Staff+ Software Engineer, ML Inference Path

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: The Safeguards ML Sampling Path team builds and operates the production services that power Claude's safety systems. These services sit on the token generation path across every platform Claude runs on: every request must pass through them, and each millisecond of added latency is wait time for our users. You’ll keep p99 latency flat as traffic grows, build for robustness as dependencies time out or partially fail, and ship changes safely to a system that cannot go down. What you'll do: Design, build, and operate the backend systems that process every token on the generation path for Claude requests, including the streaming contract with the API and inference engines. Own latency and reliability end to end: define and maintain SLOs and error budgets for added latency, time-to-first-token, and availability, and lead incident response and postmortem follow-through. Ship changes to the hot path rapidly but safely — canaried and gradual rollouts, error budget and latency gating, fast rollbacks — and drive per-token performance: chase tail latency and keep cost flat as traffic, models, and checks per request grow. Set technical direction for the sampling path: lead design reviews, make latency, reliability, and cost trade-off calls with the inference and research teams, mentor engineers, and raise the operational bar for the wider Safeguards organization. You may be a good fit if you: Have designed, built, and operated high QPS systems at global scale, and were accountable for them in production: incident response, outages, and postmortem-driven remediation. Have a strong foundation in distributed systems: replication, cons

Why Harvey At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. Role Overview Harvey is building the AI platform trusted by the world’s leading law firms and enterprises. Our infrastructure is the foundation that powers every customer interaction, every model inference, and every production workload. We’re looking for a Production Engineer to help build and operate Harvey’s core compute and networking infrastructure, Kubernetes platform, workflow orchestration platform, and production infrastructure foundations. You’ll work on the systems that enable engineering teams to move quickly and operate reliable services at scale. In this role, you’ll improve the reliability, scalability, security, and efficiency of Harvey’s infrastructure platform. You’ll solve complex production challenges across compute fleet management, capacity planning, infrastruc

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 lead the technical direction of the backend systems powering Pinterest's AI-driven product experiences — Pinterest Assistant, visual editing and content creation tools and future LLM-based products. You'll design and ship backend systems while architecting the broader platform strategy that enables these experiences to scale across surfaces and teams. This is a hands-on leadership role where you'll move between deep technical execution, system-level architecture and cross-team technical leadership. What you'll do: Define the backend and platform architecture for AI-driven product experiences — visual-chat, AI image generation and editing, and agentic or LLM-based products — partnering with Engineering, Product, ML and UX leaders to shape the technical vision and roadmap. Architect end-to-end systems

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. We are the Data Foundation & AI team within Plaid’s Data organization. Our mission is to build the shared ML and AI infrastructure that powers intelligent capabilities across Plaid’s product suite. We develop the foundational systems, models, and data assets that transform Plaid’s unique financial network data into scalable, general-purpose representations that teams across the company can leverage. Our work spans the full ML lifecycle — from large-scale data curation and model pretraining to production serving, evaluation, and monitoring. As part of the team, you’ll work at the intersection of machine learning infrastructure, applied AI, and distributed systems, helping establish the core AI platform that enables innovation across Plaid. As a Staff Machine Learning Engineer, you will lead the technical strategy and development of Plaid’s foundation models, driving key decisions across pretraining objectives, model architecture, and fine-tuning approaches that power a wide range of downstream product applications. You will serve as the technical lead for the full machine learning lifecycle, overseeing everything from data curation and experimentation to production deployment,

P-188 Our mission at Databricks is to radically simplify the whole data lifecycle from ingestion to ETL, BI, and all the way up to ML/AI with a unified platform. To achieve this goal, we believe the data warehouse architecture as we know it today will be replaced by a new architectural pattern, Lakehouse ( CIDR 2021 paper ), open platforms that unify data warehousing and advanced analytics. The new architecture will help address several major challenges, including data staleness, reliability, total cost of ownership, data lock-in, and limited use-case support. A critical part of realizing this vision is the next generation (decoupled) query engine and structured storage system that can outperform specialized data warehouses in relational query performance, yet retain the expressiveness and of general purpose systems such as Apache Spark™ to support diverse workloads ranging from ETL to data science. As part of this team, you will be working in one or more of the following areas to design and implement these next gen systems that leapfrog state-of-the-art: Query compilation and optimization Distributed query execution and scheduling Vectorized execution engine Data security Resource management Transaction coordination Efficient storage structures (encodings, indexes) Automatic physical data optimization What we look for: A passion for database systems, storage systems, distributed systems, language design, or performance optimization Experience working towards a multi-year vision with incremental deliverables Motivated by delivering customer value and impact 8+ years of experience working in a related system (preferred) Optional: PhD in databases or distributed systems Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are

Who we are 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 tackle 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. Our AI-powered Assistant serves as the initial point of contact for customers seeking assistance on how to use our platform effectively. The Customer Engagement and Docs platform team's objective is to help customers resolve their problems faster using AI / LLMs. We provide customers with precise and comprehensive solutions to their problems or build experiences to facilitate a seamless escalation to a support agent when necessary. As a Staff Engineer, you will operate at the intersection of Product development and Machine Learning. Responsibilities include gaining a deep understanding of user behavior; identifying factors contributing to problems; leveraging Product, Machine Learning (ML) and Large Language Models (LLMs) to analyze intricate technical use cases within a secure enterprise environment and eventually providing a path to resolving them. The impact you will have: Lead design, development, and deployment of systems for Evaluation, Answer retrieval and Quality improvement for helping customers. Lead architectural decisions to ensure performance, reliability, and accuracy of the knowledge systems. Drive best practices for engineering excellence, including design reviews, code quality, testing strategies, and performance optimizations. Deliver high-quality, production-ready code and serv