Data Analytics Engineer in United States

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. We are part of Micron’s Advanced Packaging Technology Development (APTD) organization, where new AI assisted packaging technologies are developed to enable future generations of memory and storage solutions. Our team works closely across engineering disciplines to improve manufacturing performance, solve complex technical challenges, and support the technologies driving advances in AI and high-performance computing. As a Shift Process Engineer, you will play a key role in supporting and improving assembly processes within a fast-paced development environment. You will investigate process issues, use data to drive decisions, and work with cross-functional teams to improve yield, quality, and operational performance. This role offers the opportunity to make a direct impact on process capability while collaborating with teams across Micron's global network. Responsibilities: Identify, diagnose, and resolve process issues using failure analysis, FMEA, 8D, SPC, and FDC methodologies Analyze process and manufacturing data to improve yield, product quality, and cost performance

1418 Graphcore is a globally recognised leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data centre hardware that provide the specialised processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. We are opening a new AI Engineering Campus in Austin, which will play a central role in Graphcore's work building the future of AI computing. The Electrical Engineer will play a pivotal role in designing innovative hardware systems for AI/ML applications. We are seeking a motivated Electrical Engineer with 2–4 years of experience in schematic capture, PCB design, and server hardware development. This role includes close collaboration with multiple partners to drive designs from concept through mass production. The ideal candidate is comfortable working across organizational boundaries, ensuring design quality, manufacturability, and on-time delivery in a fast-paced environment. Responsibilities: Develop and maintain electrical schematics for various printed circuit assemblies Design and layout multilayer PCBs Work closely with partners to review designs, provide technical guidance, and ensure alignment with system requirements Drive design for manufacturability (DFM), design for assembly (DFA), and design for testability (DFT) Support server subsystem integration Participate in design reviews Support prototype builds, board bring-up, debugging, and validation Track and resolve design issues, including root cause analysis and corrective actions Ensure proper documentation, revision control, and engineering change management (ECO/ECN processes) Requirements: Bachelor’s degree in electrical engineering 2–4 years of experience in schematic capture and PCB design

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 ship AI products. THE ROLE This is a sourcing-first role, not a deal-closing role. Baseten needs someone who can build and maintain deep relationships across the long tail of data center and powered land providers, well beyond the handful of large, well-known players that everyone in the market is already competing for. This coverage area is a key differentiator for Baseten's broader compute strategy, so we're looking for the best possible person in this specific lane rather than a generalist. You'll own the full lifecycle of a sourcing relationship — from first outreach to ongoing management — not just the introduction. WHAT YOU'LL DO Build and maintain a comprehensive map of data center and powered land opportunities, with a particular focus on the long tail rather than the handful of major, oversubscribed players Own the full sourcing lifecycle for each relationship — from identifying and reaching out to new providers, through negotiation support, to ongoing relationship management — not just the initial introduction Develop and manage sourcing relationships across neoclouds, hyperscalers, brokers, and independent operators Quickly and independently evaluate new sites and spaces to determine fit and priority Prepare business cases and cost analysis to support new data center and powered land opportunities, partnering with Finance where needed Maintain accurate records of suppliers, contracts, and commercial terms so the team has a reli

Human Factors Engineer Description - This role is responsible for shaping the usability and overall user experience of physical products or systems. The role requires a strong blend of human factors expertise, research rigor, and user empathy. The role collaborates closely with cross-functional teams, including designers, product managers, engineers, and stakeholders, to create user-centered design solutions that meet both user needs and business objectives. The role conducts thorough user research to uncover insights, behaviors, and pain points, translating findings into actionable design solutions. Responsibilities Plans, designs, and conducts usability studies and human factors evaluations across multiple stages of product development. Executes formative and summative usability testing, including protocol development, participant recruitment, data collection, and analysis. Leads human factors validation activities in alignment with relevant standards. Applies quantitative and qualitative research methods to generate actionable insights. Analyzes research data and translates findings into clear, practical design recommendations. Prepares and delivers research reports and presentations for cross-functional stakeholders. Collaborates with industrial designers, engineers, and product managers to integrate user insights into product development. Benchmarks product usability and experience against key competitors. Identifies and surfaces usability risks early in development to reduce downstream cost and rework. Supports continuous improvement of research processes, tools, and best practices. Education & Experience Recommended Four-year or Graduate Degree in Design, Human Fac

Become a part of our caring community The Lead Software Engineer codes software applications based on business requirements. The Lead Software Engineer works on problems of diverse scope and complexity ranging from moderate to substantial. The Lead Software Engineer standardizes the quality assurance procedure for software. Oversees testing and debugging and develops fixes. Researches complaints and makes necessary adjustments and/or recommendations to resolve complex software related issues. Advises executives to develop functional strategies (often segment specific) on matters of significance. Exercises independent judgment and decision making on complex issues regarding job duties and related tasks, and works under minimal supervision, Uses independent judgment requiring analysis of variable factors and determining the best course of action. Key Responsibilities Technical Architecture and Ownership:** Design and own the end-to-end architecture of Centerwell's AI systems, including LLM-powered clinical tools, RAG pipelines, harnesses, agent-based workflows, and intelligent automation. Make and communicate foundational technical decisions in close collaboration with the broader engineering team. Model Development and Fine-Tuning:** Evaluate, select, and where appropriate guide the fine-tuning of foundation models. Establish model evaluation frameworks that prioritize safety, accuracy, and clinical relevance. Clinical and Product Partnership:** Collaborate closely with product managers, designers, clinicians, and data stakeholders to understand care delivery workflows and translate them into well-scoped, high-impact AI features. HIPAA Compliance and Responsible AI:** Ensure all AI systems are designed, deployed, and monitored in compliance with HIPAA and Humana's Responsible AI standards, including participation i

Job Details: Job Description: As a Material Analysis (MA) Technician, you will be part of a Technology Development (TD) and High-Volume Manufacturing (HVM) lab responsible for performing material analysis and failure analysis in support of Intel's silicon process development and high-volume production. You will work on developing imaging, composition analysis and sample preparation techniques, and best-known methods (BKMs) to improve lab analysis quality, efficiency and output. You will directly interface with TD and HVM fab customers and quality/reliability engineers to develop solutions to problems by utilizing lab capabilities. The scope may include wafer and unit level, front-end modules and back-end/far back-end modules. Responsibilities may include but not be limited to: • Conducting hands-on analysis by effectively utilizing lab techniques, from sample prep micro-cleaver, ion mill etcher, mechanical polish to SEM/EDX, Dual beam FIB, TEM techniques to characterize Si fabricated structures at nanometer scales and integrated circuit device to improve process, performance and reliability; and to identify physical failure mode toward the root-cause identification. • Conducting hands-on data collection with various lab equipment’s, and assisting engineers to implement materials characterization techniques to determine fundamental thin film material structure/properties and to collaborate with process development engineers across functional areas and organizations to improve process performance and reliability. • Supporting and sustaining lab equipment. Ensuring that lab analytical capabilities needed to support advanced transistor and interconnect technology and/or product development are in place. Cooperating with other lab areas beyond local MA/FA (Failure Analysis) labs to achieve

Senior Low Observables (LO) Mission Systems Integration Engineer Company: The Boeing Company The Senior LO Mission Systems Integration Engineer will lead design, integration, analysis, test, and production activities for low observable materials, structures, apertures, sensors, and radomes for mission systems. The role requires strong technical leadership, independent execution of complex tasks, advanced use of computational electromagnetic (CEM) solvers, and the ability to produce and defend technical results with minimal oversight. Key Responsibilities Lead design, modeling, and analysis efforts for LO materials, coatings, structures, and integrated mission systems to meet signature reduction and performance requirements. Independently apply CEM solvers (e.g., FEKO, HFSS, CST, WIPL‑D, xFDTD, or equivalent) to model antennas, apertures, radomes, and LO treatments; perform design optimization and trade studies. Drive integration of LO treatments with mechanical, thermal, and sensor/antenna system constraints; identify and mitigate producibility, testability, and sustainment risks. Plan, execute, and oversee laboratory and field tests (anechoic chamber measurements, antenna/radome characterization, RCS measurements); lead data collection, reduction, and validation activities. Develop and validate predictive models, reconcile simulations with measurements, perform uncertainty quantification, and provide actionable recommendations to engineering and program leadership. Produce high-quality technical documentation: test plans, test reports, technical memoranda, design reviews, and customer briefings. Mentor and provide technical oversight to junior engineers and technicians; ensure adherence to engineering processes, qual

NVIDIA is seeking a Senior Firmware Engineer to join our CSP Engagements team, focusing on system software for Datacenter products such as GB200. This role combines deep technical expertise in embedded firmware development with customer-facing responsibilities to enable cloud service providers with next-generation computing platforms. You will work at the intersection of hardware and software, driving technical solutions from concept through deployment. What you will be doing: Design and develop firmware solutions for manageability and observability of data center servers. Actively participate in hardware bring-up activities, OOB firmware development, protocol stacks (Redfish, PLDM, MCTP, NSM) and hardware-software co-design for Cloud Service Provider deployments. Debug and troubleshoot NVIDIA GPU firmware issues, power management, performance, and thermal control problems for data center deployments, providing active support to CSPs. Partner directly with CSPs to deliver technical solutions, co-develop & co-debug features and optimizations, and provide support during new product introductions. Perform advanced system debugging, root cause analysis, and performance optimization for large-scale data center environments. Collaborate with AE, FAE, and Solution Architect teams to deliver integrated customer solutions and technical documentation. What we need to see: Deep expertise in data center server architectures, HPC systems, and hardware-software co-design. Deep expertise in embedded firmware, server management controllers, and hardware bring-up with proven track record of shipping production BMC solutions Strong knowledge of DMTF protocols (Redfish, IPMI, PLDM, MCTP, SPDM), telemetry frameworks, and out-of-band management architectures Expert-level skills in C/C&

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. The Cortex team is building the future of AI for enterprise data. This role focuses on the Search infrastructure that powers our flagship products like CoWork, Cortex Code & Cortex Agents fast, reliable, scalable and secure at the enterprise level. You will be building high-performance retrieval engines (leveraging vector search, hybrid search, and semantic indexing) that power Snowflake Cortex. This involves optimizing how billions of rows of data are indexed and retrieved in milliseconds. What you will do in this role: Architect Agentic Runtimes: Build and scale the orchestration engines that execute complex agentic workflows, ensuring low-latency tool execution and robust state management. Scale Context Engineering Infra: Design high-performance systems for RAG (Retrieval-Augmented Generation), including vector database integration, scalable and efficient search indexing, query processing, and result ranking, semantic caching, and automated metadata extraction. Build the "Evals Engine": Develop the automated infrastructure required to run massive-scale golden set simulations, error analysis pipelines, and "hillclimbing" experiments. Productionize AI Workflows: Collaborate with the modeling team to take raw LLM capabilities and turn them into hardened, multi-tenant mi

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role The Financial Intelligence team, part of Ramp's Applied AI org, powers the agentic analysis, FP&A, and book-close experiences that over 70,000 businesses rely on to run their finances. We turn messy financial data into a fast, trustworthy, governed data layer that AI agents can work with and build artifacts on top of. This is a frontend-leaning role for an engineer who obsesses over interaction design and data-dense UX, but is just as comfortable designing the API that feeds it. You'll own the surfaces customers actually touch: agentic financial analysis, month-end close, and exploratory data experiences that feel as polished as the best business intelligence tools. If you want your frontend work to sit at the center of real production LLM systems rather than being bolted on at the end, this is the role. What You’ll Do Design and ship customer-facing AI experiences end to end, from React UI through to the APIs and data contracts behind them Build BI-tool-quality interfaces for agentic analysis, FP&A, and book-close workflows:

What you’ll do Act as the in-house electrical lead for Midjourney Medical: own the electrical architecture of the scanner and the technical direction for all board-level design. Own complex board design end-to-end: architecture, schematic capture, layout (high-speed digital, analog/mixed-signal, power), DFM/DFT, fabrication and assembly vendor management, bring-up, and revision control. Write firmware for embedded targets (MCU/SoC): drivers, real-time control loops, safety-relevant logic, bootloaders, and field update paths. Audit and update HDL (FPGA) code for high-throughput data acquisition, timing/synchronization, triggering, and pre-processing of ultrasound and sensor data streams. Define electrical interfaces and data contracts with software, recon/ML and mechanical teams: timing budgets, clocking/sync, signal integrity, connectors/harnessing, and failure modes. Establish electrical engineering rigor: design reviews, schematic/layout review checklists, bring-up procedures, test fixtures, and documentation suitable for a regulated medical device program (DHF, traceability, change control). Mentor and grow the electrical function; select and manage external design partners where leverage is high. What we’re looking for Deep experience designing complex boards from blank page to stable revision, including high-speed digital and analog/mixed-signal domains. Strong schematic and layout skills (Altium/KiCad or equivalent) with real signal integrity, power integrity, grounding, and EMI/EMC instincts. Solid embedded firmware background in C/C++ (and Python for tooling): peripherals, DMA, interrupts, real-time constraints, and debugging on hardware. Practical HDL experience (VHDL/Verilog/SystemVerilog) for data acquisition, timing, and streaming interfaces. Track record of owning bring-up and debug on real hardware: scopes, logic analyzers, and disciplined root-cause analysis. Technical leadership: clear trade-offs, strong written documentation, and the ability to set

Role Summary: Datadog is seeking a Staff Software Engineer to help shape the future of our Bring Your Own Cloud (BYOC) Logs offering by unifying observability pipelines with log management software that customers deploy and manage in their own infrastructure. This role will focus on building and scaling systems that process, route, and store high-volume observability data within customer-managed infrastructure. You will operate as a hands-on technical leader, driving architecture, cross-team delivery, and product direction across a complex and evolving space. This is a high-impact opportunity to influence product strategy, mentor engineers, and solve deeply technical challenges at scale. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Make customer-controlled deployments feel like a managed Datadog product: deployment, upgrades, configuration, observability, diagnostics, reliability, and secure operation across diverse customer cloud environments Build and scale high-throughput systems for log processing, routing, and transformation across distributed environments Lead cross-team initiatives, aligning engineers, product managers, and stakeholders to deliver complex, multi-team projects Design and implement software that runs reliably that customers deploy and operate within their own cloud infrastructure. Improve system performance, scalability, and cost efficiency through thoughtful trade-off analysis and capacity planning Contribute hands-on to critical code paths, debugging, and deployment challenges in customer environments Who You Are: You have significant experience building software that is installed, deployed, and operated in customer environments rather than only as a fully managed SaaS service. You have strong expertise in distributed systems,

About the Team OpenAI’s Safety teams work to ensure our products are safe, trusted, and resilient as frontier AI systems scale globally. We tackle some of the company’s most important challenges across understanding and preventing misuse and misalignment, intercepting fraud and abuse, and protecting vulnerable users. We are hiring Data Scientists to help build the analytical foundations that allow OpenAI to deploy increasingly capable AI responsibly. We are hiring Data Scientists across several teams that contribute to safety in different ways, including: Safety Systems Integrity Product Policy This is a high-impact role operating at the intersection of product, safety, policy, and research. About the Role As a Data Scientist, Safety, you will help solve complex and ambiguous problems where rigorous analysis directly informs critical decisions. Depending on your background and team alignment, you may work on areas such as: Measure harmful or abusive behavior across OpenAI’s products Detect fraud, manipulation, coordinated misuse Evaluate and improve safety classifiers, rules systems, mitigation systems, and human review workflows Design experiments and causal analyses to understand product, policy, and mitigation impacts Build prevalence estimators, dashboards, monitoring systems, and executive decision frameworks Diagnose gaps in safety and integrity systems using behavioral and product data, and help quantify and navigate false positive / false negative tradeoffs Translate ambiguous safety risks into measurable problems and evidence-based recommendations Partner with Product, Engineering, Policy, Research, and Operations teams to improve safety outcomes Build zero-to-one analytical systems in rapidly evolving domains Ideal Candidate We’re looking for strong Data Scientists who thrive in ambiguous, high-leverage environments. You may be a fit if you have: Strong statistical reasoning and analytical judgment Experience with experimentation, causal inference, or obse

About the Team The Core Network Engineering team owns the end-to-end networking stack that connects OpenAI’s compute infrastructure — spanning global WAN/edge connectivity, data-center networking, and high-performance host/xPU networking used for large-scale training and inference workloads. This team is responsible for ensuring networking is never the bottleneck to model training efficiency, cluster reliability, or fleet expansion. They design and operate the systems that provide predictable, high-throughput, low-latency connectivity across some of the world’s most advanced AI infrastructure. About the Role We’re looking for engineers to help build and operate the networking foundation behind OpenAI’s frontier AI systems. Depending on your background and area of focus, you may work across host networking, datacenter fabrics, or global WAN infrastructure. The problems span low-level systems software, distributed infrastructure, protocol readiness, observability, performance engineering, automation, and large-scale network operations. You’ll work on systems where microseconds of latency, tail performance, and network reliability directly impact model training efficiency and production serving performance. This role is ideal for engineers who enjoy operating close to the hardware/software boundary and solving performance-critical infrastructure problems at massive scale. In this role, you will: Design, build, and operate networking systems that support large-scale AI training and inference infrastructure Improve performance, reliability, and scalability across host networking, datacenter fabrics, and WAN systems Develop automation for provisioning, configuration management, validation, upgrades, and lifecycle management of networking infrastructure Build tooling and observability systems for network health, performance analysis, debugging, and automated remediation Optimize network performance across technologies such as RDMA, RoCE, InfiniBand, Ethernet, and high-perf

About the Team OpenAI, in close collaboration with our capital partners, is building the world’s most advanced AI infrastructure ecosystem. Our Industrial Compute organization develops and deploys large-scale AI campuses designed to support the next generation of frontier model training and inference workloads. The Hardware Operations team is responsible for ensuring the reliability, availability, and lifecycle health of OpenAI’s compute infrastructure. We partner closely with Data Center Operations, Fleet Health Engineering, Manufacturing, Network Infrastructure, Capacity Planning, and our infrastructure partners to maintain world-class operational performance across rapidly expanding AI environments. As we scale globally, we are building the operational frameworks, reliability standards, and sustaining engineering practices required to support thousands of GPUs and servers across multiple campuses. About the Role We are seeking a Datacenter Hardware Technician Lead to serve as the senior on-site technical authority for hardware reliability and fleet health at one of OpenAI’s flagship AI campuses. This role operates at the intersection of hardware operations, sustaining engineering, and fleet reliability. You will partner closely with Cloud Service Provider operations teams, OpenAI fleet-health engineers, hardware engineering teams, and OEM vendors to identify, diagnose, and resolve hardware issues affecting production systems. Beyond day-to-day operational support, you will drive root cause investigations, reliability improvement initiatives, lifecycle management programs, and operational readiness efforts. You will help establish hardware maintenance standards, operational procedures, and best practices that scale across future OpenAI infrastructure deployments. The ideal candidate combines deep hands-on datacenter hardware expertise with strong troubleshooting, failure analysis, and cross-functional leadership skills. Candidates must be able to sit onsite at our