Open Source Software Author Cto Jobs

Salary Range: PLN Range: 260,400 - 352,200 About the job Build the framework support that helps AI developers unlock Graphcore hardware. You will help Graphcore accelerators work seamlessly with state-of-the-art ML frameworks, including Triton and PyTorch. Reporting to a Team Lead in Frameworks, you will design, implement, optimise and support critical software. Your work will shape how researchers and engineers use Graphcore hardware for demanding machine learning workloads. You will improve performance, quality and usability across a complex software stack. You will join our Triton team, delivering new features, reviewing code, writing technical documentation and working with upstream communities. You will also help coordinate open-ended technical work across teams. This is a role for engineers who want deep technical ownership and visible impact. As the ML software landscape evolves, you will keep learning and may contribute across other framework teams. The team and culture The Frameworks team connects Graphcore hardware with the tools ML engineers and researchers rely on. We work across PyTorch, Triton, JAX and TensorFlow, with a strong focus on usability and performance. Work happens through agile practices, close technical discussion and clear ownership. Engineers are trusted to speak up, solve hard problems and move work forward with pace. Decisions are shaped by evidence, code quality and business outcomes. You will collaborate across Graphcore and with open-source communities to deliver software that developers can trust. What we’re looking for · Strong software engineering skills, with the judgement to manage quality, complexity and technical debt. · Experience developing in Python and C++. · Experience in compiler development. · Ability to manage complex technical tasks with cross-team dependencies. · Clear communication skills, with a proactive approach to collaboration and technical leadership. · Interest in AI, ML frameworks, performance optimis

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. About the Team Authentication tells you who someone is. Authorization decides what they can do, and doing that well at scale is hard. Role-based access breaks down as applications grow, and AI agents are changing who, and what, asks for access. Auth0 FGA solves this with fine-grained authorization. Its engine is OpenFGA, a CNCF incubating open source project that Okta maintains with contributors from other companies, and Auth0 FGA runs that same engine as a managed service. FGA DevEx owns how developers experience both: our SDKs, CLI, IDE plugins, Helm charts and docs, all developed in the open. The FGA group owns its product end to end, from infrastructure to docs, so we move quickly and see our work reach developers. Our guiding principle: one developer experience, many deployment models. About the role We're hiring a Staff Engineer to set the technical direction for everything the team owns, and to mentor the senior engineers who build it, starting with our SDKs in Go, JavaScript, .NET, Python, Java and more. From there, you'll shape where the developer experience goes next, from how our SDKs evolve to new surfaces like MCP servers. You'll partner with the Core team on API design, so every new capability feels natural in each language. This is an individual contributor role. You'll work closely with the engineering manager, who owns people and delivery Responsibilities Set the direction: Define and drive the technical direction for FGA DevEx

About Vercel: Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience. Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide. About the Role: As a member of the AI Gateway Team, you will be responsible for developing and enhancing our AI Gateway platform, which provides a unified API for accessing hundreds of AI models from multiple providers. You will collaborate with a remote and distributed team of engineers to build reliable, low-latency systems that handle rate limiting, intelligent failovers, and seamless integrations, enabling developers to ship AI-powered applications without managing provider-specific complexities. This role focuses on ensuring production-ready reliability for AI workloads, including automatic fallbacks during outages and consistent performance across providers like OpenAI, Anthropic, Google, and more. What You Will Do: Contribute to the design, implementation, and maintenance of the AI Gateway platform, emphasizing features like unified API endpoints, rate limit management, and intelligent failover mechanisms to boost uptime and reliability. Write clean, efficient, and well-documented code, conducting thorough testing to ensure low-latency responses and stability for high-volume AI inference requests. Collaborate with cross-functional teams, including product managers, AI researchers, and infrastructure engineers, to integrate new AI providers and models while addressing scalability and performance challenges. Engage with the open-source community, contribute to AI SDK and related projects, and align with Vercel's ethos of fostering developer tools. Gather user feedback and analytics to drive innovations in AI Gateway, such as enh

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. The Engine Networking Team pulls the players together by ensuring the communication of the game state to all. As a Principal Network Transport Engineer you will help the players experience the game as a nearly synchronous world. Just as the nerves in our bodies coordinate our actions, the network system coordinates all the computers involved into a smooth experience for the players. You will work in all areas of the game platform in your quest for real-time communication of every part of Roblox. You Have: Worked on a powerful user-space network stack, solving problems related to scale, performance, latency, and throughput in client/server environments. Worked on a very large multithreaded distributed system that connects millions of users worldwide. Worked on all the devices Roblox supports - from desktop clients to mobile phone clients to console clients Worked on a game engine and understand how a game engine works You Are: A software engineer with 8+ years of experience with Game networking coming from a Game Engine/Studio A deep understanding of Network Stack with a passion for working with open source Strong systems-level C++ programming experience and fascinated by the actual work the

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . We’re looking for a Staff Software Engineer to help build the next generation of Pinterest’s big data storage platform. You’ll work on some of the most exciting big data open source technologies — especially Apache Iceberg — at exabyte scale to power the data infrastructure that helps Pinners discover and do what they love. As a Staff Software Engineer, you’ll serve as a technical leader and hands-on contributor, designing and building highly scalable storage systems for Pinterest’s data lake. You’ll partner closely with teams across data, ML/AI, analytics, and infrastructure to evolve our storage and metadata management capabilities, enabling efficient, reliable, and governed access to data at massive scale. What you’ll do: Design, implement, and optimize Pinterest’s exabyte-scale data lake storage platform. Lead complex technical projects and

P-1285 About This Role As a staff software engineer for GenAI inference, you will lead the architecture, development, and optimization of the inference engine that powers Databricks Foundation Model API.. You’ll bridge research advances and production demands, ensuring high throughput, low latency, and robust scaling. Your work will encompass the full GenAI inference stack: kernels, runtimes, orchestration, memory, and integration with frameworks and orchestration systems. What You Will Do Own and drive the architecture, design, and implementation of the inference engine, and collaborate on model-serving stack optimized for large-scale LLMs inference Partner closely with researchers to bring new model architectures or features (sparsity, activation compression, mixture-of-experts) into the engine Lead the end-to-end optimization for latency, throughput, memory efficiency, and hardware utilization across GPUs, and accelerators Define and guide standards to build and maintain instrumentation, profiling, and tracing tooling to uncover bottlenecks and guide optimizations Architect scalable routing, batching, scheduling, memory management, and dynamic loading mechanisms for inference workloads Ensure reliability, reproducibility, and fault tolerance in the inference pipelines, including A/B launches, rollback, and model versioning Collaborate cross-functionally on Integrating with federated, distributed inference infrastructure – orchestrate across nodes, balance load, handle communication overhead Drive cross-team collaboration: with platform engineers, cloud infrastructure, and security/compliance teams Represent the team externally through benchmarks, whitepapers, and open-source contributions What We Look For BS/MS/PhD in Computer Science, or a related field Strong software engineering background (6+ years or equivalent) in performance-critical systems Proven track record of owning complex system components and driving architectural decisions end-to-end Deep understa

P-1408 The Applied AI team at Databricks sits at the forefront of advancing AI/ML-powered products . Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Some of them can have hundreds of millions of assets. Finding an asset is a critical user journey for Databricks’ customers which helps them accomplish their tasks. As our Search product continues to evolve, we are seeking a Staff Engineer to lead enhancements to our Search Quality. In 2025, we will focus on enhancing search ranking, improving query understanding, building robust evals and growing the coverage of assets to enable seamless search at scale. Key Responsibilities Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services. Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration. Collaborate with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience. Contribute to building a robust framework for evaluating search ranking improvements - both offline and online. What We’re Looking For BS+ (M.S. or PhD preferred) in Computer Science, or a related field. 10+ years experience developing search relevance systems at scale in production or in high-impact research environments. Experience applying LLM to search relevance Experience in one or more of the following: Query understanding NLP Text mining Recommendations Personalization Discovery Conversational AI Strong understanding of computer science fundamentals. Contributions to well-used open-source projects. Why Join Us? At Databricks,

P-1408 The Applied AI team at Databricks sits at the forefront of advancing AI/ML-powered products. Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Some of them can have hundreds of millions of assets. Finding an asset is a critical user journey for Databricks’ customers which helps them accomplish their tasks. As our Search product continues to evolve, we are seeking a Staff Engineer to lead enhancements to our Search Quality. In 2026, we will focus on enhancing search ranking, improving query understanding, building robust evals and growing the coverage of assets to enable seamless search at scale. Key Responsibilities Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services. Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration. Collaborate with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience. Contribute to building a robust framework for evaluating search ranking improvements - both offline and online. What We’re Looking For BS+ (M.S. or PhD preferred) in Computer Science, or a related field. 10+ years experience developing search relevance systems at scale in production or in high-impact research environments. Experience applying LLM to search relevance Experience in one or more of the following: Query understanding NLP Text mining Recommendations Personalization Discovery Conversational AI Strong understanding of computer science fundamentals. Contributions to well-used open-source projects. Why Join Us? At Databricks, w

P-926 The Applied AI team at Databricks sits at the forefront of advancing AI/ML-powered products. Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Finding an asset is a critical user journey for Databricks’ customers which helps them accomplish their tasks. As our Search product continues to evolve, we are seeking multiple senior engineers to drive enhancements to our Search Quality. In 2026, we will focus on enhancing search ranking, improving query understanding, building robust evals and growing the coverage of assets to enable seamless search at scale. Key Responsibilities Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services. Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration. Collaborate with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience. Contribute to building a robust framework for evaluating search ranking improvements - both offline and online. What We’re Looking For BS+ (M.S. or PhD preferred) in Computer Science, or a related field. 5+ years experience developing search relevance systems at scale in production or in high-impact research environments. Experience applying LLM to search relevance Experience in one or more of the following: Query understanding NLP Text mining Recommendations Personalization Discovery Conversational AI Strong understanding of computer science fundamentals. Contributions to well-used open-source projects. Why Join Us? At Databricks, we are building state-of-the-art AI solutions that red

P-375 The Search team at Databricks sits at the forefront of advancing AI/ML-powered products. Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Finding an asset is a critical user journey for Databricks’ customers which helps them accomplish their tasks. As our Search product continues to evolve, we are seeking a Staff Engineer to lead enhancements to our Search Quality. We are focusing on enhancing search ranking, improving query understanding, building robust evals and growing the coverage of assets to enable seamless search at scale. Key Responsibilities Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services. Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration. Collaborate with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience. Contribute to building a robust framework for evaluating search ranking improvements - both offline and online. What We’re Looking For BS+ (M.S. or PhD preferred) in Computer Science, or a related field. 10+ years experience developing search relevance systems at scale in production or in high-impact research environments. Experience applying LLM to search relevance Experience in one or more of the following: Query understanding NLP Text mining Recommendations Personalization Discovery Conversational AI Strong understanding of computer science fundamentals. Contributions to well-used open-source projects. Why Join Us? At Databricks, we are building state-of-the-art AI solutions that redefine how users inte

About Vercel: Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience. Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide. About the Role: We are looking for a Software Engineer to join our Observability team. Vercel users rely on Observability to monitor and understand their applications’ health and behavior. In this role, you will design, implement, and maintain Observability products that meet high-quality standards and integrate seamlessly with the Vercel Platform. This role is based in NYC. If you’re based within a pre-determined commuting distance of one of our offices (SF, NY, London, or Berlin), the role includes in-office anchor days on Monday, Tuesday, and Friday. If you're located beyond that distance, the role is fully remote. For location-specific details, please connect with our recruiting team. What You Will Do: Handle large-scale data ingestion, storage, and processing from distributed systems. Develop cutting-edge visualization tools to provide insights into application behavior and performance. Integrate observability features with popular frontend tools, frameworks, and build systems to enhance developer experience. Write clean, efficient, and well-documented code, ensuring platform reliability through thorough testing. Collaborate with product managers, designers, and infrastructure teams to solve challenges and deliver top-tier solutions. Engage with the open-source community by contributing to projects and participating in discussions, supporting Vercel’s developer-focused mission. Collect feedback from developers and users to drive continuous innovation and improvement in the observability product area. About You: You have at least 5+ year

P-988 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll-up and drill-down capabilities of traditional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be building the next generation distributed data storage and processing systems that can outperform specialized SQL query engines in relational query performance, yet provide the expressiveness and programming abstractions to support diverse workloads ranging from ETL to data science. Below are some example projects: Apache Spark™ : Develop the de facto open source standard framework for big data. Data Plane Storage : Provide reliable and high performance services and client libraries for storing and accessing humongous amount of data on cloud storage backends, e.g., AWS S3, Azure Blob Store. Delta Lake : A storage management system that combines the scale and cost-efficiency of data lakes, the performance and reliability of a data warehouse, and the low latency of streaming. Its higher level abstractions and guarantees, including ACID transactions and time travel, drastically simplify the complexity of real-world data engineering architecture. Delta Pipelines : It's difficult to manage even a single data engineering pipeline. The goal of the Delta Pipelines project is to make it simple and pos

P-987 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll-up and drill-down capabilities of traditional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be building the next generation distributed data storage and processing systems that can outperform specialized SQL query engines in relational query performance, yet provide the expressiveness and programming abstractions to support diverse workloads ranging from ETL to data science. Below are some example projects: Apache Spark™ : Develop the de facto open source standard framework for big data. Data Plane Storage : Provide reliable and high performance services and client libraries for storing and accessing humongous amount of data on cloud storage backends, e.g., AWS S3, Azure Blob Store. Delta Lake : A storage management system that combines the scale and cost-efficiency of data lakes, the performance and reliability of a data warehouse, and the low latency of streaming. Its higher level abstractions and guarantees, including ACID transactions and time travel, drastically simplify the complexity of real-world data engineering architecture. Delta Pipelines : It's difficult to manage even a single data engineering pipeline. The goal of the Delta Pipelines project is to make it simple and pos

P-59 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll-up and drill-down capabilities of traditional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be building the next generation distributed data storage and processing systems that can outperform specialized SQL query engines in relational query performance, yet provide the expressiveness and programming abstractions to support diverse workloads ranging from ETL to data science. Below are some example projects: Apache Spark™ : Develop the de facto open source standard framework for big data. Data Plane Storage : Provide reliable and high performance services and client libraries for storing and accessing humongous amount of data on cloud storage backends, e.g., AWS S3, Azure Blob Store. Delta Lake : A storage management system that combines the scale and cost-efficiency of data lakes, the performance and reliability of a data warehouse, and the low latency of streaming. Its higher level abstractions and guarantees, including ACID transactions and time travel, drastically simplify the complexity of real-world data engineering architecture. Delta Pipelines : It's difficult to manage even a single data engineering pipeline. The goal of the Delta Pipelines project is to make it simple and poss

P-186 At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll-up and drill-down capabilities of traditional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be building the next generation distributed data storage and processing systems that can outperform specialized SQL query engines in relational query performance, yet provide the expressiveness and programming abstractions to support diverse workloads ranging from ETL to data science. Below are some example projects: Apache Spark™ : Develop the de facto open source standard framework for big data. Da