Model Behavior Engineer Jobs

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. As a Formal Verification Engineer at NVIDIA, you will verify the build and implementation of the industry's leading GPUs. In this position, your responsibilities will be to verify the micro-architecture using formal verification tools, define the verification scope, and ensure correctness. You will employ sophisticated formal techniques to acquire sufficiently bounded proofs while working with architects, designers, and pre- & post-silicon verification teams to accomplish your tasks. You will efficiently complete the formal verification effort for the entire project cycle, delivering high-quality results on schedule, and clearly conveying those results to the team. What you will be doing: Identify key behaviors for verification to write clear testplans for sophisticated designs. Implement testplans using the latest formal techniques, including the development of environment assumptions, assertions, and cover properties. Develop abstraction models to overcome complexity challenges and acquire full proofs, or bounded proofs with sufficient coverage. Drive formal tools to realize their best performance. Debug RTL to identify causes of failure scenarios. Contribute to flow and script development

NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for more than 25 years. Today, we are tapping into the unlimited potential of AI to define the next era of computing. As an NVIDIAN, you will address challenges spanning architecture, silicon, firmware, software, and production — and excellent judgment matters as much as technical depth! Every major NVIDIA silicon product family—from the chips powering AI and datacentre systems to gaming, professional, embedded, and automotive platforms—passes through our productization work on its way to production. NVIDIA’s Silicon Co-Design Productization team works from pre-silicon strategy and feature development through bring-up, characterization, correlation, and optimization. Our charter spans power & performance modelling, bring up & tuning of low-power features, power & thermal controllers , and system-level optimization that ultimately shape how NVIDIA products are configured, binned, specified, and shipped. What you'll be doing Drive silicon power productization from pre-silicon planning through bring-up and production, including test strategy, feature readiness, characterization, and optimization. Partner with architecture and design teams to identify improvements, validate features, and help translate them into production-ready solutions. Correlate measured silicon behaviour with pre-silicon expectations, investigate gaps, and drive complex issues to root cause. Build power and performance models and characterization methodologies that decide silicon binning, product specifications, productization decisions, and customer guidance. Use AI/ML and data-driven methods to analyse characterization & telemetry data, identify anomalies & trends , and accelerate issue debug across silicon, board, power delivery, firmware,

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The End User Protection Team Auth0 is an easy-to-implement authentication and authorization platform designed by developers for developers. We ensure access to applications is safe, secure, and seamless for the more than 100 million daily logins worldwide. Our modern approach to identity enables this Tier-0 global service to deliver convenience, privacy, and security, allowing customers to focus on innovation. The End User Protection team is responsible for building and maintaining Auth0’s Attack Protection capabilities. Cyberattacks, such as credential stuffing and password spraying, often target end users to gain unauthorised access to applications. These attacks pose a significant threat, compromising user accounts and data. The Attack Protection features mitigate these risks by continuously monitoring user login behaviour and automatically detecting and blocking malicious activity. They protect users without adding unnecessary friction. The team works closely with our Machine Learning and AI teams to develop and deploy cutting-edge detection models. This collaboration allows application builders to provide a secure login experience for their users while isolating them from the complexities and ever-evolving tactics of these attacks. The Software Engineer II Opportunity We are looking for a Software Engineer II to join our End User Protection team. What you’ll be doing Be a part of a fast-paced, agile team. Design and buil

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Job Summary We are seeking a motivated engineer to join the DRAM Systems Engineering team, focusing on the development, evaluation, and optimization of next-generation memory systems for AI accelerators. This role emphasizes research and development across hardware architecture, operating systems, and performance analysis to support Agentic AI inference workloads. If you are ambitious and eager to make an impact in the exciting world of AI and memory systems, this is the perfect opportunity for you! Responsibilities Characterize AI inference workloads and examine memory behavior Build and evaluate tiered memory hierarchies for AI accelerators Study KV cache lifecycles, MoE models, and data placement strategies Compare and optimize explicit versus hardware-assisted data movement Develop, test, debug, and detail system-level and OS components Prototype and evaluate agentic AI systems by building agents and multi-agent workflows using modern frameworks and orchestration patterns (planning, tool use, memory, and context management). Apply these technologies both as workloads under study and as accelerators for internal engineering workflows <h2 style="color:!importan

About Mixpanel Mixpanel is the leading product intelligence and analytics platform, trusted by more than 29,000 companies to help understand how people use the products they build. By combining powerful analytics with AI that knows your business, Mixpanel helps teams see what’s working, diagnose what’s not, and decide what to build next. Learn more at mixpanel.com . About the Team The Proactive Insights team is a newly formed team at the center of Mixpanel's AI-first analytics vision. With a greenfield charter, we're building the intelligent layer that transforms Mixpanel from a tool you query into a partner that works for you. We answer the question every data-driven team asks: "What changed, why, and what should I do about it?" We proactively keep users informed about what matters in their data, delivering the right insights and recommendations at the right time, to the right places, both inside and outside of Mixpanel. Some examples of what we are building: Signals : Statistical analysis that automatically identifies which user behaviors cause downstream business outcomes — such as which actions genuinely improve 30-day retention — using causal inference to move beyond correlation Forecasting : Time-series modeling that projects whether a KPI (e.g. Signups) will hit its goal by end of quarter — including trend decomposition, seasonality adjustment, and confidence bands against a target. Simulation : Causal impact modeling that estimates how moving one metric (e.g. weekly sharing rate) by a given amount will ripple through to downstream KPIs like retention or revenue — giving teams a quantified basis for prioritization Cohort Detection : Automated identification of at-risk user cohorts by finding active users who resemble known churned segments across both behavioral patterns and descriptive characteristics, before they churn. Offline batch survival analysis models that estimate each user's probability of a future outcome (e.g. likelihood to churn or convert withi

We believe communication belongs to everyone. We exist to democratize phone service. TextNow is evolving the way the world connects, and that's because we're made up of people with curious minds who bring an optimistic yet critical lens into the work we do. We're the largest provider of free phone service in the nation. And we're just getting started. Join us in our mission to break down barriers to communication and free the flow of conversation for people everywhere. About the role We’re looking for a business-minded Data Scientist who pairs strong technical skills with sound judgment about which problems are worth solving. You’ll partner with product, marketing, finance, engineering, and trust & safety to turn ambiguous questions into rigorous analyses, models, and experiments — and then turn the results into decisions. The problems are real and the data is large: understanding what drives user acquisition, engagement, and retention; improving monetization across ads and subscriptions; measuring the impact of product changes; and helping keep our network safe from fraud and abuse. You’ll own work end to end, from framing the question to landing the recommendation with leadership. What you’ll do Frame the right questions. Work with stakeholders to understand business challenges, spot where data can make a difference, and translate open-ended questions into structured analyses with clear success criteria. Find what drives the business. Dig into large, complex datasets to uncover the trends, segments, and behaviors behind user growth, engagement, retention, and revenue. Build models that get used. Develop and apply statistical and machine learning methods — predictive models, segmentation, forecasting, causal inference — and evaluate them honestly, including their assumptions and limitations. Run and read experiments. Design, analyze, and interpret A/B tests and quasi-experiments that inform product and marketing decisions. Defin

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! Figma’s Data Science team partners across product, engineering, design, marketing, sales, and operations to help Figma make better decisions with data. As a PhD Data Science Intern, you’ll bring rigorous research training to some of Figma’s most important and open-ended questions, from researching emerging product and user behaviors and Figma’s broader ecosystem to developing new measurement methodologies, applying causal inference or machine learning, and building analytical systems. You’ll own a data science project end-to-end: from framing the question and methodology to translating findings into insights that influence Figma’s products, strategy, or data science practices; with the potential to continue toward publication after the internship. This internship will be based out of our San Francisco or New York hub. What you’ll do at Figma: Partner with cross-functional teams to turn ambiguous product, platform, or business questions into well-defined data science problems Analyze user, product, or business data to uncover insights and recommend actions Design and evaluate experiments, metrics, statistical or machine learning models, and analytical frameworks Communicate assumptions, tradeoffs, limitations, and recommendations clearly to technical and non-technical partners Own a focused internship project end-to-end, from problem framing and technical execution through final recommendations, with potential to continue toward publication after the internship We’d love to hear from you if you h

The Opportunity The world of design is changing rapidly, and the Pro Design team is leading that transformation. We are the Adobe organization behind Illustrator, InDesign, and emerging experiences that connect creativity, collaboration, and AI. Our teams are reimagining what professional design looks like for the next decade - building intelligent, connected tools that empower creators and teams to move faster without sacrificing craft. We are looking for a Senior Business Data Scientist who is creative, analytical, and unafraid to question the status quo and shape the decisions that move key business metrics at scale. Join us and build Adobe’s future products! What you'll Do Map the user funnel and build the metrics, cohorts, and dashboards that Product and Growth rely on to see how users move across free, trial, and paid tiers—and pinpoint where they drop off. Dig into the hard questions (what drives activation, which behaviors predict retention and expansion) and build propensity models for conversion, upgrade, churn, and expansion that feed real-time targeting and in-product nudges. Find and size growth bets and work with Product to ship them. Set north-star, driver, and guardrail metrics with your partners, and stand up multivariate experiments across onboarding, paywalls, in-product prompts, and pricing. What you need to succeed Minimum Requirements: Bachelor's degree in a quantitative field (Statistics, Mathematics, Computer Science, Economics, Engineering, or similar) or equivalent practical experience. 5&#43; years of experience in data science, product analytics, or a similar quantitative role. Proficiency in SQL and Python (or R) for data manipulation, analysis, and modeling. Hands-on experience designing and analyzing A/B tests and interpre

About BlockTech As a Quantitative Trader on our Singapore trading floor, you’ll own positions and PnL end-to-end from interpreting live market flow and liquidity through tuning and intervening in our automated systems, all the way to shaping the next generation of execution logic and trading tools. You’ll sit shoulder-to-shoulder with Quantitative Researchers, Quantitative Developers, and Software Engineers, and your decisions will directly drive how we trade across venues. The role Managing and monitoring Delta1 positions across multiple venues, owning the PnL and risk that comes with them Reading live market flow, liquidity conditions, and market events, and translating that read into concrete trading and execution decisions Tuning and parameterising our automated and semi-automated systems, and knowing when to step in to manage risk or capture an opportunity Improving execution quality and market-making performance through data-driven analysis of strategy behaviour Designing and specifying the trading tools, dashboards, and analytics that the desk relies on to make decisions Collaborating closely with researchers, developers, and engineers to sharpen models, infrastructure, and execution logic, and shaping the roadmap for new trading initiatives What we’re looking for 3+ years of experience as a Quantitative Trader and/or Quantitative Researcher in a professional trading environment, with demonstrated PnL responsibility on linear (Delta1) products across multiple venues Hands-on experience operating automated and semi-automated trading systems under live conditions: monitoring, tuning, and intervening when it matters Strong analytical instincts: you can take a messy dataset of fills and quotes and turn it into a concrete execution improvement A deep, intuitive grasp of market microstructure and the ability to explain why a strategy works, not just that it does Proficiency in Python for analysis, tooling, and interaction with trading systems An ownership mindset:

Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange™️ platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Distributed across 160+ public exchanges globally and thousands of private exchanges at the edge, the SASE-based Zero Trust Exchange is the world’s largest in-line cloud security platform. We believe the future of work is Human + AI and are building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world’s hardest security challenges. Driven by deep customer obsession, we are committed to the mission, outcome, and to each other. We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback. Ready to make an impact at the company pioneering security transformation in the AI era? Join us at Zscaler. Role We are looking for an Account Executive, Commercial Sales to join our team. This is a Hybrid role reporting to the Sales Director based in UAE. You will join a global group of professionals passionate about cloud security and driving a secure, cloud-enabled digital future. In this role, you will demonstrate the power and agility of Zscaler cloud transformation by managing a territory focused on net new logos and up-sell opportunities. What you’ll do (Role Expectations) Take ownership of UAE territory focused on net new logo and up-sell opportunities within commercial accounts. Demonstrate expertise in building business cases that clearly show value and differentiation at all levels of customer and prospect organizations Partner effectively with Sales Engineering, Solution Architecture, Value Consulting, and Transformation teams throughout your sales cycles Drive consistent pipeline generation using mode

Our Internal Data team is on a mission to power decisions and applications across MongoDB, oriented around the business areas of GTM, Product & Technology, Finance and HR. With this role, we are focusing on delivery of scalable, insightful, and impactful data products for our Product and Technology (P&T) teams - the org that builds MongoDB products for our external customers. These products drive smarter decisions, automate workflows, enable AI agents and deliver actionable insights that accelerate growth. If shaping the future of data-as-a-product excites you, then this opportunity is for you. As a Senior Data Product Manager on our Data team — which includes Data Pipeline/Platform Engineering, Data Architecture, and Data Governance — you will lead efforts to build, enhance, and scale the data products MongoDB employees use every day across a growing, high-impact company. You’ll deliver data products like data pipelines, datasets, reports/dashboards, APIs, ML models, playbooks, and frameworks while enhancing more traditional data management tools/services to power both AI and BI. These data products form the backbone of our internal data ecosystem and are instrumental in empowering teams to achieve their KPIs and innovate faster. In this role you will also have the opportunity to drive the vision and strategy for internal data as a product, with a focus on telemetry and product adoption/engagement/churn signals. By developing tools and systems that provide deep insights into how customers use or don’t use MongoDB’s products, you will empower teams to understand customer behaviors and improve the end-user experience. The goal is to enable data-driven decisions that enhance product design, drive customer value, and fuel innovation across the MongoDB portfolio. This role can be based out of our Palo Alto, San Francisco, or New York City office or remotely in the East Coast region. Responsibilities Lead Product Strategy and Ownership Define product vision, stra

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 This role is an exciting opportunity to be instrumental in creating magical collaboration workflows within ClickUp. Your focus will be on enabling teams and organizations to work together more effectively, fostering clear communication, coordination, and improved productivity. In this role, you'll have the opportunity to shape the collaboration experience in our products. Responsibilities: Uses AI to gather customer research, generate surveys and tests, and turn insight into clear UX. Prototypes flows, interactions, and logic using Claude Code, Cursor, for rapid iteration with customers and internal stakeholder alignment. Creates high-fidelity UI prototypes that push aesthetics, animation, and visual quality beyond what manual craft alone allows. Automates handoffs to engineering via Figma or vibecoded prototypes built with Claude Code or Cursor. Conduct user research to gain deep insights into user behaviors, pain points, and needs in the collaboration space. Collaborate with cross-functional teams, including product managers, engineers, and researchers, to define product strategy and roadmap for the collaboration experience. Create wireframes, prototypes, and high-fidelity designs that effectively communicate design concepts and interaction models. Conduct usability testing and gather feedback from users to iterate and improve designs. Work closely with front-end developers to ensure the design vision is implemented to the highest standard. Requirements: Minimum of 7 years of experience in product design, with a focus on collaboration or communication products. Strong portfolio demonstrating a track

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. As a User Researcher on the Economy team, reporting directly to the Director of Design Strategy & Operations, you will generate actionable qualitative and quantitative insights that shape core economic systems, developer monetization workflows, and immersive brand experiences. Embedded directly on product teams, you will conduct generative and evaluative research centered on how creators build businesses, how brands interact on the platform, and how users participate in virtual economies. You will tackle high-priority features, solve complex behavioral puzzles, and help translate multi-faceted economic infrastructure into intuitive, trustworthy, and scalable experiences. Partnering closely with Product, Product Design, Engineering, Data Science, and Policy, you will ensure user needs directly inform platform decisions while driving mutual value across players, creators, and brands. You will: Execute end-to-end mixed-methods research projects to understand creator monetization, payouts, advertising, and commerce workflows, translating abstract user behaviors into clear product feature recommendations. Conduct foundational research to uncover key user pain points, mental models, and behav

About the Team The Safety Systems team is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. The Model Policy team aligns model behavior with desired human values and norms. We co-design policy with models and for models by driving rapid policy taxonomy iteration based on data and defining evaluation criteria for foundational models’ ability to reason about safety. Key focus areas include: catastrophic risk, mental health, teen safety and multimodal safety. About the Role Providing access to frontier AI systems raises complex questions around dual-use science and catastrophic risk. How should models respond to requests involving chemical synthesis, biological experimentation, or pathogen research? Where is the boundary between legitimate scientific inquiry and information that could enable misuse? How do we design policies that meaningfully reduce risk without unnecessarily restricting beneficial research? This is a senior role in which you’ll help shape policy creation and development at OpenAI for addressing biological and chemical risks. You will develop structured policy frameworks and taxonomies to guide safe model behavior. This role sits at the intersection of biosecurity expertise, AI safety research, and policy design. You will help ensure that frontier AI systems can support beneficial life sciences research, such as drug discovery, public health, and biosafety, while reducing the risk that these capabilities could be misused. 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’ll: Design and maintain model policies governing chemical and biological risk, defining how models should safely handle dual-use scenarios. Develop structured taxonomies of chemical and biological risk that inform model training data, evaluation benchmarks, and safet

About the Team Our Safety Systems team is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. The Model Policy team aligns model behavior with desired human values and norms. We co-design policy with models and for models by driving rapid policy taxonomy iteration based on data and defining evaluation criteria for foundational models’ ability to reason about safety. Key focus areas include: catastrophic risk, mental health, teen safety and multimodal safety. About the Role Providing access to frontier AI systems raises complex questions around dual-use science and catastrophic risk. How should models respond to requests involving chemical synthesis, biological experimentation, or pathogen research? Where is the boundary between legitimate scientific inquiry and information that could enable misuse? How do we design policies that meaningfully reduce risk without unnecessarily restricting beneficial research? This is a senior role in which you’ll help shape policy creation and development at OpenAI for addressing biological and chemical risks. You will develop structured policy frameworks and taxonomies to guide safe model behavior. This role sits at the intersection of biosecurity expertise, AI safety research, and policy design. You will help ensure that frontier AI systems can support beneficial life sciences research, such as drug discovery, public health, and biosafety, while reducing the risk that these capabilities could be misused. Our relevant publications: Preparedness framework Preparing for future AI capabilities in biology Safety evaluations hub OpenAI GPT5 System Card Evaluating Fairness in ChatGPT Improving Model Safety Behavior with Rule-Based Rewards OpenAI Model Spec Your Responsibilities: Design and maintain model policies governing chemical and biological risk, defining how models should safely handle dual-use scenarios. Develop structured taxonomi