Software Engineer, Staff - Kernel

Company:  Money Fit by DRS
Location: Santa Clara
Closing Date: 02/11/2024
Salary: £150 - £200 Per Annum
Hours: Full Time
Type: Permanent
Job Requirements / Description

Location: Santa Clara, CA

Type: Full time

Department: R&D - SW Kernels & Workloads

Compensation: IC3 - $90K – $150K • Offers Equity • Offers Bonus

The pay range below is for all roles at this level across all US locations and functions. Individual pay rates depend on a number of factors—including the role’s function and location, as well as the individual’s knowledge, skills, experience, education, and training. We also offer incentive opportunities that reward employees based on individual and company performance. This is in addition to our diverse package of benefits centered around the wellbeing of our employees and their loved ones.

About d-Matrix: d-Matrix has fundamentally changed the physics of memory-compute integration with our digital in-memory compute (DIMC) engine. We’ve achieved this with a first-of-its-kind DIMC engine. Having secured over $154M, $110M in our Series B offering, d-Matrix is poised to advance Large Language Models to scale Generative inference acceleration with our chiplets and In-Memory compute approach. We are on track to deliver our first commercial product in 2024.

Location: Hybrid, working onsite at our Santa Clara, CA headquarters 3 days per week.

The role: Software Engineer, Staff - Kernels

What you will do: The role requires you to be part of the team that helps productize the SW stack for our AI compute engine. As part of the Software team, you will be responsible for the development, enhancement, and maintenance of software kernels for next-generation AI hardware. You possess experience building software kernels for HW architectures. You possess a very strong understanding of various hardware architectures and how to map algorithms to the architecture. You understand how to map computational graphs generated by AI frameworks to the underlying architecture. You have had past experience working across all aspects of the full stack tool chain and understand the nuances of what it takes to optimize and trade-off various aspects of hardware-software co-design. You are able to build and scale software deliverables in a tight development window. You will work with a team of compiler experts to build out the compiler infrastructure working closely with other software (ML, Systems) and hardware (mixed signal, DSP, CPU) experts in the company.

What you will bring:

Minimum:

  • MS or PhD in Computer Engineering, Math, Physics or related degree with 3+ years of industry experience.
  • Strong grasp of computer architecture, data structures, system software, and machine learning fundamentals.
  • Proficient in C/C++ and Python development in Linux environment and using standard development tools.
  • Experience implementing algorithms in high level languages such as C/C++, Python.
  • Experience implementing algorithms for specialized hardware such as FPGAs, DSPs, GPUs, AI accelerators using libraries such as CuDA etc.
  • Experience in implementing operators commonly used in ML workloads - GEMMs, Convolutions, BLAS, SIMD operators for operations like softmax, layer normalization, pooling etc.
  • Experience with development for embedded SIMD vector processors such as Tensilica.
  • Self-motivated team player with a strong sense of ownership and leadership.

Preferred:

  • Prior startup, small team or incubation experience.
  • Experience with ML frameworks such as TensorFlow and/or PyTorch.
  • Experience working with ML compilers and algorithms, such as MLIR, LLVM, TVM, Glow, etc.
  • Experience with a deep learning framework (such as PyTorch, Tensorflow) and ML models for CV, NLP, or Recommendation.
  • Work experience at a cloud provider or AI compute / sub-system company.

Equal Opportunity Employment Policy: d-Matrix is proud to be an equal opportunity workplace and affirmative action employer. We’re committed to fostering an inclusive environment where everyone feels welcomed and empowered to do their best work.

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