Numenta

Company Name: Numenta
Job Title: Hardware Engineering Intern
Job Description: Job Title: Hardware Engineering Intern Role Summary: Contribute to cutting‑edge machine‑intelligence research by modeling, simulating, and prototyping high‑performance hardware architectures that accelerate deep learning models, with a focus on biologically inspired sparse algorithms. Expectations: - Engage in a 3–4 month full‑time internship (possible extensions up to one year). - Collaborate with senior engineers to analyze and tune systems for speed and accuracy, while deepening hardware engineering skills. Key Responsibilities: - Model and evaluate hardware architectures using analytical and simulation methodologies. - Develop and test virtual prototypes in SystemC or C/C++. - Implement performance‑modeling scripts in Python. - Optimize neural‑network inference performance on CPU/GPU platforms. - Document design decisions and communicate results to cross‑functional teams. Required Skills: - Strong programming in Python and Verilog; familiarity with SystemC/C/C++. - Experience with numerical analysis, machine learning, imaging, graphics, vision, or large‑scale data analytics. - Solid understanding of CPU/GPU architectures, data structures, and assembly or vector ISA (AVX, GPU). - Proficiency in math and probability theory a plus. - Excellent written and verbal communication. Required Education & Certifications: - Currently enrolled in an MS or PhD program (or recent graduate) in Computer Science, Electrical Engineering, or a related field. - Must be eligible to intern in the U.S. (U.S. citizen, Green Card holder, NAFTA citizen, or US university enrollee).

Menlo park, United states

Hybrid

Fresher

19-11-2025

Company Name: Numenta
Job Title: Algorithms and Architecture Intern
Job Description: Job title: Algorithms and Architecture Intern Role Summary: Full‑time internship (3‑4 months) focused on high‑performance machine‑learning architecture. Design, implement, and optimize sparse, biologically inspired neural network algorithms in C++/Python for CPU, GPU, and embedded systems. Contribute to research and application of real‑time, low‑latency solutions. Expectations: - Rapidly acquire knowledge of deep‑learning model execution and hardware constraints. - Develop and refine efficient algorithmic implementations. - Collaborate closely with researchers and engineers in an iterative, agile setting. - Communicate progress through code reviews, documentation, and technical presentations. Key Responsibilities: - Design and implement core learning algorithms in C/C++ with optional Python interfaces. - Profile, benchmark, and tune code for speed and accuracy across CPU, GPU, and embedded targets. - Apply sparse, biologically inspired techniques to accelerate neural network execution. - Analyze system limitations, identify bottlenecks, and propose hardware‑software co‑design solutions. - Participate in experiments, evaluate results, and document findings for publication or internal reports. - Maintain code quality, adhere to style guidelines, and contribute to shared repositories. Required Skills: - Advanced proficiency in C/C++ (modern standards, performance tuning). - Working knowledge of Python for prototyping and data analysis. - Strong understanding of CPU/GPU architectures, memory hierarchies, SIMD/AVX, and optional assembly. - Familiarity with deep‑learning fundamentals and popular frameworks. - Solid grasp of data structures, algorithms, and numerical methods. - Experience with real‑time or high‑performance systems is preferred. - Excellent written and verbal communication; ability to explain complex technical concepts. Required Education & Certifications: - Currently enrolled in or recent graduate from an MS or PhD program (Computer Science, Electrical Engineering, or related field). - Background in mathematics and probability theory; knowledge of machine learning, real‑time graphics, or embedded systems is a plus. - No specific certifications required.

Menlo park, United states

Hybrid

Fresher

19-11-2025

Company Name: Numenta
Job Title: Machine Learning Intern
Job Description: Job title: Machine Learning Intern Role Summary: Full‑time 3‑4 month internship focused on developing and optimizing large‑language‑model (LLM) systems, incorporating biologically inspired sparse algorithms, and improving deep learning performance through code and algorithmic enhancements. Expactations: • Engage with advanced ML research and closely collaborate with senior engineers and researchers. • Deliver functional code, benchmarks, and methodological insights that advance Numenta’s core learning pipelines. • Participate in code reviews, design discussions, and iterative experimentation to refine model speed and accuracy. • Communicate findings clearly through written documentation and verbal presentations. Key Responsibilities: • Design, implement, and test core learning algorithms and optimization routines. • Evaluate and tune existing LLM architectures, focusing on tokenization, transformer layers, training protocols, and inference pipelines. • Accelerate neural network performance using sparse, distributed, and heterogeneous computing strategies (FSDP, custom CUDA/Triton kernels). • Perform profiling and profiling‑guided performance engineering on GPU and CPU pipelines. • Contribute to reproducible research artifacts, including scripts, notebooks, and version‑controlled code repositories. Required Skills: • Strong programming in Python with deep experience using PyTorch (hooks, custom modules, distributed training). • Deep understanding of LLM components: tokenizers, transformer architecture, training tactics, and inference methods. • Analytical ability to diagnose model weaknesses and propose effective mitigations. • Experience with sparsity/sparse learning algorithms is advantageous. • Familiarity or experience writing CUDA, Triton, or high‑performance C++ code is a plus. • Excellent written and verbal communication. • Demonstrated intellectual curiosity and a track record of impactful individual contributions. Required Education & Certifications: • Current enrollment in an MS or PhD program, or recent graduate, in Computer Science or a closely related field. • No mandatory non‑related certifications required.

Menlo park, United states

Hybrid

Fresher

18-11-2025

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