Autonomous Machine Learning Engineer (Robotics)

Stax - Deep Tech Talent; Valencia; Presencial; EUR 85.000 - 125.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Equity participation plan

Relocation aid

Sales bonuses

Descripción de la vacante

Stax - Deep Tech Talent partners with a robotics startup building Thor, a fully electric autonomous heavy vehicle for precision agriculture and frontline logistics. The role centers on owning the autonomy stack end-to-end, from data ingestion to production deployment in field conditions across Spain.

The candidate will be hands-on, bridging data engineering, ML and cloud, with a strong software engineering background and strong English communication to collaborate with technicians, operators,

Formación

• Proven track record of deploying models in real-world settings.
• Hands-on coding and solid software engineering fundamentals.
• Ability to bridge data engineering, ML, and cloud.
• Field-ready and willing to test on real machines.
• Fluent in English and able to collaborate across teams.

Responsabilidades

• Pipeline Architecture: Build and maintain data ingestion pipelines.
• Model Evolution: Select, train, and iterate on models for autonomy.
• Field Testing: Design and run testing campaigns in virtual environments and on real fields.
• Safety & Verification: Define and implement safety criteria for autonomous operation.
• Deployment & Ops: Own shipping and monitoring of new models with end-users.

Conocimientos

Hands-on Coding

Field Testing

ML Deployment

Software Engineering

English Proficiency

Descripción del empleo

Senior Autonomy & ML Engineer: Shape the Future of Heavy Robotics (€9M Funded)

Funding: Series Seed | €9M raised since 2024

Sector: Autonomous Vehicles / Precision Agriculture / Deep-Tech

The Mission

I am partnering with a high-growth robotics startup building "Thor"—a fully electric, autonomous heavy-duty vehicle designed to revolutionise precision agriculture and frontline logistics. Following a recent €7M injection, they are scaling production to 100+ units.

We are looking for an engineer who wants to own the autonomy stack end-to-end—moving beyond notebooks and slide decks to deploy models that do real work in the field.

The Role: End-to-End Autonomy Ownership

You won’t just be a cog in a machine; you will own the stack from raw data ingestion to production deployment.

Your Core Tasks:

• Pipeline Architecture: Build and maintain data ingestion pipelines (cleaning, organising, and labelling).
• Model Evolution: Select, train, and iterate on machine learning models for high-stakes autonomy.
• Field Testing: Design and run testing campaigns in virtual environments and—more importantly—out in the vineyards, olive orchards, and citrus groves of Spain.
• Safety & Verification: Define and implement the critical safety criteria that allow 3-ton machines to operate autonomously.
• Deployment & Ops: Own the shipping and monitoring of new models, ensuring seamless communication with end-users.

Who You Are:

• Practical Visionary: You have a track record of deploying models that actually worked in the real world. You understand the state-of-the-art but know what is "field-ready."
• Hands‑on Coder: Strong software engineering fundamentals are a must.
• Generalist Mindset: While we value deep expertise, we prefer engineers with high ownership who can bridge the gap between data engineering, ML, and cloud.
• Field‑Ready: You are excited to get out of the office and test on real machines with real-world constraints.
• Collaborative: Fluent in English; you can work effectively with technicians, operators, and founders alike.

Why Join This Team?

• Unrivaled Growth: Be a foundational hire in a company that has secured €9M in just two years.
• Total Autonomy: A self-directed environment where you define how we solve the labour crisis in farming.
• Top‑Tier Rewards: Highly competitive base salary + Equity Participation Plan + Sales Bonuses.
• Custom Perks: From relocation aid to specific lifestyle benefits—the team wants to offer what you actually value.
• Location: Based in Valencia—voted one of the best cities globally for quality of life, climate, and culture.