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Platform Delivery Specialist in Austin

124 active opportunities · Updated October 2026

Explore current platform delivery specialist jobs in Austin. Filter by work mode, employment type, experience, department, date posted and distance.

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📍 Austin, Texas, United States· Full-time
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Principal Embedded SW/FW Engineer (Bringup) - Austin, Tx, USA Job Summary We have an exciting opportunity to be part of a collaborative, cross-functional development team validating cutting-edge, high-performance AI chips and platforms. You will play a key role in supporting new product introductions and post-silicon validation. Working within the Post-Silicon Validation team, you will be involved with bringing first silicon to life, functionally validating it and working closely with many other teams to help it become a fully characterised and working product, reporting project status/progress to program management on a regular basis. You will have the opportunity to provide technical guidance to other engineering team members. In this role, you can leverage our experience and industry knowledge to architect and drive implementation of continuous improvements to test infrastructure and processes. The Team The Post-Silicon Bringup team sits within the Architecture and Validation team, we are responsible for bringup and validation of new silicon when it returns from manufacture, enabling and supporting the production SW and FW teams to bring up their software and supporting the Silicon Characterisation team. Responsibilities and Duties Plan, design, develop and debug silicon validation tests in bare metal C/C++ on FPGA/Emulator prior to first silicon Deploy silicon validation tests on first silicon and debugging them Develop automated test framework and regression test suites in Python to optimize validation efficiency Collaborate closely with engineers from many other disciplines on a variety of topics Work with Validation and Production Test engineering peers to implement best practices and continuous improvements to test methodologies Analyse test results, identify and debug failures/defects Contribute to shared test and validation infrastructure Provide feedback to architects Candidate Profile Essential: Understanding of ML

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📍 Austin, TX, United States
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POSITION SUMMARY: Assists in analyzing specimens and maintains equipment in good operating condition. PRIMARY RESPONSIBILITIES: • Assist in testing of patient samples according to standard operating procedure. •Meet expected performance metrics within role as applicable. • Responsible for maintaining updated understanding and knowledge of methods performed in the lab • Provide guidance for new team members. • Follows GLP (good laboratory practice): maintain clean and organized workspace • Completes training and other deadlines on time. • Recognizes, escalates, and troubleshoot equipment malfunctions and common processing errors according to the laboratory’s standard operating procedures • Recognizes, documents, and escalates protocol deviations in lab to lead/supervisor • Communicates with team and other departments on various platforms (including via e-mail) • Provides feedback on day-to-day schedule and tasks to lead/supervisor • Assists teammates in completing daily tasks • Maintains equipment and instruments in good operating condition (such as calibration and expiration date) • Maintain sufficient inventory of material, supplies and equipment in the laboratory for performance of duties. • Participate in Continuous Improvement Projects (TAG, 5S) • Conducts himself/herself in a professional manner • Adheres to Departmental Expectations • This role works with PHI on a regular basis both in paper and electronic form and have access to various technologies to access PHI (paper and electronic) in order to perform the job • Employee must complete training relating to HIPAA/PHI privacy, General Policies and Procedure Compliance training and security training as soon as possible but not later than the first 30 days of hire. • Must maintain a current status on Natera training requirements. • Employee must pass post-offer criminal background check. • Performs other duties as assigned. QUALIFICATIONS: • BS/BA in a biological science or a related field • 0-2 y

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📍 Austin, Texas, United States
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

Hyliion is committed to creating innovative solutions that enable clean, flexible and affordable electricity production. The Company’s primary focus is to develop distributed power generators that can operate on various fuel sources to future-proof against an ever-changing energy economy. Job Purpose The Senior Manager, Additive Fleet is responsible for the day-to-day performance of Hyliion's laser powder bed fusion (LPBF) printer fleet in Austin, which produces the complex, high-density metal heat exchanger hardware in the KARNO Core. This hardware can only be produced through metal additive manufacturing, so Hyliion's ability to build KARNO at scale depends directly on the health, uptime, and throughput of the fleet. The role leads the technicians and operators who run and maintain the machines, and owns preventive maintenance strategy, machine health monitoring, and decisions on hardware and software upgrades. The fleet runs the full range of Colibrium Additive LPBF platforms, including new machine technology being adopted in real time, and a primary focus is reducing machine-to-machine variation and building repeatable processes across machine models. This is a hands-on leadership role with regular time on the shop floor, and its scope will grow as Hyliion's print capacity scales. AI at Hyliion At Hyliion, AI is core to how we work. We equip every team member with leading AI tools and count on you to use them — to move faster, solve harder problems, and help us realize the full potential of KARNO technology for the world. Duties and Responsibilities Own fleet uptime and drive continuous improvement in machine-to-machine consistency across Hyliion's LPBF printer fleet. Build and maintain a preventive maintenance program across all machines to identify failure modes before they cause downtime. Lead, schedule, and develop the team of technicians and operators who run and maintain the fleet. Develop machine health monitoring us

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📍 Austin, Texas, United States· Full-time
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. 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. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Senior Principal Network Engineer to help design, deploy, and optimize next‑generation AI data center networks. AI training and inference workloads require extremely high bandwidth, deterministic low latency, and zero‑packet‑loss networking environments. In this role, you will partner closely with the Network Architecture Lead to design and scale high‑performance computing (HPC) network fabrics supporting GPU clusters. You will work across hardware, networking, and AI application layers to ensure Graphcore’s large‑scale AI infrastructure operates at peak performance. The ideal candidate brings deep experience operating hyperscale or HPC data center networks and has expertise in high‑speed Ethernet fabrics, RDMA technologies, advanced automation, and telemetry systems. The Team The Data Center Network Engineering team designs and operates the high‑performance network fabrics that power Graphcore’s AI compute platforms. The team collaborates closely with hardware engineering, AI researchers, and infrastructure teams to build scalable networking environments optimized for distributed training and infe

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