Model Designer Jobs

About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About This Role We're looking for a Staff HR Business Partner to build and own the people strategy for Snorkel's Data as a Service (DaaS) organization. This role is hybrid ( 3 days/week in office) in San Francisco, CA . The DaaS org is a delivery-first team that has more than tripled in size over the last six months, with no signs of slowing. They deliver high-quality data operations and AI deployment outcomes for frontier labs and AI teams. This org has a unique composition: forward deployed engineers, technical and operations delivery managers, a supply team managing a workforce comprised of multiple worker types at scale, and others. The people challenges here require an HRBP who has seen this kind of complexity before, such as workforce planning across FTEs and contractors, building a high performance culture rooted in delivery outcomes, and keeping a geographically dispersed, operationally complex team connected to Snorkel's culture. You'll partner directly with our DaaS GM and leadership team, and you'll need to be as comfortable in the operational weeds as you are in strategic conversations. The ideal background is professional services, managed services

Overview: Guidepoint seeks an experienced Data/AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products. This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The Senior AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products. Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services. This is a hybrid position based in Toronto. What You'll Do: Architect and Build Production Systems: Design, build, and operate scalable, low-latency backend services and APIs that serve Generative AI features, from retrieval-augmented generation (RAG) pipelines to complex agentic systems. Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications, including system design, development, deployment (CI/CD), monitoring, and optimization

Overview: Guidepoint seeks an experienced AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products. This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products. Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services. This is a hybrid position based in Toronto. What You'll Do: Architect and Build Production Systems: Design, build, and operate scalable, low-latency backend services and APIs that serve Generative AI features, from retrieval-augmented generation (RAG) pipelines to complex agentic systems. Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications, including system design, development, deployment (CI/CD), monitoring, and optimization in production

About the Team The Cooperative AI team is scaling OpenAI with OpenAI. We are building a model-powered scaled automated workforce and knowledge system that evolves and learns alongside a human workforce. By leveraging OpenAI’s state-of-the-art models and technologies, some already in production, others still in the lab, we develop systems that reason and work autonomously for a wide variety of operational work. We leverage real workloads for critical systems across finance, sales, customer support, integrity, product insights, internal operations, and more in order to drive insights into product and industry. We partner closely with internal teams and external customers globally, operating in a hyper-fast feedback loop where many of our users are just a few steps away. This proximity allows us to iterate quickly, validate impact in real time, and accelerate industry impacting learnings and systems builds. We are a highly multidisciplinary, self-contained team focused on transforming the workplace via smart systems, knowledge, scalable and reliable primitives that apply world-class AI capabilities across domains. Our mission is to learn fast and transform how humans collaborate with AI at scale. About the Role We are looking for a hands-on Engineering Manager to lead a small, fast-moving team building AI-powered automation systems that redefine how work gets done across OpenAI. This role sits at the intersection of applied AI, research, and product engineering. You’ll lead a team that builds systems that know how to learn from humans, and carry real workloads across, sales, support, finance, IT, and more, while staying deeply involved in the technical work. You will operate in a highly iterative environment, deploying systems directly to internal users, gathering rapid feedback, and evolving solutions in real time. This is a high-ownership role for someone excited about building 0→1 systems, working closely with customers, and shaping how AI transforms operational wor

Become a part of our caring community Most AI engineering jobs are a thin wrapper around a model API. This role is different. We build the platform that transforms millions of clinical documents into trusted, actionable data. Our systems use large language models (LLMs) to read medical records, extract structured facts, answer complex questions with citations back to the source document, and route ambiguous cases to human experts for review. Our users make decisions that impact real healthcare outcomes, so “good enough” is not good enough. Building AI systems that are accurate, reliable, auditable, and scalable is at the core of this role. As a Senior AI Applied Engineer, you will design, build, deploy, and operate production AI systems used at scale within one of the largest health insurers in the United States. You will own solutions end-to-end, from user experience and APIs to model orchestration, evaluation frameworks, infrastructure, and production operations. Why Join Us Build production AI systems where LLMs are in the critical path, not just demos or proofs of concept. Work on extraction, retrieval, agentic workflows, and human-review systems that process real healthcare data at scale. Own projects end-to-end across frontend, backend, AI orchestration, infrastructure, deployment, and operations. Solve challenging problems around accuracy, explainability, traceability, and reliability in regulated environments. Ship quickly in a small, high-impact team that embraces AI-assisted development and rigorous quality standards. Build systems that continuously improve through expert feedback, evaluations, and human-in-the-loop workflows. Key Responsibilities Design, develop, and deploy full-stack AI-powered application

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

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

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