Ai Deployment Manager Jobs

Scale Labs, Research Scientist — Agent Robustness As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist working on Agent Robustness you will work on the fundamental challenges of building AI agents that are safe and aligned with humans. For example, you might: Research the science of AI agent capabilities with a focus on how they relate to safety, risk factors, and methodologies for benchmarking them; Design and build harnesses to test AI agents’ tendency to take harmful actions when pressured to do so by users or tricked into doing so by elements of their environment; Design and build exploits and mitigations for new and unique failure modes that arise as AI agents gain affordances like coding, web browsing, and computer use; Characterize and design mitigations for potential failure modes or broader risks of systems involving multiple interacting AI agents. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be comfortable building and leveraging agent scaffolding, designing evaluation harnesses, an

Scale Labs, Research Scientist — Safety Post Training As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist working on Safety Post-Training you will develop and apply post-training methods and interpretability techniques to make frontier AI systems safer, and better understood by researchers and policymakers.. For example, you might: Design and run post-training pipelines to study how training choices affect model safety, robustness, and alignment properties; Develop interpretability-informed evaluations that reveal how and why models produce unsafe, deceptive, or otherwise undesirable behaviors, and use those insights to guide targeted mitigations; Collaborate with policymakers, engineers, and other researchers to translate post-training and interpretability findings into actionable safety standards, evaluation benchmarks, and best practices. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Experience with post-training and RL techniques such as RLHF, DPO, GRPO, and similar approaches. A track record of published research in machine learning, particularly in generati

Scale Labs, Research Scientist — Frontier Risk Evaluations As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist focused on Frontier Risk Evaluations, you will design and create evaluation measures, harnesses and datasets for measuring the risks posed by frontier AI systems. For example, you might do any or all of the following: Design and build harnesses to test AI models and systems (including agents) for dangerous capabilities such as security vulnerability exploitation, CBRN uplift, and other high-risk activities; Work with government agencies or other labs to collectively scope and design evaluations to measure and mitigate risks posed by advanced AI systems; Publish evaluation methodologies and write technical reports for policymakers. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be comfortable building and instrumenting ML pipelines, writing evaluation harnesses, and quickly turning new ideas from the research literature into working prototypes. A track record of published research in m

About the team OpenAI's mission is to build safe artificial general intelligence (AGI) which benefits all of humanity. This long-term undertaking brings the world's best scientists, engineers, and business professionals into one lab together to accomplish this. In pursuit of this mission, our Go To Market (GTM) team helps customers understand, adopt, and deploy OpenAI's technology across their most important workflows. The team is made up of Sales, Solutions, Support, Marketing, and Partnerships professionals who work together to bring AI to as many people and organizations as possible. About the role As an Account Director focused on Life Sciences, you will own executive-level relationships with organizations across biopharma, medical technology, and life science services. This includes pharmaceutical and biotechnology companies, medical device and diagnostics companies, contract research organizations, contract development and manufacturing organizations, research tools companies, and laboratory or scientific services providers. This is a role for someone who understands how life sciences companies create, validate, manufacture, commercialize, and support scientific and medical products. You will help these customers evaluate and deploy OpenAI's technology to accelerate R&D, improve clinical and regulatory workflows, scale scientific and medical content operations, modernize commercial and field teams, and improve knowledge work across highly regulated environments. The role blends scientific literacy, enterprise sales discipline, technical curiosity, and relationship-driven account leadership. You will partner closely with solutions, research, product, legal, security, and compliance teams to design secure, responsible, and high-impact AI deployments for life sciences customers. This role can be remote but New York or San Francisco office locations are preferred. We use a hybrid work model of three days in the office per week and offer relocation assistance t

About the Team OpenAI’s Hardware organization develops system and infrastructure solutions tailored to the demands of advanced AI workloads. We work across the full stack—from silicon to system integration—partnering closely with internal teams and external vendors to define and deliver next-generation AI infrastructure. Our team focuses on defining scalable, high-performance system architectures and reference designs that balance performance, cost, and operational efficiency across rapidly evolving technologies. About the Role We are seeking a 3P Architect to define and drive rack- and cluster-level reference designs in collaboration with external partners. This role is responsible for translating workload requirements and system-level goals into concrete architectures, aligning partners on critical design attributes, and ensuring vendor roadmaps meet our infrastructure needs. You will work closely with performance modeling and internal architecture teams to evaluate tradeoffs, while owning the end-to-end definition and execution of third-party system designs. This includes identifying gaps in current technologies, driving vendor development, and shaping future infrastructure capabilities. This role requires strong system intuition, cross-functional leadership, and the ability to operate effectively across internal teams and external ecosystems. 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. Key Responsibilities Define rack- and cluster-level reference architectures for AI infrastructure deployments. Translate workload requirements into clear system design specifications and partner deliverables. Collaborate with performance modeling teams to evaluate architectural tradeoffs and system behaviors. Align internal stakeholders and external partners on critical system attributes (performance, cost, power, reliability, scalability). Identify gaps in current technology offerings and dr

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. Principal Data Cloud Architect - SI Partners We are seeking a highly experienced and results-driven AI/ML focused Principal Data Cloud Architect to join our Partner Solution Engineering (PSE) team. Our mission is to empower System Integrator (SI) partners to rapidly achieve technical wins and successful production deployments of AI/ML solutions on the Snowflake AI Data Cloud. Snowflake, the AI Data Cloud, enables teams to seamlessly run analytical workflows, develop agentic apps, and train models using both structured and unstructured data. With over 4,000 customers leveraging our gen AI and ML technology weekly, we are at the forefront of AI innovation. This role is crucial in accelerating AI/ML customer journey technical wins and production deployments being implemented by SI partners. IN THIS ROLE YOU WILL PERFORM: Strategic Account Alignment with top accounts for SI partners (Focus on Acceleration): Unlock High-Impact Customer Journeys: Identify and prioritize AI/ML customer journeys for SI partner top accounts, focusing on quick wins and high consumption, informed by your understanding of SI partner needs. Expedited POCs and RFPs: Provide support for partners during RFI/RFP processes and POCs, ensuring rapid turnaround and successful outcomes, informed by your SI propo

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: As a Software Engineer on Collections Infra, you’ll help scale the infrastructure behind Notion’s database block. Databases power views, boards, charts, forms, and the workflows customers use to run their companies; as Notion grows into larger enterprise deployments and AI-native work, those systems need to become faster, more reliable, and ready for much higher concurrency. This team sits between infrastructure and product, building backend architecture that improves the customer experience while becoming a platform other Notion teams can build on. You’ll work on problems like database load performance, microservices, high-volume writes from agents, and the flexibility that makes Notion databases powerful and hard to scale. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve: By your 90th day, you’ll understand how Collections Infra supports Notion’s database

Who We Are Nuro is a self-driving technology company on a mission to make autonomy accessible to all. Founded in 2016, Nuro is building the world’s most scalable driver, combining cutting-edge AI with automotive-grade hardware. Nuro licenses its core technology, the Nuro Driver™, to support a wide range of applications, from robotaxis and commercial fleets to personally owned vehicles. With technology proven over years of self-driving deployments, Nuro gives automakers and mobility platforms a clear path to AVs at commercial scale, empowering a safer, richer, and more connected future. About the Team Frontier models are fungible. Any team can rent the same intelligence we can, and the model we build on today will be replaced within a month. What is not fungible is the infrastructure that decides whether an autonomous system's output can be trusted — evaluation, verification, and the discipline to gate on evidence instead of impressions. Nuro has spent a decade building exactly that discipline for a robot that drives on public roads, and this team turns it inward: we build the platform that lets AI agents operate autonomously inside Nuro's own engineering organization, under the same standard of proof we apply to the vehicle. Our mandate is to amplify the output of every engineer and researcher at Nuro by 100x. Not a better IDE, not a faster build — a change in what a single person can attempt. That number is a target, not a claim, and reaching it depends on one thing above all: autonomous work has to be trustworthy enough to run unattended. So our central ambition is to build the most rigorous closed-loop evaluation system for AI work anywhere. Leverage follows from trust, and trust follows from measurement. We operate as a startup inside a company that has already shipped a hard thing. Small team, no established playbook, direct access to compute and to the systems we are automating. You will work directly with engineering leadership and the CEO, and the deci

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Join Tenstorrent’s AI Models team and work at the layer most ML engineers never see: bringing advanced models to life on custom AI hardware. You’ll own real workloads end‑to‑end including porting, tuning, and validating LLMs and vision models on our accelerator, and chasing down every last millisecond and percentage point of accuracy. This role is for people who love the craft of ML engineering and want their work to matter at silicon scale, not just behind another API. This role is hybrid , based in Cyprus. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Bring up, run, and debug modern ML models (e.g., transformers) using PyTorch or TensorFlow. Analyze model behavior and performance, and identify bottlenecks across the stack. Improve efficiency, correctness, and scalability of model execution in real systems. Work closely with compiler, kernel, and hardware teams to drive performance and system-level improvements. Help translate state-of-the-art model architectures into production-grade, high-performance deployments. What We Need Strong experience building and working with ML models in PyTorch or TensorFlow. Strong understanding of mod

About the Team OpenAI’s Applied AI Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. We work with customer executives, product and engineering teams, security leaders, and transformation teams to identify valuable opportunities, accelerate technical implementation, and scale what works. Enterprise deployments are defined by complexity rather than any one industry: existing architectures, diverse data environments, security and governance requirements, multiple stakeholder groups, and organization-wide change. We turn lessons from these deployments into better products and reusable patterns for customers everywhere. About the Role As an Applied AI Engineer you will partner directly with leading organizations to design, build, and deploy AI systems that deliver measurable business outcomes. You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from use-case selection and architecture through prototyping, evaluation, production launch, and scale. You will write and debug code, build evaluation systems, resolve complex integrations, and guide decisions involving model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. Success is measured by production systems, sustained adoption, and meaningful customer impact—not simply activity or successful demonstrations. This is a rare opportunity to work on consequential real-world deployments at the frontier of AI while directly influencing how OpenAI’s products evolve. This role is based in Singapore. 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: Partner directly with enterprise customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteria. Design, build, and de

About the Team OpenAI’s Applied AI Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. We work with customer executives, product and engineering teams, security leaders, and transformation teams to identify valuable opportunities, accelerate technical implementation, and scale what works. Enterprise deployments are defined by complexity rather than any one industry: existing architectures, diverse data environments, security and governance requirements, multiple stakeholder groups, and organization-wide change. We turn lessons from these deployments into better products and reusable patterns for customers everywhere. About the Role As an Applied AI Engineer you will partner directly with leading organizations to design, build, and deploy AI systems that deliver measurable business outcomes. You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from use-case selection and architecture through prototyping, evaluation, production launch, and scale. You will write and debug code, build evaluation systems, resolve complex integrations, and guide decisions involving model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. Success is measured by production systems, sustained adoption, and meaningful customer impact—not simply activity or successful demonstrations. This is a rare opportunity to work on consequential real-world deployments at the frontier of AI while directly influencing how OpenAI’s products evolve. This role is based in Tokyo, Japan. 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: Partner directly with enterprise customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteria. Design, build, an

About the Team OpenAI’s Applied AI Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. We work with customer executives, product and engineering teams, security leaders, and transformation teams to identify valuable opportunities, accelerate technical implementation, and scale what works. Enterprise deployments are defined by complexity rather than any one industry: existing architectures, diverse data environments, security and governance requirements, multiple stakeholder groups, and organization-wide change. We turn lessons from these deployments into better products and reusable patterns for customers everywhere. About the Role As an Applied AI Engineer you will partner directly with leading organizations to design, build, and deploy AI systems that deliver measurable business outcomes. You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from use-case selection and architecture through prototyping, evaluation, production launch, and scale. You will write and debug code, build evaluation systems, resolve complex integrations, and guide decisions involving model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. Success is measured by production systems, sustained adoption, and meaningful customer impact—not simply activity or successful demonstrations. This is a rare opportunity to work on consequential real-world deployments at the frontier of AI while directly influencing how OpenAI’s products evolve. This role is based in London. 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: Partner directly with enterprise customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteria. Design, build, and deplo

About the Team OpenAI’s Applied AI Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. We work with customer executives, product and engineering teams, security leaders, and transformation teams to identify valuable opportunities, accelerate technical implementation, and scale what works. Enterprise deployments are defined by complexity rather than any one industry: existing architectures, diverse data environments, security and governance requirements, multiple stakeholder groups, and organization-wide change. We turn lessons from these deployments into better products and reusable patterns for customers everywhere. About the Role As an Applied AI Engineer you will partner directly with leading organizations to design, build, and deploy AI systems that deliver measurable business outcomes. You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from use-case selection and architecture through prototyping, evaluation, production launch, and scale. You will write and debug code, build evaluation systems, resolve complex integrations, and guide decisions involving model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. Success is measured by production systems, sustained adoption, and meaningful customer impact—not simply activity or successful demonstrations. This is a rare opportunity to work on consequential real-world deployments at the frontier of AI while directly influencing how OpenAI’s products evolve. This role is based in Abu Dhabi, UAE. 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: Partner directly with enterprise and digital native customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteri

About Bolna Bolna is Voice AI infrastructure built for India. We help businesses deploy intelligent voice agents that can call, converse, and convert in any language, at scale. From collections to customer support to sales, our agents handle millions of conversations so humans don't have to. We're a YC F25 company, backed by General Catalyst, with 1,050+ paying customers and growing fast. Our team of ~25 is based in Bengaluru. The Role You're the person who makes our voice agents actually sound good and actually work for real customers. As an AI Solutions Engineer, you'll sit at the intersection of our product and our customers. Your primary job is to design, write, and iterate on the prompts and tools that power Bolna's voice agents, making them smarter, more natural, and more effective for each use case. You'll work closely with customers to understand their goals, build agent flows, test conversations, and fix what breaks. No heavy coding required-if you can vibe-code a basic script or write a solid system prompt, you're qualified. What You'll Do Write, test, and iterate on system prompts for voice agents across industries like D2C, fintech, healthcare, and logistics Listen to real call recordings, identify where agents fail, and fix them Build conversation flows and call pathways for new customer deployments Help onboard new customers-understand their use case, set up their agent, and get it live Maintain a growing library of prompts, templates, and best practices across Bolna's verticals Red-team agents-try to break them, find edge cases, and make them bulletproof Work with vernacular inputs: test agents in Hindi, Hinglish, and regional languages Feed insights back to product and engineering-you'll see what customers need before anyone else does What We're Looking For Must-have: You've spent serious time prompting ChatGPT, Claude, or similar LLMs-not just casually, but to actually build or solve something You're obsessive about language-you notice when a senten

About the Team OpenAI’s Applied AI Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. We work with customer executives, product and engineeriIng teams, security leaders, and transformation teams to identify valuable opportunities, accelerate technical implementation, and scale what works. Enterprise deployments are defined by complexity rather than any one industry: existing architectures, diverse data environments, security and governance requirements, multiple stakeholder groups, and organization-wide change. We turn lessons from these deployments into better products and reusable patterns for customers everywhere. About the Role As an Enterprise Applied AI Engineer you will partner directly with leading organizations to design, build, and deploy AI systems that deliver measurable business outcomes. You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from use-case selection and architecture through prototyping, evaluation, production launch, and scale. You will write and debug code, build evaluation systems, resolve complex integrations, and guide decisions involving model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. Success is measured by production systems, sustained adoption, and meaningful customer impact—not simply activity or successful demonstrations. This is a rare opportunity to work on consequential real-world deployments at the frontier of AI while directly influencing how OpenAI’s products evolve. This role is based in our SF or NYC office. 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: Partner directly with enterprise customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteri