Artificial Intelligence

Senior Principal Model Bring-up Engineer

Austin, TXOnsiteFull TimePrincipal$208,000–$312,000 /yrPosted 9 days agoVisa sponsorship available

Is this role right for you?

Upload your resume and get a skill-by-skill breakdown — see exactly where you match, where you're close, and what to highlight. Not a mystery percentage.

Get a tailored resume highlighting what this role needs.

Required skills

open-weight models
dense models
mixture-of-experts
hybrid Mamba/attention
sliding-window attention
multi-token prediction
Hugging Face
SambaNova RDU
dataflow accelerators
compiling

Nice to have

dataflow compilers
spatial compilers
kernel DSLs
Mamba
SSMs
multi-agent AI engineering workflows

Role summary

SambaNova Systems is seeking a Senior Principal Model Bring-up Engineer to productionize frontier open-weight models on their RDU dataflow accelerators. This role involves adapting, mapping, compiling, and numerically validating LLM architectures, including dense, MoE, and hybrid Mamba/attention models. Responsibilities include building shared inference features like continuous batching, speculative decoding, and FP8/FP4 support, and debugging model-compiler-hardware interactions. The ideal candidate has 8+ years of experience in ML systems, inference, or compiler engineering, with strong Python, PyTorch internals, and C++ skills, deep transformer-inference knowledge, and hands-on experience with ML compilers or inference engines. Experience with accelerator bring-up and numerical debugging is crucial.

SambaNova is a leader in next-generation AI infrastructure, delivering a full-stack inference platform for customers worldwide. At the core of SambaNova's technology is the RDU (Reconfigurable Dataflow Unit) — a chip built on a dataflow architecture rather than the traditional GPU model. Its decode performance is especially strong for agentic workloads like multi-turn agents, code generation, and long-running applications. RDUs are packaged into SambaRack, rack-scale hardware that lets customers deploy state-of-the-art models with better performance, greater energy efficiency, and faster time to value.

About the team

We take frontier open-weight models (dense, mixture-of-experts with hundreds of experts, hybrid Mamba/attention, sliding-window attention, multi-token prediction) from Hugging Face to production serving on SambaNova's RDU dataflow accelerators. That means compiling them, proving them numerically correct against the reference, serving them with the full feature set, and merging the work into a shared stack so the next model is cheaper.

About the role

You will bring new open-weight LLMs, including dense, mixture-of-experts, and hybrid Mamba/attention architectures, up on SambaNova’s RDU dataflow accelerators and into production serving. That means adapting the model, mapping it across chips and hosts, compiling it, and validating it numerically against the reference. You also build inference features like continuous batching, speculative decoding, and FP8/FP4 as shared modules, so each new model costs less to bring up.

Responsibilities

Bring up new LLM architectures end to end: model adaptation, checkpoint conversion, multi-chip / multi-host mapping, compile, strict numerical validation, production serving with latency / throughput numbers.

Build inference features once as shared modules: continuous batching over a paged KV pool, prompt caching, chunked and incremental prefill, dynamic tensor shapes, speculative decoding (EAGLE-3, drafters, MTP), FP8 / FP4, tensor and expert parallelism.

Debug where model, compiler and hardware meet; land each fix in the right shared component.

Required qualifications

B.S. in Computer Science, Electrical Engineering, or related field

8+ years of industry experience in ML systems, inference, or compiler engineering

Strong Python and PyTorch internals experience, plus some C++

Deep transformer-inference knowledge, including KV caching, GQA and sliding window attention, MoE routing, prefill vs decode, batching, and speculative decoding

Hands-on experience with accelerator bring-up, ML compilers (MLIR, XLA, TVM, Triton, torch-mlir), or inference engines (vLLM, SGLang, TensorRT-LLM)

Rigor in numerical debugging

Comfort with Bazel, Slurm, and large monorepos

Clear writing and evidence-backed claims

Preferred qualifications

M.S. or Ph.D. in Computer Science, Electrical Engineering, or related field

Experience with dataflow or spatial compilers

Experience with kernel DSLs

Experience with FP8 and FP4 inference

Experience with Mamba and SSMs

Experience with expert parallelism

Experience with multi-agent AI engineering workflows

Open-source inference or compiler contributions

Success in six months

Own a model family from first compile to served and merged; turn a one-model fix into a shared module others adopt; measurably shorten one long loop for the team.

Base Salary Range:

Base Pay Range$208,000—$312,000 USD

Submission GuidelinesPlease note that in order to be considered an applicant for any position at SambaNova Systems, you must submit an application form for each position for which you believe you are qualified.

EEO PolicySambaNova Systems is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws.

Benefits Summary for US-Based, Full-Time Employment PositionsSambaNova offers a competitive total rewards package, including the base salary, plus equity and benefits. We cover 95% premium coverage for employee medical insurance, and 77% premium coverage for dependents and offer a Health Savings Account (HSA) with employer contribution. We also offer Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life, and AD&D insurance plans in addition to Flexible Spending Account (FSA) options like Health Care, Limited Purpose, and Dependent Care. Our library of well-being benefits available to you and your dependents includes a full subscription to Headspace, Gympass+ membership with access to physical gyms, One Medical membership, counseling services with an Employee Assistance Program, and much more.

Ready to apply?

You'll be redirected to SambaNova Systems's application page.