---
title: 'Senior AI Engineer at Oligo Space'
canonical: 'https://feeny.ai/job/senior-ai-engineer-oligo-space-hawthorne-f42186p5qzm7'
type: 'job'
last_seen: '2026-09-10'
---

# Senior AI Engineer at Oligo Space

- **Company:** Oligo Space
- **Location:** Hawthorne
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-07-09
- **Last confirmed live:** 2026-09-10
- **Apply:** https://jobs.ashbyhq.com/oligo/633c2b59-9b24-44c7-b7f4-7bbb0ab1bd5d

## Job description

Oligo is building a manufacturing-in-the-loop foundation model to automate spacecraft design and production worldwide. Our approach allows customers to focus entirely on their own technology and mission objectives, while we handle everything, from design and manufacturing to launch and operations. Leveraging cutting edge AI-driven generative design and automated manufacturing, our ex-MIT, Harvard, and NASA JPL team work to create the most advanced payload-specific spacecraft at scale in weeks over months.

With world‑class advisors on our board, and fresh funding from top investors like Lux Capital, we’re always on the lookout for exceptional builders, fast learners, and ambitious engineers. Whether your passion lies in spacecraft systems, avionics, ML/AI, or advanced manufacturing, you’ll be collaborating across disciplines on real missions that fly, perform in orbit, and scale internationally.

We pair world-class AI/ML talent with top-tier satellite engineers under one roof to reimagine how space systems are built, starting from first principles. No bureaucracy. No legacy thinking.

If you think you’re a fit, we are extremely excited to meet you.

## Role Overview

Oligo builds vertically integrated infrastructure for automated spacecraft design and manufacturing. Our AI software stack, Zenith, turns raw mission requirements into flight-ready spacecraft using a pipeline of agentic AI systems, embedded simulation, and hardware-in-the-loop validation. We’re hiring a Senior Software/AI Engineer with a background in both ML/AI as well as classical automation to lead the advancement of core algorithms used for generative design, simulation-aware geometry creation, process acceleration, and algorithmic tooling for spacecraft engineers. You’ll work alongside spacecraft engineers and flight software developers to build automations that don’t just simulate reality—but design it. This is a hands-on, high-leverage role for mid to late-career engineers interested in applying cutting-edge algorithms to real-world hardware. You’ll learn spacecraft engineering, astrodynamics, and manufacturability by building models that directly influence how our satellites fly.

## What You’ll Lead

- Develop and maintain foundation models with strong spatial reasoning capability that act as the basis for various spacecraft design automations.
- Design complex self-supervised and low-data/low-fidelity model training schemes using the limited real-world spacecraft data.
- Develop and deploy automation tooling to accelerate spacecraft design processes using classical and learning-based methods.
- Develop and deploy agentic VLM frameworks that parse technical documents, datasheets, and system specs into structured engineering constraints.
- Build and train models using reinforcement learning to explore high-dimensional multivariable design spaces—balancing structural, thermal, orbital, and manufacturability objectives.
- Interface with physical simulation tools (Ansys, GMAT, Thermal Desktop) and CAD environments (OpenCascade, CadQuery, SolidWorks plugins) to ground designs in physical constraints.
- Collaborate daily with engineers building the real hardware—what you code will be tested in thermal chambers, vibration tables, and flown on orbit.

## What You’ll Bring

## Minimum Qualifications

- Master’s degree or higher in Computer Science, ML/AI, or a related technical field.
- Significant experience in ML/AI through academic or industry research, personal projects, or internships beyond coursework.
- Significant experience in classical algorithm development through academic or industry research, personal projects, or internships beyond coursework.
- 4+ years of experience building advanced ML/AI systems (LLM agent frameworks, complex RL algorithms, transformer architectures (text, vision, diffusion, etc.), data and compute efficient architectures).
- Strong proficiency in Python (specifically PyTorch and other standard Python libraries), C++, and C#. Proficiency or willingness to learn modern tooling.
- Ability to think clearly about tradeoffs between simulation fidelity, inference speed, and manufacturability.

## Preferred Skills and Experience

- Experience working with physics-informed deep learning models and PDE-grounded neural networks.
- Experience working with and adapting enterprise software (e.g. Ansys, SolidWorks, Fusion360, etc.) outside of API usage (e.g. OS calls, plugins, editing binaries, etc.).
- Hands-on ability to prototype, build, and debug hardware systems—bonus if you’ve worked with microcontrollers, sensors, or test rigs.
- Prior experience working in the aerospace industry. Familiarity with spacecraft concepts, astrodynamics, or control systems.
- Familiarity through coursework or beyond with data/differential privacy methods for deep learning.

Pay Range

- Salary range: $140,000 - $164,000 per year.
- This role is on-site in Hawthorne, CA.

## Benefits

- Equity
- Unlimited PTO
- Medical (Platinum coverage), Vision, & Dental Insurance
- Catering provided on-site everyday.

Additional Information You may be eligible for our suite of benefits including medical, vision & dental coverage.

## About Oligo Space

## Company Overview
- **One-liner**: Oligo Space is building a manufacturing-in-the-loop foundation model to automate spacecraft design and production, delivering payload‑centered, flight‑ready platforms in under eight months.
- **Entity Type**: Private (Seed stage)
- **Headquarters**: Hawthorne, California, United States (also offices in Boston, MA and Cambridge, MA, with an additional location in Israel)
- **Founded**: 2022 (some sources list 2024; the company’s first grant was in February 2024)
- **Founders**: Jacob Rodriguez (Founder & CEO)

## Core Business
- **Primary industries**: Space Research and Technology, Aerospace, Artificial Intelligence
- **Target customers**: Payload developers, mission operators, government agencies, and commercial space companies (B2B / Enterprise)
- **Mission**: “Build the infrastructure that will power humanity’s expansion through the Solar System” by redefining spacecraft design as a space environmental engineering problem and automating the entire design‑to‑manufacturing pipeline.

## Products & Services
- **Zenith (Generative Design Engine)**: An AI‑powered software platform that takes mission and payload requirements as input and outputs an optimized spacecraft design, including geometry, constraints, and physics‑based optimization. Type: SaaS / API.
- **Epoch (Mission Operations Platform)**: AI/ML models for anomaly detection, generative design, and mission operations across the spacecraft lifecycle. Type: SaaS / API.
- **Payload Hosting Services**: Shared and dedicated ESPA‑class spacecraft platforms delivered in less than 8 months, with availability for June 2026 and June 2027 launches. Type: Service / Hardware.
- **Manufacturing‑in‑the‑Loop Foundation Model**: Proprietary AI that captures aerospace expertise and automates production instructions, enabling quotes within one business day. Type: Technology / Platform.

## Market Standing
- **Valuation**: Not publicly available (total funding is $100K)
- **Key Metric (Funding)**: Total funding of $100,000 across two rounds – a $100K grant (Feb 2024) from Massachusetts Technology Collaborative, and a Seed round (Jun 2025) led by Kakao Ventures (3 investors).
- **Notable Investors/Partners**: Kakao Ventures (lead investor), Massachusetts Technology Collaborative (grant provider); partnerships include Melagen Labs for in‑space demonstration (Spacedock mission, Q2 2026).
- **Growth Signals**: 325% year‑over‑year employee growth (from 5 to 18 people); 1,017 LinkedIn followers (+155% YoY); multiple open roles across engineering, software, and leadership; first in‑space demonstration planned for Q2 2026.

## Competitive Advantages
- **AI‑First, Manufacturing‑in‑the‑Loop**: Unlike traditional aerospace companies, Oligo uses a foundation model that learns from manufacturing feedback, enabling rapid iteration and automated design.
- **Payload‑Centric Approach**: The entire spacecraft is optimized for the payload, shifting complexity from the satellite bus to the mission itself.
- **Speed**: Quotation in 1 business day and full design in minutes; integrated, launched, and mission‑ready in under 8 months.
- **Modular First‑Principles System**: Captures decades of aerospace expertise in a modular, physics‑based system that can be applied across the solar system.

## Strategic Focus
- **Scaling the Foundation Model**: Expanding the AI model to handle more mission types and environments.
- **First In‑Space Demonstration**: The Spacedock mission with Melagen Labs in Q2 2026 is a critical milestone to validate the approach.
- **Talent Acquisition**: Actively hiring across all disciplines (ML/AI, avionics, mechanical, flight software, ATLO, business engineering) to support rapid growth.
- **Global Expansion**: Offices in the US (Hawthorne, Boston, Cambridge) and Israel, with plans to serve customers worldwide.

## Why Work Here
- **Culture**: “Exceptional builders, fast learners, and ambitious engineers” – the team comes from top institutions (MIT, NASA JPL, The Aerospace Corporation, Rocket Lab) and values hands‑on prototyping and rapid iteration.
- **Work Policy**: Hybrid workspace – employees engage in a combination of remote and on‑site work; typical on‑site presence in Hawthorne, CA or Israel offices.
- **Perks & Environment**: Cutting‑edge problems at the intersection of AI and space hardware; opportunity to work on real missions from design through launch; flat structure with high ownership.
- **Engineering Culture**: Emphasis on deep learning, simulation, and real‑world space systems; space experience is a plus but not required – the company values strong generalist engineering skills.

## Sources
1. [Oligo Space Website](https://www.oligospace.com)
2. [Oligo Careers Page (Ashby)](https://jobs.ashbyhq.com/oligo)
3. [Built In – Oligo Company Profile](https://builtin.com/company/oligo)
4. [LinkedIn – Oligo Space](https://www.linkedin.com/company/oligo-space)
5. [Oligo Space Contact Page](https://www.oligospace.com/contact)

## Other roles at Oligo Space

- [Chief Spacecraft Engineer](https://feeny.ai/job/chief-spacecraft-engineer-oligo-space-hawthorne-9dcyz42nz5xa) — Hawthorne
- [Technical Strategy & Business Engineer](https://feeny.ai/job/technical-strategy-business-engineer-oligo-space-hawthorne-pw4kkh0z92qj) — Hawthorne
- [Spacecraft Engineer Intern (Mechanical)](https://feeny.ai/job/spacecraft-engineer-intern-mechanical-oligo-space-hawthorne-veaj2zcp1knw) — Hawthorne
- [Spacecraft Engineer Intern (Flight Software)](https://feeny.ai/job/spacecraft-engineer-intern-flight-software-oligo-space-hawthorne-z0k2s0348s5s) — Hawthorne
- [Manufacturing Engineer - Mechanical](https://feeny.ai/job/manufacturing-engineer-mechanical-oligo-space-hawthorne-vf8hq00326kt) — Hawthorne
- [Generative Spacecraft Engineer - Electrical](https://feeny.ai/job/generative-spacecraft-engineer-electrical-oligo-space-hawthorne-z5npm59g5y6r) — Hawthorne
- [ML/AI/CS Intern](https://feeny.ai/job/ml-ai-cs-intern-oligo-space-hawthorne-74403sy2nnm6) — Hawthorne
- [Generative Spacecraft Engineer - Mechanical](https://feeny.ai/job/generative-spacecraft-engineer-mechanical-oligo-space-hawthorne-xbbfz3rwhbkd) — Hawthorne
- [Generative Spacecraft Engineer - Systems](https://feeny.ai/job/generative-spacecraft-engineer-systems-oligo-space-hawthorne-m2p118a9j799) — Hawthorne
- [Spacecraft Engineer Intern - all fields](https://feeny.ai/job/spacecraft-engineer-intern-all-fields-oligo-space-hawthorne-3dvnx7xt3rqv) — Hawthorne