Full Stack Java Developer Jobs

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. We are looking for talented systems developers and researchers to join the Snowflake AI Research team and advance the state of the art in LLM inference systems and optimization . Our mission is to build the next generation of high-performance and intelligent inference systems . We optimize not only how fast and efficiently models run, but also how quickly inference systems can adapt to new models, architectures, hardware, and workloads. Our work spans the full inference stack—from distributed serving and runtime systems to GPU kernels and model-system co-design. We explore techniques such as adaptive parallelism, speculative and parallel decoding, disaggregated inference, scheduling and batching, KV-cache optimization, model swapping, quantization, and GPU kernel optimization to push the frontier of latency, throughput, scalability, and cost. Beyond optimizing individual models, we are building intelligent and adaptive inference systems that can automate performance optimization—rapidly profiling new models and workloads, identifying bottlenecks, selecting effective execution strategies, and adapting system configurations with minimal manual tuning. We embrace AI-native engineering , using AI not only as the workload we optimize, but also as a tool to accelerate system deve

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Baseten is seeking talented and experienced Software Engineers to join our Platform team within the Infrastructure organization. As a senior member of Baseten's Platform Team, you will own the systems that let every engineer at Baseten prove their code works before it reaches production. Our product runs mission-critical AI inference for customers who measure downtime in dollars per second, which means our internal bar for correctness, performance, and failure tolerance has to be exceptional. Your focus is the full testing stack: fast and reliable unit test tooling, integration harnesses that spin up realistic environments on demand, load and performance testing for GPU-backed inference workloads, and resilience testing that deliberately breaks things so our customers never have to find out what happens when a node dies mid-request. This is a builder role with org-wide leverage. You won't be writing tests for other teams — you'll be building the frameworks, harnesses, and feedback loops that make writing good tests the path of least resistance, and you'll set the standards for what "well-tested" means at Baseten. RESPONSIBILITIES Own Baseten's testing strategy end to end — define the standards, the tiers, and the tooling that engineering teams build against. Build and maintain unit, integration, load and performance testing frameworks Design end to end test infrastructure that provisions realistic dependencies

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Design and implement novel research ideas, ship state of the art models to production, and maintain deep connections to academia and the government. We have one of the highest ratio of compute to engineers in the world. We do not delineate strongly between engineering and research. Everyone will contribute to writing production code and conducting research depending on individual interest and organizational needs. We have all the compute, data, and talent available for you to do your best work. As a Member of Technical Staff - Sovereign AI, you will: Design, build and scale agentic AI systems for serving mission critical use cases. Research, implement, and experiment with ideas on our supercompute and data infrastructure. Learn from and work with the best researchers in the field. Execute across the full AI stack and ship products to serve public interest. You may be a good fit if you have: Canadian citizenship and eligibility for security clearance ( required for this role ). Extremely strong software engineering skills. Proficiency in Python and related ML frameworks. Experience training, evaluating, and using (

About the Team The Monetization team is a new cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products, including next-generation ads experiences, that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers, advertisers, and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, Research, and external customers to bring new monetization products into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to help build Ads Manager, the UI platform advertisers use to create, manage, measure, and optimize ad campaigns across OpenAI’s ads ecosystem. This is a foundational role responsible for designing and implementing advertiser-facing products, APIs, tools, and services that connect external customers to OpenAI’s next-generation monetization products. You’ll work across the full technical stack to build intuitive self-serve workflows for small and mid-sized advertisers, as well as scalable APIs and integrations for large enterprise advertisers, agencies, and ad-tech partners who manage campaigns through their own buying platforms or intermediary systems. This includes building advertiser-facing APIs and tooling for campaign management, conversion APIs, pixels, measurement, and insights. You will collaborate deeply with Product, Design, Research, and Go-To

About the Team The Monetization team is a new cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products, including next-generation ads experiences, that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers, advertisers, and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring new ad experiences into real-world systems across OpenAI surfaces at global scale, including thoughtfully integrating them into the core ChatGPT experience. About the Role We’re looking for an experienced Software Engineer to help build the creative rendering and presentation layer of OpenAI’s ads ecosystem. This is a foundational role responsible for defining how ads are structured, rendered, and delivered across different surfaces, platforms, and media types. You’ll work across the full technical stack to build infrastructure and tooling for new ad formats, including text, image, video, native, conversational, and interactive experiences. You will help ensure these formats render reliably, perform efficiently, and feel natural within the core ChatGPT experience. You’ll collaborate deeply with Product, Design, and Research to create ads experiences that are useful, high-quality, privacy-preserving, and aligned with OpenAI’s standards for safety and user trust. In this role, you will: Design, build, and

About the Team The Monetization team is a new cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products—including next-generation ads experiences—that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to help build the core monetization and ads systems at OpenAI. This is a foundational role responsible for designing and implementing the infrastructure, APIs, and user-facing experiences that will power OpenAI’s next-generation monetization products—including ads. You’ll work across the full technical stack to architect, build, and ship 0→1 systems that are robust, safe, and scalable. You will collaborate deeply with Product, Design, and Research to define the future of monetized AI experiences and ensure these systems meet OpenAI’s highest standards for safety, privacy, and policy alignment. This role is exclusively based across our San Francisco and Seattle sites. We offer relocation assistance to new employees. In this role, you will: Design, build, and scale the core infrastructure behind OpenAI’s monetization and ads products Develop advertiser-facing APIs and tools that enable the cre

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE You will be the pivotal, end-to-end owner driving the product lifecycle for our cutting-edge data center storage solutions. Your mission is to translate product vision into Mass Production (MP) reality, managing all aspects of the hardware (Mechanical and Electrical Engineering) and the full software stack (firmware, OS). This highly visible role requires you to orchestrate global, cross-functional engineering, manufacturing, and supply chain teams while leading executive-level phase gate reviews to ensure our products deliver optimal performance and compliance, on time and on budget. WHAT YOU'LL DO End-to-End Release Ownership: Own the overall release plan, including scope, milestones, and dependencies. You’ll be the primary point of contact for release lines across Product, Engineering, QA, and Security. Strategic Program Leadership: Manage multiple concurrent workstreams involving cross-functional stakeholders. You will own the "big picture," ensuring that high-level technical architecture aligns with execution. Release Integrity: Own release branch health metrics. You’ll lead bug scrubs, triage critical issues, and define the criteria for merging new payloads (leveraging your experience with Git-based workflows). Operational Excellence: Drive the Product Lifecycle (PLC) phase exit reviews (Phases 0–3). You will define exit criteria, ensure they are met, and formally drive approvals. Risk & Conflict Resolut

NVIDIA is at the forefront of the AI and robotics revolution, and NVIDIA’s robotics teams are on a mission to build the essential technology that can enable any company to become a robotics company. The Seattle Robotics Lab is uniquely positioned at the intersection of open academic research and real-world industry impact, pursuing fundamental and applied robotics research across the full robotics stack, including perception, planning, control, reinforcement learning, imitation learning, simulation, and robotics foundation models. This research aims to transform research paradigms, transfer into NVIDIA’s robotics and simulation products, and create new robotics markets for the world. The Seattle Robotics Lab has published over 500 research papers, including many influential works that have been presented at top robotics, AI, and computer vision conferences. These works include BayesSim , cuRobo , DeXtreme , DiSECT , Factory , GraspNet , IndustReal , ITPS , LAPA , <a href="h

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team The AI team is focused on one of Stripe’s most strategic growth areas: enabling the monetization and scaling of AI-native and AI-enabled businesses. We’re in a unique position – partnering with the world’s most ambitious AI companies (the likes of OpenAI, Anthropic, NVIDIA, etc) building on the frontier of artificial intelligence -- across infrastructure, foundation models, agents, and applications -- to help them grow and commercialize globally using Stripe’s full financial stack. As part of Stripe’s GTM / Sales organization, this team works closely with Product, Engineering, and Marketing to shape Stripe’s AI GTM strategy and ensure that the world’s leading AI companies -- from early-stage innovators to the largest public players -- choose Stripe as their monetization platform. What you’ll do Work with existing Stripe customers in the AI Industry to develop and execute long-term sales strategies to expand Stripe’s revenue Own the full sales cycle, from business case development, to deal structuring and negotiating, to close Develop account plans and cross sell into your list of strategic AI customers, driving growth through expansion and new revenue streams Drive deal strategy and commercial negotiations for large, complex renewals Develop relationships with executive stakeholders within your book of business, deeply understanding problems they are solving and helping drive to solutions Be responsible for account mapping and coor

About the Team OpenAI’s acquisition of io marks our entry into consumer hardware and our ambition to define the next human–computer interface. Success in hardware requires strong financial stewardship across the full product cost stack—from early design and sourcing decisions through manufacturing, logistics, inventory, returns, and warranty. Hardware Finance works across Product, Supply Chain, Operations, Accounting, Systems/Data, and Finance to connect business decisions to product cost, inventory, cash, COGS, and margin. About the Role We are seeking a Hardware Finance Manager to own an assigned area of hardware COGS and inventory end to end. The initial assignment will depend on business priorities and the successful candidate’s expertise. It may include BOM and product cost, manufacturing variance analysis, inventory planning, logistics, returns and warranty, customer support, or another connected set of hardware-finance responsibilities. This is an individual-contributor role with broad scope. Prior hardware experience and deep, hands-on expertise in at least two relevant domains are required. The person will be expected to operate independently, build reusable processes and analytical workflows, and remain accountable for the analysis, judgment, and recommendations. In this role, you will: Own an assigned area of hardware COGS and inventory end to end. Own forecasting, close, and business variance analysis for the assigned scope. Provide hardware leadership with clear variance explanations, trend analysis, and forward-looking signals that connect business and supplier decisions to inventory, cash, COGS, and margin. Partner with business teams and Finance Platforms to establish the financial data, systems, and dashboards needed to support analysis. Ensure data integrity and governance through clear definitions, ownership, validation checks, controls, and review processes. Improve forecasting, reporting, systems, and finance processes so they remain reliable an

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The People Technology stack has never been more capable, the differentiator now is the expertise to unlock it. . As a Senior Workday Engineer at Lyft, you'll be the technical cornerstone of our People Technology team, owning the design, development, and delivery of the integrations, custom applications, and AI solutions that the entire People function depends on. This role uniquely combines deep, demonstrable mastery across the full Workday technology stack with an AI-native engineering approach, enabling you to build solutions that don't just automate what exists today but fundamentally raise the bar for how People Technology delivers value. We're seeking a hands-on engineer who commands the full depth of the Workday ecosystem, from Studio and Core Connectors to Extend and Prism Analytics, and brings the technical judgment to architect solutions that scale with the business. You'll be the trusted technical owner of our People Technology platforms, partnering closely with HR, Payroll, Finance, and Benefits stakeholders to translate complex requirements into scalable, maintainable solutions that truly move the needle. With AI reshaping how People Technology teams operate, your expertise will be critical in actively identifying, building, and shipping AI-powered solutions that eliminate manual work, accelerate delivery, and push our teams from tactical execution to strategic impact. In this role, you'll integrate LLMs into HR workflows, build and maintain MCP servers that expose People systems data securely to AI agents, mentor junior engineers, and set the engineering standard for a team that is redefining what enterprise People Technology looks like. If you are a candidate who has the vision of what could be, who has the ability to cultivate relationships, and has a belief in driving impact, then you

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. We’re looking for a strategic and execution-oriented Senior Director, Revenue Operations to lead and scale the operational backbone of our B2B organization. Sitting within B2B Operations, this role will own the strategy, architecture, and optimization of our revenue systems, processes, and analytics across Sales, Customer Success, and Marketing. You will serve as a key partner to B2B leadership, driving operational rigor, scalable infrastructure, and data-driven decision-making to accelerate revenue growth. You will define the roadmap for revenue systems, lead cross-functional initiatives, and build the foundation for long-term scale. What you'll do: Define and execute the B2B Revenue Operations roadmap in alignment with C1 growth objectives Act as a strategic partner to B2B leadership on forecasting, pipeline health, performance metrics, and operational investments. Establish scalable processes that improve conversion, velocity, forecasting accuracy, and revenue predictability at scale. Lead the redesign of Salesforce to support complex B2B sales motions, with hands-on responsibility for system configuration, reports, and dashboards Architect and optimize the full revenue tech stack (Salesforce, Outreach, ZoomInfo, HubSpot, Gong, LinkedIn Sales Navigator, etc.) Maintain data quality (deduplication, enrichment, normalization), build and evolve reporting frameworks, and troubleshoot integration issues across the revenue tech stack when they arise. Create and maintain internal documentation, runbooks, and training materials; support enabl