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. Responsibilities Strategize and lead productivity, yield, quality, and cost improvement engagements with global sites and the network team via plasma process optimization, new/FOAK chemistry & hardware qualification , and CIP development collaboration with dry etch suppliers. Collaborate with cross-functional teams to drive breakthroughs in defect reduction, particle/residue control, CD uniformity, profile control, and chamber-matching across the global fleet. Develop the process and hardware CIP roadmap for Dry Etch — covering chamber parts, RF/match networks, gas delivery, ESC, endpoint, and plasma source upgrades. Drive process & hardware improvement with emphasis on safety, defect reduction, cost efficiency, throughput, quality, and sustainability across Dry Etch modules ( Conductor Etch, Dielectric Etch, Poly/Gate Etch, Metal Etch, High-Aspect-Ratio (HARC) Etch, Spacer/ALE, etc.). Partner with suppliers to establish equipment start-up acceptance criteria, chamber qualification flows, and tool service requirements ; work with global facilities to address new tool installation requirements (abatement, exhaust, RF compliance, gas/chemical infrastructure). Improve tool efficiency, WPD, and utilization across all Micron Dry Etch fleets through benchmarking, MAXOUT-style productivity programs, and pathfinding solutions . Set up IoT/FDC sensors and advanced chamber telemetry for defen
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At Zoox, we are developing a purpose built autonomous robotaxi, and the Sustaining Engineering team plays a critical role in ensuring the long term reliability, safety, serviceability, and availability of our fleet as it operates at scale. As a Sustaining Engineer supporting Body and Closure Systems, you will independently own sustaining engineering for key subsystems supporting both the in-service fleet and vehicles in current production. You will drive root cause investigations and corrective actions, making subsystem-level technical decisions and leading changes through design, validation, release, and fleet implementation. This role requires close collaboration with Vehicle Development, Manufacturing, Service, Quality, Reliability, and Suppliers in a fast paced and often ambiguous environment. You will prioritize work based on fleet and production impact, delivering solutions that improve safety, durability, fleet uptime, and manufacturing performance. In this role, you will: Own sustaining engineering and corrective action development for body and closure systems across the in service fleet and vehicles in current production, from root cause confirmation through fleet-wide implementation Drive end-to-end resolution of field and manufacturing issues across door systems, latches, actuators, sealing, access panels, glazing, and body structures Apply fleet and production data, including MTBF, repeat failure rates, and downtime drivers, to prioritize work, validate solutions, and drive continuous improvement Lead design updates and system improvements, ensuring robust performance, durability, efficiency, and serviceability in both fleet and production environments Author and manage Engineering Change Requests and Change Actions, and develop and execute validation plans at component, system, and vehicle levels Support and lead retrofit and rework campaigns, and partner with suppliers to resolve quality issues and im
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 Reinforcement learning is how Claude learns to reason, write code, and act autonomously over long horizons. At frontier scale, an RL run is an unusually demanding distributed system. Training, sampling, and environment execution run concurrently across a large fleet of accelerators and hosts, exchange data continuously, and have to keep making progress while hardware fails, load shifts, and the research changes underneath them. How well that system holds together determines how much of our compute turns into learning, and how quickly the team can try the next idea. As a Research Engineer on the Distributed Systems team within RL Engineering, you'll work on whatever part of that system is the current limit. That might be scheduling and placement, data movement between components, running large numbers of sandboxed environments, storage and checkpointing, networking, fault tolerance, autoscaling, or the observability that tells us what a run is actually doing. We're looking for generalists: engineers who can move between these layers, reason from first principles about a system they haven't seen before, and pick the problem that matters most rather than the one closest to their prior experience. Our system changes as fast as the research does, correctness under failure matters as much as throughput, and the best solutions often come from understanding the ML workload well enough to know which guarantees it actually needs. Strong candidates have built and run large distributed systems, care about getting the details right, and want to apply that experience to a workload that is very large, very heterogeneous, and changing
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 Our Inference team is responsible for building and scaling the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry’s largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators. The team has a dual mandate: maximizing compute efficiency to reliably serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms. Inference systems are highly performance sensitive distributed systems. Inference serves hundreds of thousands of customers every day, and the size & span of the inference fleet requires sophisticated routing, scaling, and networking systems. Key responsibilities Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide Develop resilient, flexible systems that adapt in real time to real world events Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators and multiple cloud providers Maximize compute efficiency and optimize cost across the fleet by autoscaling and orchestrating production, research, and experimental workloads across multiple cloud providers Build and operate production-grade deployment pipelines for releasing new models to user
We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. In this part-time position, you will work 20 hours per week, to including every other weekend. You will participate in a holiday rotation. Availability to work East Coast hours is required. Position Summary The MinuteClinic Support Coordinator is responsible for managing nationwide callouts, processing Workbrain payroll corrections for the fleet, and performing various administrative tasks. This role requires timely handling of callouts and an understanding of the dynamic work environment and unique staffing needs of retail health clinics. The Support Coordinator will collaborate with their direct supervisor, regional coordinators, and field leaders to review and analyze Workbrain payroll corrections related to staffing and scheduling. This position requires weekend coverage and scheduling flexibility to work part-time (20 hours per week) across 4–5 days, with shifts varying between 6:00 AM and 9:00 PM Eastern Time. Required Qualifications Minimum of 1 year of experience in workforce scheduling or a related field. High School diploma or GED equivalent. Preferred Qualifications Knowledge of workforce scheduling practices. Strong attention to detail and ability to meet deadlines. Critical thinking and problem-solving skills. Excellent custom
This is Adyen Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition. For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster. Adyen is looking for full-time Kotlin Engineers to help us develop our in-person payments solution. We have a large and varied fleet of payment terminals and payment SDKs in the field, which we are continuously improving by adding new features and payment methods. Kotlin development plays a vital role in this effort, as your code will be deployed across our various solutions using Kotlin Multiplatform. What you’ll do As a Kotlin Engineer you will work on solutions for our payment terminals and payment SDKs featuring many capabilities, such as: Accepting payments using credit cards and debit cards, Apple Pay or Google Pay on mobile phones or accepting payments through QR codes Building and maintaining payment features for global merchants Integration with a variety of cash registers using state of the art standards You will be working on developing our main business logic in Kotlin, which will be deployed on both Android and Linux based payment terminals, and on our backend. You will also be contributing to C++ libraries that are central to our payment business logic. Your code is tested using a variety of testing methods. These methods range from unit testing to complete product testing via automated programmable robots in order to offer a stable and feature rich solution to all of our merchants. Who you are: A motivated, enth
Job Title Sales, Strategic Accounts Director - Image Guided Therapy Systems (Southeast/Mid-Atlantic) Job Description The Director of IGT Strategic Accounts will work with 2 IGTS Districts and be responsible for order and revenue growth at a targeted set of named accounts. Your primary responsibilities will be to act strategically and grow Philips Marketshare by focusing on: executing fleet replacement plans of Philips Install Base accelerating competitive replacements at accounts where Philips is not installed (red accounts). In this role, you will work closely with the Philips IGT Sales and Marketing teams, you will build deep customer relationships at multiple touchpoints throughout your assigned health systems, all while developing and deploying strategies to solve interesting hospital challenges to help IGT continue to win. Your role Deliver agreed-upon growth in targeted accounts, and contribute to the overall sales results of the covered districts. Actively manage, monitor and continually improve the team’s overall sales process to ensure a successful productivity ramp in order to exceed revenue and commercial goals. Analyze and quantify equipment replacement potential at targeted accounts, assess regional market conditions, and use this to create and execute strategies to help grow Philips share Partner with CADs and ECEs to relentlessly assess and build out IDN and GPO sales strategies that help the district grow Philips IB or replace competitive IB Track and analyze customer performance to identify positive or negative trends, all while looking for opportunities to find mutually beneficial areas for growth. Able to quickly digest data, identify trends, and turn them into proactive strategies Ability to both work with and lead the IGT field sales teams in a matrix environ
SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. ABOUT THE ROLE: Determine true root cause of fleet hardware failures — component and system level — and drive fixes through vendors to the manufacturer. Turn "swap it again" into "vendor redesign / firmware fix / manufacturing escape found." RESPONSIBILITIES: Own named failure classes across GPU trays/baseboards, NIC/DPU, motherboard/PCIe switch, memory, power, thermal, cables/connectors, and rack-scale patterns. Run recurrence analysis and fleet-wide defect clustering; detect systemic patterns before they become fleet-scale loss. Build vendor technical escalation packages with evidence quality that forces action; partner with OEM/ODM/component manufacturers on firmware, bring-up, and manufacturing escapes through committed CAPA. Feed findings into RMA policy, spare strategy, and "do not reseat forever" stop-rules. Work the FA intake queue on rotation; keep queue age within SLA BASIC QUALIFICATIONS: Bachelor's degree in Systems Engineering, Electrical Engineering, Computer Science, or a related field (or equivalent experience). 2+ years of experience in hardware reliability engineering, preferably in high-performance computing or data center environments. Proven expertise in fir
About Supabase Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth. About the Role We are seeking a platform engineer to join our Compute Capacity team. This team owns the capacity plan that keeps compute supply ahead of demand across every region we operate in — the forecasting, buffer policy, and provisioning systems that make sure a project never runs into a wall it didn't know was there. You'll work on the systems that turn a capacity plan into provisioned reality: reservation acquisition, fleet reconciliation, and the automation that keeps what we've committed to in sync with what we're actually running. You'll help build the metrics and alerting that let capacity problems surface months out, on vendor lead time, rather than at the moment someone needs the room. You'll design, build, and operate systems that are both robust and highly automated — helping us hold the right buffer at the right cost, catch drift before it becomes a shortage, and give every team a single, trustworthy view of how much room we have across the millions of databases we manage. What You'll Be Responsible For Help build and maintain the capacity plan that keeps Supabase's compute supply ahead of demand across regions and instance families Support buffer policy by modeling headroom targets and their cost tradeoffs for review and sign-off Build and maintain automation that turns the capacity plan into provisioned reality — reservation acquisition and top-up, fleet reconciliation, drift detection between committed and running capacity Extend our infrastructure as code for capacity-relevant provisioning Instrument capacity: build and maintain metrics for saturation, reservation coverage, idle buffer, forecast error, and provisioning latency Build and tune capacity alerting so headroom,
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 Every request that hits Claude — from claude.ai , the API, our cloud partners, or internal research — depends on a set of decisions made before it ever reaches a model: where each request should be served and how much capacity each model needs right now. Getting those decisions right is crucial to satisfying throughput, reliability, and latency constraints. This group builds the control plane that makes those decisions for Anthropic's inference fleet and own the inference request path. This is a deeply technical group. The engineers here design placement and load-balancing algorithms, build quantitative models of demand, capacity, and system performance, improve latency across kernel, network, and framework boundaries, and reason carefully about how a change to the fleet ripples through everything that depends on it. You'll lead a strong group of ML platform, infrastructure, and distributed-systems engineers working alongside the teams that build our ML internals and cloud infrastructure. You need enough systems depth to make architectural calls, hire people who go deep, and see when a proposed change will ripple across the fleet. You're accountable for the health of the whole path from request to model: its efficiency, its reliability, and how well it evolves as models, hardware, and clouds change underneath it. Key responsibilities Own the technical roadmap for how the inference fleet is coordinated — where traffic goes, where capacity lives, how caches are placed, how fast the system reacts to demand, and the protocols that keep the control plane and the inference engines in sync Partner with the product, inference e
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 Endpoint team (Client Platform Engineering) manages the laptops and handsets every Anthropic employee works on, plus the infrastructure underneath them. We treat the fleet as a distributed platform, not a collection of devices, and every piece of configuration ships as code through pull requests, CI, staging, and a canary group. Today the mobile side of the fleet is BYOD. This role exists to change that. You will design and implement a corporate-issued mobile device program (managed company phones and managed Apple accounts) in every region Anthropic operates in, and take it from early design to production. The team is deliberately lean and runs with high autonomy. You’ll define what a corporate mobile program looks like at Anthropic and own the platform decisions that get it there. Responsibilities Design the corporate-issued mobile device program: device standards, what we issue to whom, and how the program grows from a first region to everywhere Anthropic operates Own the global logistics of issuing hardware: procurement partners, regional coverage, spares, and refresh cycles Bring mobile configuration into the team’s config-as-code pipeline so mobile policies are reviewed, tested, and progressively rolled out like the rest of the fleet Build zero-touch enrollment: Apple Business Manager and ADE with managed Apple accounts on iOS, the zero-touch equivalent on Android, so a new phone works the first time without hands-on setup Own policy, compliance, and device lifecycle for the corporate fleet, from issue to wipe Build telemetry on the corporate fleet: which devices are checking in, OS and patch state, drift betw
As Senior Data Scientist for Engineering Systems you will work independently alongside sharp, generous, and pragmatic engineers from Server Query, Atlas Clusters, and Release Quality, among other teams. Together, we tackle problems spanning resource scaling across the Atlas fleet, safe feature rollout to MongoDB clusters, automated incident response and query engine performance. Join the Platform Data Science team and help us research, prototype and ship machine learning features for MongoDB’s core server, query engine and Atlas, our database-as-a-service cloud offering. We are looking to speak to candidates who are based in Dublin or Cork for our hybrid working model. What You'll Do Partner with Server Query, Atlas Clusters, Release Quality and other engineers to embed algorithmic rigor and optimization into resource scaling, release-safety and monitoring systems across the fleet and inside query engine Deliver production-ready, thoroughly tested statistical and ML algorithms with well-identified limitations that deliver measurable business impact, not just an impressive-sounding methodology Own the full feedback loop: instrument model architecture with the metrics needed to track performance and create dashboards in collaboration with our stellar analytics team, collect feedback from users and metrics to diagnose issues or opportunities, and iterate accordingly Deliver thoughtful, kind code reviews to your peers and act as a core contributor to internal packages, tooling, and team processes that increase developer productivity Measures of Success In 3 months, you’re familiar with our workflow, have an elementary understanding of our product and what teams we work with. You have delivered small-to-medium improvements to our project portfolio In 6 months, you’ve delivered one feature you researched and prototyped from scratch and demonstrated its impact on business metrics of your choice In 12 months, you've established a track record of shipping ML-driven improveme
About the Role Together AI is looking for a Manager to own the commercial relationships with our international cloud compute suppliers and the market intelligence that drives our compute supply strategy. You will manage the lifecycle of international cloud service provider (CSP) contracts and renewals, run RFP processes for new capacity, build pricing benchmarks across the global GPU cloud landscape, and partner with infrastructure engineering, finance, and GTM to secure the right capacity at the best economics as we rapidly scale our GPU fleet globally. Responsibilities Manage the lifecycle of international CSP leasing agreements, from sourcing and RFPs through contract execution and renewals Partner with infrastructure engineering to translate technical requirements into commercial specifications, and coordinate technical evaluations during vendor selection Develop and maintain relationships with cloud compute suppliers to expand Together's vendor ecosystem into new international markets Build and maintain market intelligence to stay ahead of pricing trends, supply availability, and the evolving international cloud compute vendor landscape Develop negotiation strategies that improve our cost position and terms as we scale, accounting for local contracting norms and market dynamics Drive continuous improvement on Total Cost of Ownership (TCO) and actively mitigate supply chain and commercial risks across the GPU fleet Establish and lead regular, structured vendor performance reviews, including Quarterly Business Reviews (QBRs), with international cloud and infrastructure compute suppliers. Track the country-level factors that shape international capacity decisions, including power availability, local regulatory and data residency requirements, currency, and tax and duty implications Requirements 5+ years in cloud sourcing, strategic sourcing, or infrastructure commercial roles, with exposure to GPU or high-performance compute environments Track record negotia
SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. ABOUT THE ROLE: Join the High Power Engineering team supporting SpaceXSI to design, build, operate, and maintain electrical infrastructure for AI training campuses. As a Lead Engineer for Battery Storage, you will work with a small on-site team to scale high-capacity power systems on a schedule set by compute demand. The position is based in Memphis, TN, with potential travel to other sites. RESPONSIBILITIES: Own the storage fleet as a power plant, not as an accessory: architecture, sizing, controls, safety case, and grid-forming behavior that lets the campus ride through compute step loads and generation contingencies. Own BESS architecture: pack-to-MV-transformer grouping, string composition, medium-voltage collection topology, string-level protection, and physical block layout including spacing per NFPA 855. Own sizing; translate compute duty cycles — step loads, training-job ramps, actual-versus-nameplate utilization — into power and energy requirements. Own inverter control strategy: grid-forming versus grid-following, droop and virtual inertia, fault-current contribution, ride-through, and coordination with generation governors and excitation. Own the plant controller and
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 Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry’s largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators. The team has a dual mandate: maximizing compute efficiency to reliably serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms. Inference systems are highly performance sensitive distributed systems. Inference serves hundreds of thousands of customers every day, and the size & span of the inference fleet requires sophisticated routing, scaling, and networking systems. Key responsibilities Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide Develop resilient, flexible systems that adapt in real time to real world events Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators Maximize compute efficiency across the fleet by autoscaling and orchestrating production, research, and experimental workloads Build and operate production-grade deployment pipelines for releasing new models to users Provide high-performance inference infrastructure that enables researcher
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