Entry Level Performance Architect Jobs
New grad performance architect jobs welcome recent graduates and entry level candidates with zero to two years of experience, where a strong portfolio or internship project can carry more weight than a long resume. Most openings reflect a mix of on-site, remote, and hybrid settings across Technology & Software, Electronics & Hardware, and Telecommunications, with employers like Qualcomm and I Machines hiring at this level now.
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Showing 5 of 8+ Entry Level Performance Architect jobs
About Our Company
We’re a fast-paced, fabless semiconductor startup redefining the boundaries of AI through cutting-edge, scalable AI-infused compute architecture. Our mission is to deliver scalable, efficient, and intelligent silicon solutions for the next generation of edge AI, robotics, autonomous systems, and mobile devices. Our leadership team brings together decades of experience in semiconductor innovation, spanning chip architecture, system design, and global business operations. The team includes pioneers behind several generations of groundbreaking compute architectures, experts in software-hardware co-design, SoC and AI development with hundreds of patents in our portfolio as well as leaders of multi-billion-dollar business units at top-tier technology companies.
Position Overview
We are seeking an AI/ML Performance Architect to join our Architecture and Performance Modeling team. This role is focused on AI/ML inference performance on CPUs, with a strong emphasis on model architecture, quantization, and software–hardware co-design. You will work close to the metal—bridging modern AI frameworks with CPU microarchitecture—to analyze, model, and optimize AI workloads for scalable, power-efficient inference. This is a hands-on, deeply technical role for engineers who thrive at the intersection of machine learning systems, compilers, and CPU architecture.
Key Responsibilities and Duties
- Analyze and optimize AI/ML inference workloads on CPU platforms with a focus on performance, efficiency, and scalability.
- Optimize CPU-focused inference frameworks and runtimes (e.g., llama.cpp and similar lightweight engines) to identify bottlenecks and improve kernel-level performance.
- Develop a deep understanding of ML model architectures (Transformers, LLMs, CNNs) and map their compute and memory characteristics to modern CPU microarchitectures.
- Perform low-level performance tuning, including:
- Instruction-level and microarchitectural analysis
- Cache, memory hierarchy, and data-movement optimization
- SIMD/vectorization and multi-threading optimizations
- Design and implement quantization, pruning, and model-compression strategies, including PTQ, QAT, and mixed-precision inference (INT8/INT4).
- Create and evaluate preprocessing and graph-level optimizations such as operator fusion, graph restructuring, and unsupported-op replacement.
- Collaborate closely with CPU architects, compiler teams, and system software engineers to influence architectural features and software design decisions.
- Build and use performance analysis tools, micro-benchmarks, profiling pipelines, and roofline models.
- Contribute to performance modeling, workload characterization, and end-to-end inference analysis across hardware and software stacks.
Qualifications and Skills
Successful candidates should possess the following qualifications and skills:
Required Qualifications
(You must possess the following skills to be considered for this position)
- MS or PhD in Computer Science, Electrical Engineering, or Computer Engineering.
- MS with 2–5 years of industry experience or PhD with 0–3 years of industry experience in performance engineering, ML systems, or computer architecture.
- Strong experience optimizing AI/ML inference frameworks on CPUs.
- Solid understanding of modern ML model architectures, quantization techniques, and fine-tuning workflows.
- Hands-on expertise in low-level performance tuning, including:
- C/C++ optimization
- Profiling and performance analysis tools
- Cache, memory, and compute efficiency optimization
- Strong fundamentals in computer architecture and systems.
- Proficiency in C/C++; working knowledge of Python for tooling, analysis, or model workflows.
Preferred / Nice-to-Have Qualifications
- Familiarity with RISC-V architecture and ecosystem.
- Experience with CPU microarchitecture concepts such as:
- Vector ISAs and SIMD execution
- Memory consistency and coherency
- Pipeline behavior and execution scheduling
- Exposure to performance modeling, analytical models, or architectural simulators.
- Familiarity with ML compiler stacks (MLIR, LLVM, XLA) and custom lowering passes.
- Hands-on experience with ONNX, TorchScript, Apache TVM, or similar toolchains.
- Experience working at the hardware–software boundary, including custom kernels and inference runtimes.
Why Join Us
- Get in early at a breakthrough deep-tech startup reshaping AI compute.
- Work closely with industry innovators and experienced leaders where your work will have a direct impact on the success of the company.
- Be part of a mission-driven team building foundational technology for the future.
- We balance sharp execution with continuous innovation to push the boundaries.
- Competitive compensation, equity, and growth opportunities.
Benefits and Perks
At I Machines, Inc., we offer competitive salaries and a comprehensive benefits package, including:
- Health, dental, and vision insurance
- Retirement savings plans
- Paid time off and holidays
- Professional development opportunities
- Flexible Schedule
Equal Opportunity Employer
I Machines, Inc. is an equal opportunity employer and does not discriminate based on race, color, religion, gender, national origin, age, disability, or any other legally protected status. All qualified applicants will be considered for employment.
About Our Company
We’re a fast-paced, fabless semiconductor startup redefining the boundaries of AI through cutting-edge, scalable AI-infused compute architecture. Our mission is to deliver scalable, efficient, and intelligent silicon solutions for the next generation of edge AI, robotics, autonomous systems, and mobile devices. Our leadership team brings together decades of experience in semiconductor innovation, spanning chip architecture, system design, and global business operations. The team includes pioneers behind several generations of groundbreaking compute architectures, experts in software-hardware co-design, SoC and AI development with hundreds of patents in our portfolio as well as leaders of multi-billion-dollar business units at top-tier technology companies.
Position Overview
We are seeking an AI/ML Performance Architect to join our Architecture and Performance Modeling team. This role is focused on AI/ML inference performance on CPUs, with a strong emphasis on model architecture, quantization, and software–hardware co-design. You will work close to the metal—bridging modern AI frameworks with CPU microarchitecture—to analyze, model, and optimize AI workloads for scalable, power-efficient inference. This is a hands-on, deeply technical role for engineers who thrive at the intersection of machine learning systems, compilers, and CPU architecture.
Key Responsibilities and Duties
- Analyze and optimize AI/ML inference workloads on CPU platforms with a focus on performance, efficiency, and scalability.
- Optimize CPU-focused inference frameworks and runtimes (e.g., llama.cpp and similar lightweight engines) to identify bottlenecks and improve kernel-level performance.
- Develop a deep understanding of ML model architectures (Transformers, LLMs, CNNs) and map their compute and memory characteristics to modern CPU microarchitectures.
- Perform low-level performance tuning, including:
- Instruction-level and microarchitectural analysis
- Cache, memory hierarchy, and data-movement optimization
- SIMD/vectorization and multi-threading optimizations
- Design and implement quantization, pruning, and model-compression strategies, including PTQ, QAT, and mixed-precision inference (INT8/INT4).
- Create and evaluate preprocessing and graph-level optimizations such as operator fusion, graph restructuring, and unsupported-op replacement.
- Collaborate closely with CPU architects, compiler teams, and system software engineers to influence architectural features and software design decisions.
- Build and use performance analysis tools, micro-benchmarks, profiling pipelines, and roofline models.
- Contribute to performance modeling, workload characterization, and end-to-end inference analysis across hardware and software stacks.
Qualifications and Skills
Successful candidates should possess the following qualifications and skills:
Required Qualifications
(You must possess the following skills to be considered for this position)
- MS or PhD in Computer Science, Electrical Engineering, or Computer Engineering.
- MS with 2–5 years of industry experience or PhD with 0–3 years of industry experience in performance engineering, ML systems, or computer architecture.
- Strong experience optimizing AI/ML inference frameworks on CPUs.
- Solid understanding of modern ML model architectures, quantization techniques, and fine-tuning workflows.
- Hands-on expertise in low-level performance tuning, including:
- C/C++ optimization
- Profiling and performance analysis tools
- Cache, memory, and compute efficiency optimization
- Strong fundamentals in computer architecture and systems.
- Proficiency in C/C++; working knowledge of Python for tooling, analysis, or model workflows.
Preferred / Nice-to-Have Qualifications
- Familiarity with RISC-V architecture and ecosystem.
- Experience with CPU microarchitecture concepts such as:
- Vector ISAs and SIMD execution
- Memory consistency and coherency
- Pipeline behavior and execution scheduling
- Exposure to performance modeling, analytical models, or architectural simulators.
- Familiarity with ML compiler stacks (MLIR, LLVM, XLA) and custom lowering passes.
- Hands-on experience with ONNX, TorchScript, Apache TVM, or similar toolchains.
- Experience working at the hardware–software boundary, including custom kernels and inference runtimes.
Why Join Us
- Get in early at a breakthrough deep-tech startup reshaping AI compute.
- Work closely with industry innovators and experienced leaders where your work will have a direct impact on the success of the company.
- Be part of a mission-driven team building foundational technology for the future.
- We balance sharp execution with continuous innovation to push the boundaries.
- Competitive compensation, equity, and growth opportunities.
Benefits and Perks
At I Machines, Inc., we offer competitive salaries and a comprehensive benefits package, including:
- Health, dental, and vision insurance
- Retirement savings plans
- Paid time off and holidays
- Professional development opportunities
- Flexible Schedule
Equal Opportunity Employer
I Machines, Inc. is an equal opportunity employer and does not discriminate based on race, color, religion, gender, national origin, age, disability, or any other legally protected status. All qualified applicants will be considered for employment.
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Entry Level Performance Architect Jobs: Frequently Asked Questions
How do I get an entry level performance architect job?
Entry level performance architect roles reward candidates who can show practical work: a portfolio of optimization projects, internship results, or coursework tied to real systems. Employers at this level look for familiarity with performance testing tools, an understanding of system bottlenecks, and the ability to interpret data. Highlighting measurable outcomes from academic or personal projects gives junior candidates a clear edge over a bare resume.
Which companies hire entry level performance architects?
Companies hiring entry level performance architects right now include Qualcomm and I Machines, based on current listings on Migrate Mate as of November 2026. At this level, hiring comes from a range of organizations including mid-size technology firms, consulting shops, and enterprise teams that build internal performance engineering practices and need junior talent to grow into those functions.
Are there remote entry level performance architect jobs?
Yes, though availability varies by employer and role type. About 0% of entry level performance architect openings are remote or hybrid as of November 2026, giving new grads real flexibility in where they work. On-site roles still exist, particularly at companies where engineers collaborate closely on live infrastructure, so it is worth checking each listing for the work setting before applying.
Are these new grad performance architect jobs?
Yes, many of the openings here are new grad and junior roles that explicitly welcome candidates with limited professional experience. A new grad friendly posting typically invites applicants with zero to two years of experience, accepts internship or academic work as qualifying background, and does not require prior full-time performance engineering history. Recent graduates and career changers who can show relevant project work are well positioned for these roles.
Which industries hire the most entry level performance architects?
Entry Level performance architect roles concentrate in Technology & Software, Electronics & Hardware, and Telecommunications, based on current listings on Migrate Mate as of November 2026. These sectors drive hiring at this level because they operate at scale, where even small performance gaps have measurable business impact, and they invest in junior talent to build long-term engineering capability rather than relying solely on experienced hires.