o and o1-mini. About the Role As a member of the architecture team, you will push the frontier of architecture development for OpenAI's flagship models, enhancing intelligence, efficiency, and adding new capabilities. Ideal candidates have a deep understanding of LLM architectures, a sophisticated understanding of model inference, and a hands-on empirical approach. A good fit for this role will be equally happy coming up with a creative breakthrough, investing in strengthening a baseline, designing an eval, debugging a thorny regression, or tracking down a bottleneck. This role is based in San Francisco. 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: Design, prototype and scale up new architectures to improve model intelligence Execute and analyze experiments autonomously and collaboratively Study, debug, and optimize both model performance and computational performance Contribute to training and inference infrastructure You might thrive in this role if you: Have experience landing contributions to major LLM training runs Can thoroughly evaluate and improve deep learning architectures in a self-directed fashion Are motivated by safely deploying LLMs in the real world Are well-versed in the state of the art tran

About the Team Training Runtime designs the core distributed machine-learning training runtime that powers everything from early research experiments to frontier-scale model runs. With a dual mandate to accelerate researchers and enable frontier scale, we’re building a unified, modular runtime that meets researchers where they are and moves with them up the scaling curve. Our work focuses on three pillars: high-performance, asynchronous, zero-copy tensor and optimizer-state-aware data movement; performant, high-uptime, fault-tolerant training frameworks (training loop, state management, resilient checkpointing, deterministic orchestration, and observability); and distributed process management for long-lived, job-specific and user-provided processes. We integrate proven large-scale capabilities into a composable, developer-facing runtime so teams can iterate quickly and run reliably at any scale, partnering closely with model-stack, research, and platform teams. Success for us is measured by raising both training throughput (how fast models train) and researcher throughput (how fast ideas become experiments and products). About the Role As a Training Performance Engineer, you’ll drive efficiency improvements across our distributed training stack. You’ll analyze large-scale training runs, identify utilization gaps, and design optimizations that push the boundaries of throughput and uptime. This role blends deep systems understanding with practical performance engineering — analyzing GPU kernel performance, collective communication throughput, investigating I/O bottlenecks, and sharding our models so we can train them at massive scale. You’ll help ensure that our clusters are running at peak performance, enabling OpenAI to train larger, more capable models with the same compute budget. This role is based in San Francisco, CA. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you will: Profil

About the Team The Cooperative AI team is scaling OpenAI with OpenAI. We are building a model powered knowledge system that evolves and learns as our products, systems and customers evolve. We leverage our state of the art models, technologies, and products (some external, some still in the lab) to assist or completely automate robust operations supporting both internal and external customers. We support OpenAI customers and internal partners globally, powering systems from customer support to integrity to product insights. We are a self-contained multi-disciplinary team, who enjoy a lightning fast feedback loop with customers at scale, some of whom sit just a few pods away. We iterate fast, and engineer for reliable long-term impact. We're constantly looking for the similarities and patterns in different types of work, and focus on building simple primitives, to apply world class knowledge to many domains. The work of this team exemplifies use of OpenAI technologies. We build systems so everyone can see the leverage that is possible with well designed AI-based implementations. We do this by working through internal use cases focused on Customers (specifically knowledge systems, automation systems, and automated agent systems) to prove impact, then we scale. About the Role We’re looking for a Backend Software Engineer to help architect and scale the infrastructure that powers our knowledge systems. 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. In this role, you will: 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 product, research, and engineering teams to integrate OpenAI mode