Nvidia Gpu Confidential Computing Demystified Jobs in Usa

Real-Time Software Systems Engineer

We are currently partnered with an innovative technology company building next-generation real-time systems that power highly interactive, low-latency applications. They are looking to expand their engineering team with an experienced Real-Time Systems Engineer to design and scale complex systems where performance and responsiveness are critical.

This role is full time on site

Key responsibilities

• Design, build, and own the server-side real-time engine, including session lifecycle, state management, and the core interaction loop
• Develop and maintain the timing and scheduling architecture to ensure consistent, low-latency system performance
• Integrate GPU-backed model inference into the real-time pipeline, connecting model outputs into system state and rendering workflows

Key requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field
• Strong experience building real-time systems with tight latency constraints
• Background in domains such as robotics or autonomous vehicles ect.
• Experience designing and implementing complex systems from the ground up
• Familiarity with GPU-based computation and integrating model inference into production systems

Keywords:

Real-Time Systems / Low Latency / Distributed Systems / GPU / Model Inference / Performance Engineering / Profiling / Tracing / APIs / Event Streams / Robotics / Autonomous Systems / AR/VR / Game Engines / Backend Engineering / Systems Design

If you are interested in this position, please send a CV to

By applying to this role you understand that we may collect your personal data and store and process it on our systems. For more information please see our Privacy Notice

Position Summary:

The Scientific Computing and Data group at the Icahn School of Medicine at Mount Sinai partners with scientists to accelerate scientific discovery. To achieve these aims, we support a cutting-edge high-performance computing and data ecosystem along with MD/PhD-level support for researchers. The group is composed of a high-performance computing team, a clinical data warehouse team and a data services team.

The Lead HPC Architect, Cybersecurity, High Performance Computational and Data Ecosystem, is responsible for designing, implementing, and managing the cybersecurity infrastructure and technical operations of Scientific Computing’s computational and data science ecosystem. This ecosystem includes a 25,000+ core and 40+ petabyte usable high-performance computing (HPC) systems, clinical research databases, and a software development infrastructure for local and national projects. The HPC system is the fastest in the world at any academic biomedical center (Top 500 list).

To meet Sinai’s scientific and clinical goals, the Lead brings a strategic, tactical and customer-focused vision to evolve the ecosystem to be continually more resilient, secure, scalable and productive for basic and translational biomedical research. The Lead combines deep technical expertise in cybersecurity, HPC systems, storage, networking, and software infrastructure with a strong focus on service, collaboration, and strategic planning for researchers and clinicians throughout the organization and beyond. The Lead is an expert troubleshooter, productive partner and leader of projects. The lead will work with stakeholders to make sure the HPC infrastructure is in compliance with governmental funding agency requirements and to promote efficient resource utilizations for researchers

This position reports to the Director for HPC and Data Ecosystem in Scientific Computing and Data.

Key Responsibilities:

HPC Cybersecurity & System Administration:

• Design, implement, and manage all cybersecurity operations within the HPC environment, ensuring alignment with industry standards (NIST, ISO, GDPR, HIPAA, CMMC, NYC Cyber Command, etc.).
• Implement best practices for data security, including but not limited to encryption (at rest, in transit, and in use), audit logging, access control, authentication control, configuration managements, secure enclaves, and confidential computing.
• Perform full-spectrum HPC system administration: installation, monitoring, maintenance, usage reporting, troubleshooting, backup and performance tuning across HPC applications, web service, database, job scheduler, networking, storage, computes, and hardware to optimize workload efficiency.
• Lead resolution of complex cybersecurity and system issues; provide mentorship and technical guidance to team members.
• Ensure that all designs and implementations meet cybersecurity, performance, scalability, and reliability goals. Ensure that the design and operation of the HPC ecosystem is productive for research.
• Lead the integration of HPC resources with laboratory equipment for data ingestion aligned with all regulatory such as genomic sequencers, microscopy, clinical system etc.
• Develop, review and maintain security policies, risk assessments, and compliance documentation accurately and efficiently.
• Collaborate with institutional IT, compliance, and research teams to ensure all regulatory, Sinai Policy and operational alignment.
• Design and implement hybrid and cloud-integrated HPC solutions using on-premise and public cloud resources.
• Partner with other peers regionally, nationally and internationally to discover, propose and deploy a world-class research infrastructure for Mount Sinai.
• Stay current with emerging HPC, cloud, and cybersecurity technologies to keep the organization’s infrastructure up-to-date.
• Work collaboratively, effectively and productively with other team members within the group and across Mount Sinai.
• Provide after-hours support as needed.
• Perform other duties as assigned or requested.

Requirements:

• Bachelor’s degree in computer science, engineering or another scientific field. Master's or PhD preferred.
• 10 years of progressive HPC system administration experience with Enterprise Linux releases including RedHat/CentOS/Rocky Systems, and batch cluster environment.
• Experience with all aspects of high-throughput HPC including schedulers (LSF or Slurm), networking (Infiniband/Gigabit Ethernet), parallel file systems and storage, configuration management systems (xCAT, Puppet and/or Ansible), etc.
• Proficient in cybersecurity processes, posture, regulations, approaches, protocols, firewalls, data protection in a regulated environment (e.g. finance, healthcare).
• In-depth knowledge HIPAA, NIST, FISMA, GDPR and related compliance standards, with prove experience building and maintaining compliant HPC system
• Experience with secure enclaves and confidential computing.
• Proven ability to provide mentorship and technical leadership to team members.
• Proven ability to lead complex projects to completion in collaborative, interdisciplinary settings with minimum guidance.
• Excellent analytical ability and troubleshooting skills.
• Excellent communication, documentation, collaboration and interpersonal skills. Must be a team player and customer focused.
• Scripting and programming experience.

Preferred Experience

• Proficient with cloud services, orchestration tools, openshift/Kubernetes cost optimization and hybrid HPC architectures.
• Experience with Azure, AWS or Google cloud services.
• Experience with LSF job scheduler and GPFS Spectrum Scale.
• Experience in a healthcare environment.
• Experience in a research environment is highly preferred.
• Experience with software that enables privacy-preserving linking of PHI.
• Experience with Globus data transfer.
• Experience with Web service, SAP HANA, Oracle, SQL, MariaDB and other database technologies.

Strength through Unity and Inclusion

The Mount Sinai Health System is committed to fostering an environment where everyone can contribute to excellence. We share a common dedication to delivering outstanding patient care. When you join us, you become part of Mount Sinai’s unparalleled legacy of achievement, education, and innovation as we work together to transform healthcare. We encourage all team members to actively participate in creating a culture that ensures fair access to opportunities, promotes inclusive practices, and supports the success of every individual.

At Mount Sinai, our leaders are committed to fostering a workplace where all employees feel valued, respected, and empowered to grow. We strive to create an environment where collaboration, fairness, and continuous learning drive positive change, improving the well-being of our staff, patients, and organization. Our leaders are expected to challenge outdated practices, promote a culture of respect, and work toward meaningful improvements that enhance patient care and workplace experiences. We are dedicated to building a supportive and welcoming environment where everyone has the opportunity to thrive and advance professionally. Explore this opportunity and be part of the next chapter in our history.

About the Mount Sinai Health System:

Mount Sinai Health System is one of the largest academic medical systems in the New York metro area, with more than 48,000 employees working across eight hospitals, more than 400 outpatient practices, more than 300 labs, a school of nursing, and a leading school of medicine and graduate education. Mount Sinai advances health for all people, everywhere, by taking on the most complex health care challenges of our time — discovering and applying new scientific learning and knowledge; developing safer, more effective treatments; educating the next generation of medical leaders and innovators; and supporting local communities by delivering high-quality care to all who need it. Through the integration of its hospitals, labs, and schools, Mount Sinai offers comprehensive health care solutions from birth through geriatrics, leveraging innovative approaches such as artificial intelligence and informatics while keeping patients’ medical and emotional needs at the center of all treatment. The Health System includes more than 9,000 primary and specialty care physicians; 13 joint-venture outpatient surgery centers throughout the five boroughs of New York City, Westchester, Long Island, and Florida; and more than 30 affiliated community health centers. We are consistently ranked by U.S. News & World Report's Best Hospitals, receiving high "Honor Roll" status.

Equal Opportunity Employer

The Mount Sinai Health System is an equal opportunity employer, complying with all applicable federal civil rights laws. We do not discriminate, exclude, or treat individuals differently based on race, color, national origin, age, religion, disability, sex, sexual orientation, gender, veteran status, or any other characteristic protected by law. We are deeply committed to fostering an environment where all faculty, staff, students, trainees, patients, visitors, and the communities we serve feel respected and supported. Our goal is to create a healthcare and learning institution that actively works to remove barriers, address challenges, and promote fairness in all aspects of our organization.

Machine Learning Engineer | Python | Pytorch | Distributed Training | Optimisation | GPU | Hybrid, San Jose, CA

Title: Machine Learning Engineer

Location: San Jose, CA

Responsibilities:

• Productize and optimize models from Research into reliable, performant, and cost-efficient services with clear SLOs (latency, availability, cost).
• Scale training across nodes/GPUs (DDP/FSDP/ZeRO, pipeline/tensor parallelism) and own throughput/time-to-train using profiling and optimization.
• Implement model-efficiency techniques (quantization, distillation, pruning, KV-cache, Flash Attention) for training and inference without materially degrading quality.
• Build and maintain model-serving systems (vLLM/Triton/TGI/ONNX/TensorRT/AITemplate) with batching, streaming, caching, and memory management.
• Integrate with vector/feature stores and data pipelines (FAISS/Milvus/Pinecone/pgvector; Parquet/Delta) as needed for production.
• Define and track performance and cost KPIs; run continuous improvement loops and capacity planning.
• Partner with ML Ops on CI/CD, telemetry/observability, model registries; partner with Scientists on reproducible handoffs and evaluations.

Educational Qualifications:

• Bachelors in computer science, Electrical/Computer Engineering, or a related field required; Master’s preferred (or equivalent industry experience).
• Strong systems/ML engineering with exposure to distributed training and inference optimization.

Industry Experience:

• 3–5 years in ML/AI engineering roles owning training and/or serving in production at scale.
• Demonstrated success delivering high-throughput, low-latency ML services with reliability and cost improvements.
• Experience collaborating across Research, Platform/Infra, Data, and Product functions.

Technical Skills:

• Familiarity with deep learning frameworks: PyTorch (primary), TensorFlow.
• Exposure to large model training techniques (DDP, FSDP, ZeRO, pipeline/tensor parallelism); distributed training experience a plus
• Optimization: experience profiling and optimizing code execution and model inference: (PTQ/QAT/AWQ/GPTQ), pruning, distillation, KV-cache optimization, Flash Attention
• Scalable serving: autoscaling, load balancing, streaming, batching, caching; collaboration with platform engineers.
• Data & storage: SQL/NoSQL, vector stores (FAISS/Milvus/Pinecone/pgvector), Parquet/Delta, object stores.
• Write performant, maintainable code
• Understanding of the full ML lifecycle: data collection, model training, deployment, inference, optimization, and evaluation.

Machine Learning Engineer | Python | Pytorch | Distributed Training | Optimisation | GPU | Hybrid, San Jose, CA

Hi ,

Position : GPU Lab / Datacenter Integration Engineer (Linux & Network)

Location: San Jose, CA(Hybrid)

Duration: 12+ Months Contract

Open only for Contract.

Need USC & GC Holders only.

15 Minute short video discussion is mandated for Submission.

Job Summary:

• We are seeking a Lab Support Engineer to support networking test lab operations in San Jose. The ideal candidate will have strong hands-on experience with networking hardware setup, test topology creation, and lab equipment management. This role involves working closely with engineering teams to deploy, maintain, and troubleshoot lab infrastructure while automating routine workflows using Python.

Must Have Skills:

• Hands-on experience with routers and switches setup and configuration.
• Experience using network traffic generators (Ixia, Spirent).
• Ability to design and build network test topologies.
• Experience working with terminal servers and optical switches in lab environments.
• Strong troubleshooting and problem-solving skills.
• Basic Python scripting for workflow automation.
• Experience with lab hardware ordering, receiving, and inventory management.
• Excellent verbal and written communication skills.

Job Title: QA Engineer

Location: Santa Clara, CA

Employment Type: Full-Time

Role Overview

We are seeking an experienced QA Engineer to support validation and quality assurance activities for consumer desktop platforms. This role is responsible for testing, issue analysis, and ensuring release readiness across internal and OEM configurations. The ideal candidate will have strong Windows BSP testing experience, hands-on debugging expertise, and prior exposure to OEM system validation.

The position requires close collaboration with BSP, OEM QA, and automation teams to ensure CI/CD quality compliance and timely issue resolution.

Key Responsibilities

Device Setup & Configuration

• Flash builds onto Yukon boards and OEM devices.
• Configure UEFI, OS images, and KDNET settings for debugging.
• Enable crash dump collection and install SoC, GPU, and platform drivers.

Testing & Validation

• Develop, execute, and maintain manual and automated test cases.
• Perform functional, stress, power, and performance testing on internal and OEM devices.
• Conduct exploratory testing to identify corner-case scenarios (expertise in one or more subsystems preferred).
• Validate power states, hibernate cycles, and Modern Standby functionality.
• Support certification readiness activities including USB4 and DP tunneling validation.

Debugging & Issue Management

• Triage internal and OEM defects; track reproducibility and resolution status.
• Collect logs, crash dumps, and perform root cause analysis.
• Utilize debugging tools such as WinDbg and KDNET.
• Perform memory debugging and analyze system-level issues.

CI/CD & Reporting

• Ensure quality and compliance of BSP builds within CI/CD pipelines.
• Upload and document test results accurately.
• Prepare detailed test execution reports and communicate findings to stakeholders.
• Support build readiness and release validation processes.

Collaboration

• Work closely with BSP, OEM QA, and automation teams.
• Coordinate with internal and external stakeholders for validation and issue resolution.

Required Skills & Qualifications

• 5–8 years of experience in Windows-based QA and BSP validation.
• Strong hands-on experience with Windows BSP testing and platform setup.
• Experience with UEFI flashing, KDNET debugging, and crash dump analysis.
• Proficiency in bug triage, log analysis, and defect reporting tools.
• Solid understanding of power management states, hibernate cycles, and Modern Standby.
• Experience with OEM device validation and system-level testing.
• Familiarity with CI/CD pipelines for BSP builds and QA automation.
• Experience with Intel and AMD platforms.
• Knowledge of USB4, DP tunneling, and certification readiness tasks.
• CUDA knowledge is preferred.

Summary:

The Computed Tomography (CT) Technologist will perform a wide variety of routine and advanced imaging procedures, will provide support for other imaging technologists as needed, and will help to facilitate smooth and efficient patient flow. The CT Technologist will demonstrate flexibility by working other shifts and/or at other campuses as needed or required. The CT Technologist must be able to troubleshoot basic maintenance, participate in QA, and resolve issues related to image processing and the image archiving system. Expectation to participate in ongoing education, safety, and technical advances within their scope of licensure. The CT Technologist will adhere to and maintain expected imaging competencies as management outlines. Behavior and communication skills must align with the organization's mission, values, and culture.

Responsibilities:

• Meets expectations of the applicable OneCHRISTUS Competencies: Leader of Self, Leader of Others, or Leader of Leaders.
• Demonstrates adherence to the Core Values of CHRISTUS Health.
• Maintains consistency with Administrative and Departmental policies with appropriate behavior, dress, attitude, attendance, confidentiality, professionalism, and reliability.
• Promotes staff growth, development, and employee engagement by collaborating with management, coworkers, and physicians to create an optimal work environment.
• Promotes exceptional physician satisfaction by providing meaningful assistance to radiologists and referring physicians.
• Performs all duties in a manner that protects the confidentiality of patients and does not solicit or disclose any confidential information unless it is necessary in the performance of assigned job duties.
• Appropriately adapt assigned patient assessment, treatment, and/or care methods to accommodate the unique physical, psychosocial, cultural, spiritual, age-specific, and other developmental needs of each patient served.
• Ensures compliance with all policies, procedures, and standards of care as deemed appropriate by State and Federal agencies, the hospital, and other regulatory entities.
• Performs examinations/procedures as needed to assist in patient throughput within the scope of the Manager’s license(s), certification(s), and/or documented competencies.
• Demonstrates flexibility by working other shifts and at other campuses as needed or required.
• Ensures completed exams are scanned and stored correctly in PACS.
• Ability to follow PACS downtime procedures as a PACS Superuser and escalate any problem(s) or issue(s) to the PACS administrator or Designee if needed.
• Troubleshoots and reports any equipment malfunctions to the Director/Manager and/or Biomedical personnel;
  does appropriate follow-up.
• Performs other duties as assigned.

Job Requirements:

Education/Skills

• Graduate of an accredited school of Radiology Technology or other accepted and approved equivalent required

Experience

• 1 year of CT experience in a Hospital or Clinical setting preferred
• Basic computer experience required

Licenses, Registrations, or Certifications

• One of the following primary modality certifications is required
  • Radiography (R) by ARRT
  • Nuclear Medicine Technology by ARRT or NMTCB
• Computed Tomography (CT) by ARRT or NMTCB is required within 1 year of hire (CT required upon hire in the state of New Mexico)
• State Licensure required
  • Texas: MRT by TMB
  • Louisiana: LRT (R), (N), or (F) by LSRTBE
  • New Mexico: CT or FUS by MIRTP NMED
• BLS required

Work Schedule:

MULTIPLE SHIFTS AVAILABLE

Work Type:

Full Time