---
title: 'MLOps Engineer at Atomic Machines'
canonical: 'https://feeny.ai/job/mlops-engineer-atomic-machines-emeryville-kkaqm1wtaf8n'
type: 'job'
last_seen: '2026-09-11'
---

# MLOps Engineer at Atomic Machines

- **Company:** Atomic Machines
- **Location:** Emeryville, CA
- **Compensation:** $200k–$250k
- **Posted:** 2026-08-27
- **Last confirmed live:** 2026-09-11
- **Apply:** https://job-boards.greenhouse.io/atomicmachines/jobs/4385503009

## Job description

Atomic Machines is ushering in a new era of micromanufacturing with its Matter Compiler™ technology platform. This platform enables new classes of micromachines to be designed and built by providing manufacturing processes and a materials library that are inaccessible to semiconductor manufacturing methods. It unlocks MEMS manufacturing not only for device classes that could never be produced by semiconductor methods, but also for entirely new categories. Furthermore, this digital platform is fully programmable in the way 3D printing is digital—but whereas 3D printing produces parts of a single material using a single process, the Matter Compiler™ technology platform is a multi-process, multi-material system: bits and raw materials go in, and complete, functional micromachines come out. The Atomic Machines team has also created an exciting first device—made possible only through the Matter Compiler™ technology platform—that we will be unveiling to the world soon.

Our offices are in Emeryville and Santa Clara, California.

About The Role:

We are seeking an MLOps Engineer to join our AI and Modeling & Simulation org within the Data Engineering and Analytics team.

You will build and operate the infrastructure that takes AI and machine learning models from experimentation to reliable production - covering training, deployment, serving, monitoring, and continuous improvement. This is a DevOps-leaning MLOps role centered on the model feedback loop: connecting production signals and expert feedback back to training so models improve as the system operates.

We are looking for senior-level candidates who can take meaningful ownership of production ML infrastructure. The scope and seniority of the role will be shaped by the candidate's experience, technical depth, and demonstrated impact.

You will work closely with Data, AI, Process, Design, and Software engineers in a highly cross-functional environment.

What You’ll Do:

- Build and evolve the MLOps platform and CI/CD: Own the path from experiment to production, including experiment tracking, model registry, packaging, automated training and retraining, deployment, and safe rollout and rollback.
- Operate model serving infrastructure: Build reliable, scalable batch, streaming, and real-time inference for models and digital twins supporting design, process control, scheduling, and inspection.
- Build ML data and feature pipelines: Turn machine telemetry, process and knowledge graphs, images, time-series, agentic conversations, and other production data into contextualized, model-ready datasets and features.
- Maintain ML data infrastructure: Support feature-store capabilities and a lakehouse foundation using Apache Iceberg on S3, with strong data quality, lineage, versioning, and reproducibility.
- Close the model feedback loop: Build model observability and human-in-the-loop systems that capture production signals and expert corrections, version them as ground truth, and feed them into evaluation and retraining workflows.
- Create paved roads for ML development: Develop standardized tooling and workflows that enable Data and AI engineers to move quickly while maintaining production reliability and reproducibility.
- Drive technical ownership: Identify infrastructure, reliability, and scalability challenges and drive solutions from design through production. More senior candidates will have opportunities to shape architecture, technical direction, and engineering practices across the ML platform.
- Collaborate across disciplines: Work with Process, Chemical, Materials, Simulation, Software, Data, and AI engineers to define deployment, serving, and data-collection requirements.

What You’ll Need:

- 5+ years of relevant industry experience building production software, infrastructure, data, or machine learning systems. We value demonstrated technical depth, ownership, and impact over a specific number of years.
- Proven experience building and operating machine learning systems in production, with a strong MLOps/DevOps orientation.
- Strong DevOps fundamentals, including CI/CD, containers, Kubernetes, cloud infrastructure, and infrastructure-as-code.
- Proficiency in Python and SQL.
- Hands-on experience with MLflow or similar tooling for experiment tracking, model registry, and model lifecycle management.
- Experience with S3, lakehouse technologies such as Apache Iceberg, and workflow orchestration tools such as Airflow or Dagster.
- Experience building pipelines for multimodal ML data, including images, time-series, structured, and semi-structured data.
- Familiarity with manufacturing systems, sensors, process automation, or other physical-world data systems.
- Strong problem-solving skills, attention to data quality and reliability, and clear technical communication.
- Bachelor's or Master's degree in Computer Science, Data Engineering, Data Science, or a related STEM field, or equivalent practical experience.
- This role is open across multiple levels, from early in career though Staff (L4 through L6). We'll determine the appropriate level and compensation based on your experience, skills, and the scope of the role through the interview process.

Bonus Points For:

- Experience with feature stores, human-in-the-loop systems, active learning, or data-labeling infrastructure.
- Robotics or robotic automation experience, including sensors, vision systems, or robotics data.
- Experience operating ML systems in manufacturing or other physical-world environments.
- Experience building internal tools for expert feedback, labeling, model evaluation, or model interaction.
- Experience designing shared ML infrastructure or platforms used across multiple teams or applications.

The compensation for this position also includes equity and benefits.

Salary Range $200,000—$250,000 USD

## About Atomic Machines

## Company Overview
- **One-liner**: Atomic Machines is building a new robotic micro-manufacturing platform to create a class of micro-electromechanical (MEMS) devices unattainable with traditional semiconductor-based fabrication.
- **Entity Type**: Private (Series B)
- **Headquarters**: Berkeley, California, USA (with additional offices in Emeryville and Santa Clara, CA) [pitchbook.com](https://pitchbook.com/profiles/company/461907-37)
- **Founded**: 2019 [pitchbook.com](https://pitchbook.com/profiles/company/461907-37)
- **Founders**: Not publicly available

## Core Business
- **Primary industry/industries**: Advanced Manufacturing, Nanotechnology, Robotics, MEMS (Micro-Electromechanical Systems), Machinery (B2B), Semiconductors [pitchbook.com](https://pitchbook.com/profiles/company/461907-37)
- **Target customers**: B2B — technology innovators and manufacturers in the AI data center world and broader tech industry requiring rapid prototyping and large-scale production of micro-devices [atomicmachines.com](https://www.atomicmachines.com/)
- **Mission or purpose statement**: "Redefining humanity’s relationship with matter" — building the machines that make everything, taking digital manufacturing to the extreme [builtin.com](https://builtin.com/company/atomic-machines)

## Products & Services
- **MEMS 2.0 Platform**: A proprietary robotic manufacturing technology stack that breaks traditional paradigms of silicon-fab-based MEMS fabrication, enabling new classes of microdevices with radically shorter development lifecycles [atomicmachines.com](https://www.atomicmachines.com/)
- **First Commercial Device**: A product addressing a critical need in the rapidly evolving AI data center world, currently being commercialized [atomicmachines.com](https://www.atomicmachines.com/join)
- **Microelectromechanical Systems Power Relay**: Patented technology (multiple patents filed globally) for power relay applications [pitchbook.com](https://pitchbook.com/profiles/company/461907-37)

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed (private company)
- **Key Metric**: Total funding raised — **$144M** across two rounds (Series A in Nov 2022, Series B in Feb 2025) [pitchbook.com](https://pitchbook.com/profiles/company/461907-37)
- **Notable Investors/Partners**: Sozo Ventures, XTX Ventures, Deep Ventures, and individual angel investors (10 total investors) [pitchbook.com](https://pitchbook.com/profiles/company/461907-37)
- **Growth Signals**: Strong product/market fit with a clear go-to-market path; headcount of 134 employees (as of 2026) growing rapidly; well-funded with $75M Series B raised in Feb 2025; active patent portfolio [pitchbook.com](https://pitchbook.com/profiles/company/461907-37) [atomicmachines.com](https://www.atomicmachines.com/join)

## Competitive Advantages
- **Proprietary Technology Stack**: A completely new micro-manufacturing approach that is not based on traditional semiconductor/MEMS fabrication — a fundamental innovation rather than an incremental improvement [atomicmachines.com](https://www.atomicmachines.com/)
- **Extreme Digital Manufacturing**: Enables "unimaginably short product development lifecycles" and rapid prototyping with compelling economics [atomicmachines.com](https://www.atomicmachines.com/join)
- **First-Mover Advantage in MEMS 2.0**: Breaking traditional manufacturing paradigms for a new class of microdevices
- **Patented IP**: Multiple active and pending patents for microelectromechanical systems power relay technology [pitchbook.com](https://pitchbook.com/profiles/company/461907-37)

## Strategic Focus
- **Commercialization**: Scaling the first device targeting the AI data center market [atomicmachines.com](https://www.atomicmachines.com/join)
- **Platform Expansion**: Building the full "matter compiler" — the machines that make everything — from rapid prototyping to large-scale production [atomicmachines.com](https://www.atomicmachines.com/)
- **Talent Aggregation**: Actively hiring across multiple disciplines (AI, software, hardware, manufacturing, IT security, finance) to build a world-class multi-disciplinary team [greenhouse.io](https://job-boards.greenhouse.io/atomicmachines)

## Why Work Here
- **Mission-Driven Work**: A rare opportunity to work on a "world-changing mission" to democratize the power to make physical things — from bits to atoms [atomicmachines.com](https://www.atomicmachines.com/join)
- **Apolitical Maker Culture**: The company explicitly states it is building "an apolitical maker culture of continuous invention, operational excellence and idea meritocracy" with information transparency [atomicmachines.com](https://www.atomicmachines.com/join)
- **Significant Equity**: Employees receive significant equity compensation and are treated as true company owners who benefit financially from overall success [builtin.com](https://builtin.com/company/atomic-machines)
- **Multi-Disciplinary Environment**: Work alongside incredibly talented engineers, scientists, and builders across robotics, MEMS, software, AI, and manufacturing [atomicmachines.com](https://www.atomicmachines.com/join)
- **Work Policy**: In-Office — employees work from physical offices in Emeryville, Santa Clara, or Berkeley, CA [builtin.com](https://builtin.com/company/atomic-machines) [greenhouse.io](https://job-boards.greenhouse.io/atomicmachines)
- **Growth Opportunity**: Join as an early-stage company (founded 2019, still stealth) with strong funding and clear product/market fit — opportunity to help define the company from its early days [builtin.com](https://builtin.com/company/atomic-machines)

## Sources
1. [atomicmachines.com](https://www.atomicmachines.com/)
2. [atomicmachines.com/join](https://www.atomicmachines.com/join)
3. [greenhouse.io](https://job-boards.greenhouse.io/atomicmachines)
4. [pitchbook.com](https://pitchbook.com/profiles/company/461907-37)
5. [builtin.com](https://builtin.com/company/atomic-machines)

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