---
title: 'Machine Learning Engineer - New Grad at SambaNova Systems'
canonical: 'https://feeny.ai/job/machine-learning-engineer-new-grad-sambanova-systems-austin-0mtfjwqptra2'
type: 'job'
last_seen: '2026-11-10'
---

# Machine Learning Engineer - New Grad at SambaNova Systems

- **Company:** SambaNova Systems
- **Location:** Austin, TX / San Jose, CA
- **Compensation:** $131k–$197k
- **Posted:** 2026-11-03
- **Last confirmed live:** 2026-11-10
- **Apply:** https://sambanova.ai/sambanova-available-positions/?gh_jid=6240725004

## Job description

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

The Machine Learning team builds the model-side techniques that make SambaNova’s platform fast and capable. We train speculative decoding models that accelerate inference, develop efficient ML methods such as quantization, sparsity, and distillation, and build agentic systems on top of our foundation model serving stack. Our work spans research, applied science, and production, from novel approach design to proofs of concept and shipping to product. Reinforcement learning and post-training are within our scope and a growing part of our roadmap.

## About the Role

As a new grad Machine Learning Engineer, you’ll train and evaluate models that make large language models cheaper and more capable to serve. Depending on your interests, that could mean training speculator (draft) models and tuning acceptance rates, compressing models without losing accuracy, or designing and evaluating agentic workflows for tool use, planning, and long-horizon tasks. You’ll work closely with the AI performance, compiler, and runtime teams to turn research results into measured end-to-end wins, and you’ll have room to pursue open problems as our reinforcement learning and post-training work ramps up.

## Responsibilities

- Train, evaluate, and tune speculative decoding models (Dspark/Dflash, Medusa/Eagle-style heads, and multi-token prediction) to increase acceptance rates on production workloads.
- Develop and implement optimization techniques, including quantization, sparsity, distillation, pruning, and parameter-efficient fine-tuning, to quantify the trade-offs between model quality, latency, and resource efficiency.
- Build and evaluate agentic systems: tool calling, multi-step planning, retrieval, and long-context reasoning on top of our serving stack.
- Design rigorous evaluations and benchmarks; make accuracy and quality claims that hold up under scrutiny
- Translate recent research into working implementations, and run ablations to understand what actually drives the result
- Partner with the AI performance, compiler, runtime, and product teams to ship model improvements into SambaNova products
- Contribute to emerging areas such as reinforcement learning, post-training, and reward modeling as the roadmap expands

Required Qualifications

- B.S. in Computer Science, Electrical Engineering, Mathematics, or a related field
- Strong programming skills in Python
- Solid foundation in machine learning, linear algebra, probability, and numerical computing
- Hands-on experience with PyTorch, TensorFlow, or JAX
- Working knowledge of transformer architectures and the LLM training or inference pipeline
- Ability to design a clean experiment, interpret results honestly, and communicate findings clearly

## Preferred Qualifications

- M.S. or Ph.D. in Computer Science, Electrical Engineering, or a related field
- Research or internship experience in LLM training, post-training, or inference
- Experience with speculative decoding, distillation, quantization, sparsity, or other model efficiency techniques
- Experience building agentic systems, tool-calling pipelines, or LLM evaluation harnesses
- Familiarity with reinforcement learning or preference optimization (RLHF, DPO, GRPO, reward modeling)
- Experience with distributed training frameworks (FSDP, DeepSpeed, Megatron) or inference frameworks such as vLLM, SGLang, or TensorRT-LLM
- Publications at ML venues (NeurIPS, ICML, ICLR, ACL, EMNLP) or meaningful open source contributions

Base Salary Range:

Base Pay Range $131,200—$196,800 USD

Submission Guidelines Please 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 Policy

SambaNova 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 Positions SambaNova 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.

## About SambaNova Systems

## Company Overview
- **One-liner**: SambaNova Systems provides a full-stack AI platform, from specialized Reconfigurable Dataflow Unit (RDU) chips to an agentic AI inference platform, designed for enterprises and governments.
- **Entity Type**: Private (Series E)
- **Headquarters**: San Jose, California, USA
- **Founded**: 2017
- **Founders**: Rodrigo Liang (Co-founder & CEO), Kunle Olukotun (Co-founder & Chief Technologist)

## Core Business
- **Primary Industry**: Artificial Intelligence / Enterprise AI Infrastructure
- **Target Customers**: Developers, large enterprises, government agencies, and data centers (B2B)
- **Mission Statement**: To be the most efficient and adaptable AI platform on the planet, empowering enterprises to control the trajectory of their data and AI future.

## Products & Services
- **SambaNova Suite**: The company's core product, a fully integrated AI platform that includes hardware, software, and models. It provides OpenAI-compatible APIs for inference.
- **SambaRack (SN40 & SN50)**: A state-of-the-art, rack-scale system optimized for AI inference. The SN50 is the fifth-generation system designed for fast agentic inference with high energy efficiency (average of 10 kWh for SN40).
- **Reconfigurable Dataflow Unit (RDU)**: A custom-designed AI chip (SN40L, SN50) with a unique three-tier memory architecture that delivers high speed and throughput for large models while using less power than traditional GPUs.
- **SambaOrchestrator**: A management tool for deploying, monitoring, and auto-scaling AI models across data centers.
- **Sovereign AI Platform**: An offering for governments and enterprises to keep data secure and governed while enabling business teams to use AI.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed (Private company).
- **Key Metric**: Total funding of **$1.484B** (raised over multiple rounds, including a $350M Series E in early 2026).
- **Notable Investors/Partners**: Intel, GV (Google Ventures), BlackRock, Redline Capital Management, Atlantic Bridge Capital.
- **Growth Signals**: 
    - Raised a $350M Series E in early 2026.
    - A launch partner for Meta's Llama 4 series.
    - First platform to support all three variants of Llama 3.1 (8B, 70B, and 405B).
    - Has filed 313 patents related to parallel computing, computer memory, and instruction processing.
    - Customers include Blackbox and Texas Advanced Computing Center.

## Competitive Advantages
- **Full-Stack Integration**: Unlike many competitors, SambaNova controls the entire AI stack from the chip (RDU) to the software and models, allowing for deep optimization.
- **Efficiency**: The RDU's dataflow architecture is designed for high performance with significantly lower power consumption (best tokens per watt), a key differentiator for scaling AI.
- **Open-Source Focus**: The company is a strong supporter of open-source AI models, being a launch partner for major releases like Meta's Llama 4.

## Strategic Focus
- **Agentic AI**: The company is heavily focused on enabling complex, multi-step agentic AI workflows, with the SN50 chip and SambaOrchestrator built for this purpose.
- **Sovereign AI**: Targeting government and enterprise clients who need secure, on-premises or private cloud AI solutions.
- **Scaling Inference**: Prioritizing high-speed, low-latency inference for the largest open-source models (e.g., DeepSeek, Llama) at scale.

## Why Work Here
- **Culture**: Described as a "smart and motivated team" that values "talent first," "innovation that impacts," and "trust and integrity." The company emphasizes collaboration across departments and access to founders.
- **Work Environment**: Offers flexible working hours and a hybrid/remote-friendly policy (Flexible PTO in the U.S.).
- **Notable Perks**: 
    - Flexible PTO
    - Parental Leave
    - Medical, Dental, and Vision benefits
    - 401k/Pensions
    - Gym Access
    - Mentorship and buddy programs
    - Internship programs
- **Engineering Culture**: A deep-tech environment where you work on cutting-edge AI hardware (RDUs) and software, pushing the boundaries of AI performance.

## Sources
1. [SambaNova.ai](https://sambanova.ai/)
2. [SambaNova About Us](https://sambanova.ai/company/about)
3. [SambaNova Careers](https://sambanova.ai/company/careers)
4. [SambaNova Job Openings](https://sambanova.ai/company/careers/job-openings)
5. [CB Insights Profile](https://www.cbinsights.com/company/sambanova-systems)

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