Systems Software Engineer - AI Infrastructure
The Systems Software Engineer - AI Infrastructure at Confidential Client is responsible for designing, deploying, and operating scalable and secure AI platforms that support large-scale AI and machine learning workloads. This role involves researching emerging technologies, integrating hardware and software components, optimizing performance, and ensuring security and compliance to enable reliable AI infrastructure across the company. The engineer collaborates with cross-functional teams to develop reference architectures and standards that drive innovation and efficiency in AI platform development.
About Careertakes
👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Semiconductor Manufacturing.
Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.
What You’ll Do
You will design, build, and operate next-generation AI infrastructure to support large-scale model training, inference, and production AI systems. This role sits at the intersection of systems engineering, MLOps, and DevOps — creating reliable, secure, cost-effective platforms that enable data scientists and ML engineers to deliver production-ready AI.
- Architect, deploy, and operate scalable AI platforms, distributed training clusters, and model serving systems.
- Research and evaluate emerging compute, storage, and networking technologies; produce reference designs and standards for enterprise adoption.
- Integrate and troubleshoot hardware, firmware, OS, and platform-level issues during bring-up and throughout lifecycle.
- Design high-performance storage, networking, and data pipelines for large-scale ML workloads.
- Build observability, monitoring, and performance tuning for GPU/TPU workloads to meet reliability and availability goals.
- Implement security-by-design: encryption, identity/access management, secrets management, and AI data protection.
- Collaborate with ML researchers, data scientists, software engineers, IT, and security teams to align platform capabilities with product goals.
Tools & Technologies
- Linux systems administration, containerization (Docker), Kubernetes, Slurm, Ray
- Machine learning frameworks: TensorFlow, PyTorch; GPU/TPU optimization
- High-speed networking, storage systems, virtualization, server management
- Automation & scripting: Bash, Python, CI/CD, Infrastructure as Code (IaC)
- Security tooling: TPM-based encryption, Kubernetes RBAC, OPA/Gatekeeper, container security
Qualifications
- Degree in Computer Science, Computer Engineering, or a related field
- 5–8 years in systems engineering, DevOps, or ML/AI infrastructure
- Hands-on experience building and operating GPU/AI clusters and distributed training environments
- Strong troubleshooting skills across hardware, OS, and platform layers
- Experience with orchestration and workload schedulers (Kubernetes, Slurm, Ray) and ML frameworks
- Experience with observability, performance tuning, and storage/network architecture for ML workloads
Minimum Qualifications
Doctorate degree with no related work experience; or Master's degree with 3 years related experience; or Bachelor's degree with 5 years related experience.
Compensation & Location
Base Pay Range: $136,300.00 - $199,900.00 Annually
Primary location: Milpitas, CA (USA)
The range above reflects the pay for this position in Milpitas, CA. Actual pay depends on factors like location, experience, and education. Benefits may include medical, dental, vision, life insurance, 401(k) with employer match, employee stock purchase program, tuition reimbursement, wellness programs, paid time off, and parental leave. Specific benefit eligibility and details will be provided during the hiring process.
About the confidential client
The confidential client is a leader in semiconductor manufacturing technologies, delivering advanced inspection, metrology, and analytics solutions that enable high-quality semiconductor production. The team combines physics, high-performance computing, and AI to solve complex challenges across advanced packaging, memory, logic, and specialty processes.
Candidate Experience & Hiring Notes
- This role is full-time and based in Milpitas, CA.
- Interviews assess technical skills, problem solving, and hands-on experience. Use of AI tools in interviews is restricted unless explicitly approved as a reasonable accommodation.
- Reasonable accommodations are available for applicants with disabilities; contact the recruiter or Careertakes for assistance.
Equal Opportunity & Hiring Transparency
Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.
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