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 As an Engineering Manager (Player & Coach), you will lead and mentor a team of Forward Deployed Engineers focused on building, scaling, and optimizing LLM inference workloads for Baseten customers. Applying both hands-on technical ownership and managerial leadership, you will guide your team through the processes of designing, deploying, and managing high performance, low latency AI applications on Baseten’s platform. FDE at Baseten is not a sales function – we are a mix of engineering, product, and customer architects who contribute to the core Baseten codebase, drive large portions of our feature roadmap, and execute on complicated customer engagements. You will also partner with product, infrastructure, and other customer engineering teams to ensure that large language models (LLMs) and other generative AI systems deliver best-in-class performance, reliability, and cost efficiency in production environments. EXAMPLE INITIATIVES Take a look at these blog posts written by members of our Forward Deployed Engineering team: Forward Deployed Engineering on the frontier of AI The fastest, most accurate Whisper transcription Deploy production-ready model servers from Docker images Deploy custom ComfyUI workflows as APIs RESPONSIBILITIES Leadership & Team Management Lead, mentor, and grow a team of Forward Deployed Engineers, providing guidance on technical direction, project execution, and professional deve
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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. Observe by Snowflake is an AI-powered observability platform built on the Snowflake AI Data Cloud and engineered for scale. We ingest and store logs, metrics, traces, and events on an open, scalable data lakehouse using Apache Iceberg — at dramatically lower cost. OpenTelemetry is the foundation of how customers send data to Observe, and we are making significant investment in upstream OTel contributions to ensure Observe is the best destination for OTel-instrumented environments. As a Senior Software Engineer on the OpenTelemetry team, you'll play a key role in driving Observe's open-source strategy within the OpenTelemetry ecosystem. You'll work on some of the most exciting challenges in telemetry collection and instrumentation — expanding coverage into emerging domains like LLM/AI observability and Browser RUM — while collaborating closely with the OTel community to shape the standards that the industry builds on. AS A SENIOR SOFTWARE ENGINEER - OBSERVE BY SNOWFLAKE, OPENTELEMETRY, YOU WILL: Pioneer new instrumentation capabilities in the OpenTelemetry community, defining and building next-generation telemetry collection for emerging domains including LLM/AI inference, Browser RUM, and mobile. Design and implement OTel Collector components (receivers, processors, exporte
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. About Dynamic Tables Dynamic Tables (DTs) are Snowflake's declarative streaming transformation primitive. Customers define a SQL query and a freshness target; Snowflake handles the rest: orchestrating refreshes, maintaining snapshot consistency across a DAG of dependencies, and automatically incrementalizing the computation so that cost scales with what changed. Dynamic Tables is one of the fastest growing products at Snowflake and is a core part of Snowflake’s Data Engineering strategy. The Dynamic Tables performance team is responsible for making incremental refresh fast, predictable, and cost-efficient across increasingly complex query shapes. As a Staff Engineer on this team, you will own the technical direction for critical performance initiatives and be a force multiplier for the engineers around you. What You'll Do Lead the design and implementation of performance improvements to the incremental view maintenance engine, including multi-join incrementalization, novel incrementalization semantics, incremental window functions, and stacked operations. Help define the roadmap for the incremental view maintenance engine, identifying key performance, scalability, and correctness milestones, prioritizing high-impact enhancements, and aligning technical investments with prod
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. • Identify, diagnose and resolve assembly process related problems • Coordinate and execute process, equipment and material evaluation / optimization initiatives and implement changes at process step • Lead / participate in continuous yield improvement and cost reduction activities • Validate and fan out new process baseline qualified, including new process, tools and/or materials for new product introduction • Support SPC/FDC/RMS/APC • Support site to site portability • Manage / audit material suppliers to achieve quality, cost and risk management objectives • Support internal and external audits About Micron Technology, Inc. We are an industry leader in innovative memory and storage solutions transforming how the world uses information to enrich life for all . With a relentless focus on our customers, technology leadership, and manufacturing and operational excellence, Micron delivers a rich portfolio of high-performance DRAM, NAND, and NOR memory and storage products through our Micron® and Crucial® brands. Every day, the innovations that our people create fuel the data economy, enabling advances in artificial intelligence and 5G applications that unleash opportunities — from the data center to the intelligent edge and across the client and mobile user experience. To learn more, please visit micron.com/careers All qualified applicants will receive
The Team + The Role Our Engineering Team is focused on building AI Products for our product experience (PX) platform. We build from the ground up to explore, prototype, and ship AI-native experiences that change how software teams understand and serve their users. This is not an AI layer added to existing product; it is a deliberate bet on what product intelligence looks like next. The team operates with high autonomy, moves quickly, and builds products without clear precedents. As a Staff Software Engineer (AI), you will sit at the intersection of deep technical capability and strong product judgment. You will design and build production-grade AI systems, including RAG pipelines, agentic workflows, and LLM-powered features, while making clear tradeoffs across prompting, fine-tuning, architecture, evaluation, and deployment. You will also partner closely with product, design, and engineering stakeholders to frame the right problems and communicate technical decisions clearly. This role is based in our New York office. What this looks like day-to-day Applied AI systems: Design and build AI-native systems, including RAG pipelines, agentic workflows, and LLM-powered product features. You will take ideas from prototype through production and ensure they can support real users. Model strategy: Make principled decisions about when to prompt, when to fine-tune, and when to use a different technical approach entirely. You will explain those tradeoffs clearly to engineers and non-engineers. Evaluation and guardrails: Instrument and evaluate model outputs rigorously by defining evaluation frameworks and identifying hallucinations early. You will implement guardrails that hold up under real-world usage and load. Productionize AI ownership: Own model deployment, monitoring, latency optimization, cost management, and reliability at scale. You will ensure AI systems are observable, performant, and production-ready. Full-stack delivery: Contribute across the stack when needed to g
The Team + The Role Our Engineering Team is focused on building AI Products for our product experience (PX) platform. We build from the ground up to explore, prototype, and ship AI-native experiences that change how software teams understand and serve their users. This is not an AI layer added to existing product; it is a deliberate bet on what product intelligence looks like next. The team operates with high autonomy, moves quickly, and builds products without clear precedents. As a Sr. Software Engineer (AI), you will sit at the intersection of deep technical capability and strong product judgment. You will design and ship applied AI systems, including RAG pipelines, agentic workflows, and LLM-powered features, from prototype through production. You will make principled technical decisions, evaluate model behavior rigorously, and communicate tradeoffs clearly to engineers and non-engineers alike. This role is based in our New York office. What this looks like day-to-day Applied AI systems: Design and build AI systems including RAG pipelines, agentic workflows, and LLM-powered features. You will take work from prototype through production and ensure it can hold up in real customer environments. Technical decision-making: Make principled decisions on when to prompt, when to fine-tune, and when to use a different tool entirely. You will explain these tradeoffs clearly so the team can move quickly without sacrificing quality. Model evaluation: Instrument and evaluate model outputs rigorously by defining evaluation frameworks and catching hallucinations early. You will implement guardrails that can withstand real-world load and production use. Productionize AI ownership: Own model deployment, monitoring, latency optimization, cost management, and reliability at scale. You will help ensure AI systems are observable, efficient, and dependable in production. Full-stack product shipping: Contribute across the stack when needed because this team ships products, not just mod
A Career with Point72's Technology Team As Point72 reimagines the future of investing, our Technology group is constantly improving our company’s IT infrastructure, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts experimenting, discovering new ways to harness the power of open source solutions, and embracing enterprise agile methodology. We encourage professional development to ensure you bring innovative ideas to our products while satisfying your own intellectual curiosity. What you'll do Lead the design, development, and operation of scalable, enterprise-grade AI/ML architectures and systems with a strong emphasis on reliability, availability, and performance. Lead and mentor a team of engineers, driving technical direction, code quality, and iterative delivery of large-scale solutions. Partner closely with data scientists, engineers, product teams, and compliance to integrate AI/ML solutions into existing and new products. Own the end-to-end lifecycle of GenAI services, including LLM inference, model serving, and proxy/gateway layers that support multiple downstream applications. Define and uphold engineering best practices around observability, scalability, security, and cost efficiency for AI/ML platforms. Evaluate tools, technologies, and processes to ensure the highest quality and performance of AI/ML systems. Stay abreast of the latest advancements in AI/ML technologies and methodologies, and translate them into pragmatic solutions for the business. Ensure compliance with industry standards and best practices in AI/ML. What's required Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 10+ years of experience in software/AI/ML engineering, with a proven track record of successful delivery of complex, production-grade systems. Demonstrated experience building large-scale enterprise-grade services with high reliability, availability, and observability (SLO/SLA-driven en
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 Pure Storage is seeking a full-time Principal Hardware Engineer working as part of our Hardware Development Team. In this position, you'll be working to define the technical direction of our next-generation hardware platforms. You’ll work closely with Architects, Engineering, Operations, OEM/JDM Partners and Support & Escalation Teams. You'll be responsible for the future of Pure’s high performance storage systems, acting as the primary subject matter expert for system hardware across executive, product, and client interactions.. WHAT YOU'LL DO Define system-level hardware architecture for FlashBlade, including compute, memory, interconnect, storage, power, and thermal design. Translate product requirements and customer needs into clear technical specifications and design trade-offs. Evaluate and select key components, technologies, and vendors, and lead make-vs-buy decisions. Drive architecture reviews and design reviews, and ensure designs meet performance, reliability, and compliance targets. Partner with firmware and software teams to define hardware/software interfaces and optimize the full stack Track emerging technologies and industry standards, and shape the long-term hardware roadmap. Work with manufacturing and supply chain on DFM/DFT, yield, cost reduction, and component risk. Strong understanding of X86 architecture and proven design track record Solid understanding of Major Bus
Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. About the Role: Join our Product Engineering team to develop AI and Machine Learning solutions that transform semiconductor workflows. This role focuses on model development and agentic AI applications, enabling smarter testing, faster yield advancement, and engineering automation to improve cost, cycle time, and quality. This is a ground-breaking opportunity to work on modern technologies and make a significant impact in a world-class company! You will also train and guide Citizen Data Scientists (CDS or equivalent experience) within Product Engineering, helping them apply advanced ML techniques and analytics tools to gain domain-specific insights. Key Responsibilities: Machine Learning Development: Build predictive models for yield, test time, and reliability analysis using structured/tabular data Use advanced machine learning techniques to analyze complex datasets and generate actionable insights that improve manufacturing and operational performance Build and validate ML workflows for large-scale semiconductor datasets Agentic AI Solutions: Develop intelligent agents to automate engineering tasks (e.g., test program validation, yield analysis, report generation) Integra
About the Team The Codex team is responsible for building state-of-the-art AI systems that can write code, reason about software, and act as intelligent agents for developers and non-developers alike. Our mission is to push the frontier of code generation and agentic reasoning, and deploy these capabilities in real-world products such as ChatGPT and the API, as well as in next-generation tools specifically designed for agentic coding. We operate across research, engineering, product, and infrastructure—owning the full lifecycle of experimentation, deployment, and iteration on novel coding capabilities. About the Role As a Performance & Systems Engineer on the Codex team, you will be responsible for whole-system optimization across a complex, evolving stack. Codex spans LLM inference, cloud orchestration, agentic work management, and multiple product surfaces. Your job will be to identify and land high-leverage changes—across infrastructure, modeling, and product layers—that make Codex agents significantly faster and cheaper to serve. We’re looking for generalists who thrive in ambiguity and love chasing performance bottlenecks to ground. This is a high-ownership role where your work will directly improve the experience of millions of users. 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 will: Hunt down and address inefficiencies across the Codex system stack, from agent behavior to LLM inference to container orchestration, and beyond. Build tooling to measure, profile, and optimize system performance at scale. Collaborate with researchers and engineers to land high-ROI changes that improve latency and cost. You might thrive in this role if you: Have experience operating across both ML systems and cloud infrastructure. Enjoy diving into messy, ambiguous problems and emerging with clear wins. Think holistically about performance, balancing spee
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 Our Senior Applied AI Engineer builds and operate production-grade AI systems that extract meaning from large-scale unstructured document collections, enabling enterprise data discovery classification, and governance. This role owns the full lifecycle of graph intelligence solutions — from problem definition and data modelling, to building and enriching knowledge graphs, and deploying ML- and LLM-assisted analytics in production. The focus is on semantic and contextual analysis of unstructured data to uncover relationships, patterns, and insights that support AI safety, security, and compliance requirements. WHAT YOU'LL DO Design, build, and deploy graph-based AI solutions, combining knowledge graphs , LLMs, and ML models applied to large-scale unstructured data Define and own data pipelines that extract, transform, and enrich entity relationships into production-grade knowledge graphs Integrate LLMs and ML models into text processing pipelines for classification, embedding generation, document similarity, and semantic analysis Design, deploy, and operate graph and vector databases to support retrieval, reasoning, and analytics Optimize models and inference pipelines for production constraints including latency, throughput, cost, and infrastructure Deploy, monitor, and iterate on ML systems in production environments ensuring reliability and continuous integration Drive architectural decisions and tech
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. Observe by Snowflake is an AI-powered observability platform built on the Snowflake AI Data Cloud and engineered for scale. We ingest and store logs, metrics, traces, and events on an open, scalable data lakehouse, using open formats like Apache Iceberg, at dramatically lower cost. A dynamic Context Graph and chat-based AI SRE provide rich context and automated workflows so teams can move from detection to root cause of production issue and resolution 10x faster. Leading engineering teams at companies like Capital One, Topgolf, and Dialpad rely on Observe to troubleshoot hundreds of terabytes of telemetry daily while maintaining reliability at enterprise scale. As part of Snowflake, Observe combines startup-style ownership and velocity with the global reach, operational excellence, and ecosystem of one of the world’s leading data platforms. The Role You'll be our dedicated expert in query execution and query performance. That means owning the query execution service end-to-end: working on caching strategies, incremental execution, query rewrites, and other optimizations that directly affect the speed and cost of running Observe at scale. You'll also be the go-to resource when query latency issues arise during customer evaluations and new deal cycles, diagnosing root causes
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. Observe by Snowflake is an AI-powered observability platform built on the Snowflake AI Data Cloud and engineered for scale. We ingest and store logs, metrics, traces, and events on an open, scalable data lakehouse, using open formats like Apache Iceberg, at dramatically lower cost. A dynamic Context Graph and chat-based AI SRE provide rich context and automated workflows so teams can move from detection to root cause of production issue and resolution 10x faster. Leading engineering teams at companies like Capital One, Topgolf, and Dialpad rely on Observe to troubleshoot hundreds of terabytes of telemetry daily while maintaining reliability at enterprise scale. As part of Snowflake, Observe combines startup-style ownership and velocity with the global reach, operational excellence, and ecosystem of one of the world’s leading data platforms. We are hiring a Senior Frontend Engineer, AI Products team at Observe by Snowflake. As an AI Product engineer you'll always be thinking first about the user experience and how to create the best product, technical choices, and implementation decisions that stem from that product first thinking. This team builds the AI-powered products and developer tooling at the core of Observe's platform, including our flagship AI SRE product, real-tim
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’re hiring a talented Software Engineering Manager to lead the Snowtrail infrastructure team at Snowflake. Snowtrail is the infrastructure that enables Snowflake to deliver dedicated coverage for customer-specific workloads. Its innovative approach allows Snowflake to precisely test and measure the impact of changes on individual customers, making it essential for ensuring the platform’s reliability, correctness, and performance. Through query replay, Snowtrail helps us catch regressions early. By leveraging machine learning models to intelligently sample queries and workloads, we continuously optimize for both cost and performance. Evolving Snowtrail to incorporate new engine features while improving scalability, efficiency, and reliability is central to our continued success OUR IDEAL MANAGER WILL HAVE : Strong passion and proven track record for shipping quality software in high code velocity environments 10+ years industry experience designing and building distributed data systems. Excellent problem solving skills, and strong CS fundamentals including data structures, algorithms, and distributed systems. Fluency in SQL, Java, C++, Python or Go. Ability to collaborate well across teams, build high-performing teams and mentor junior engineers. Excellent interpersonal co
About Us: Paytm is India's leading mobile payments and financial services distribution company. Pioneer of the mobile QR payments revolution in India, Paytm builds technologies that help small businesses with payments and commerce. Paytm’s mission is to serve half a billion Indians and bring them to the mainstream economy with the help of technology. About the role: As an Senior Engineering Manager, you will be developing the detailed design structure, implementing the best practices and coding standards, leading a team of developers for successful delivery of the project. You will be working on design, architecture and hands-on coding. Requirements: 9 to 13 years in Technical development with 5+ years in Providing technical leadership for high performance teams. Work closely with business and product teams to understand the requirements, drive design, architecture and influence the choice of technology to deliver solutions working closely with architects and leadership team. Build robust, scalable, highly available and reliable systems using Micro Services Architecture based on Java, Spring boot. Improve Engineering and Operational Excellence by identifying and building the right solutions for observability and manageability. Keep the tech stack current with the goal to optimize for scale, cost and performance. Migrate workloads to public cloud. Attitude to thrive in a fun, fast-paced environment. Serve as a thought leader and mentor on technical, architectural, design and related issues. Proactively identify architectural weaknesses and recommend appropriate solutions. Preferred Qualification : Bachelor's/Master's Degree in Computer Science or equivalent Skills that will help you succeed in this role: Tech Stack: Lang: Java, DB: RDBMS, Messaging: Kafka/RabbitMQ, Caching: Redis/Aerospike, Micro services, AWS. Strong experience in scaling, performance tuning & optimization at both API and storage layers Hands-on leader, and problem solver with a passion for e
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