Software Engineer - Machine Learning

Empower Global Construction Innovation as our Next Machine Learning Engineer!

Are you ready to independently design and implement impactful machine learning solutions, driving product innovation and mentoring emerging talent within our AECO segment? This role is for an experienced professional ready to take ownership of machine learning projects from conceptualization to production, applying advanced statistical modeling to solve complex problems and significantly improve system performance for our global customers.

Trimble is a global technology company that connects the physical and digital worlds, transforming the ways work gets done. With relentless innovation in precise positioning, modeling and data analytics, Trimble enables essential industries including construction, geospatial and transportation. Whether it's helping customers build and maintain infrastructure, design and construct buildings, optimize global supply chains or map the world, Trimble is at the forefront, driving productivity and progress.

The Trimble AECO segment provides digital construction solutions that increase precision and productivity for Architecture, Engineering, Construction, and Operations.

In this role, you'll be the primary architect of ML solutions that directly impact the construction lifecycle, moving beyond theory to deploy robust models that solve real‑world industry challenges at scale.

• Spearhead the full ML lifecycle by identifying, training, and refining deep learning models to solve complex, real‑world problems at scale.
• Architect robust datasets to ensure high‑quality data coverage for diverse industry use cases, directly moving the needle on model performance.
• Champion MLOps excellence through containerization, versioning, and proactive monitoring to ensure system reliability in production.
• Collaborate with domain experts to translate ambiguous business needs into actionable technical tasks and innovative product features.
• Elevate team expertise by acting as a technical resource, providing guidance to colleagues and sharing best practices in machine learning.

• 3+ years of professional experience with a proven track record of shipping production‑ready machine learning models.
• Fluency in .NET/C# coding and a solid understanding of software architecture and data modeling.
• Deep practical knowledge of machine learning principles, including model selection, Bayesian analysis, and evaluation methodologies.
• Experience with Data Bricks for managing large‑scale data and model workflows.
• Strong quantitative background with a degree in Computer Science, Engineering, Math, or a related field.

• Experience in the AECO (Architecture, Engineering, Construction, and Operations) or Fintech industries.
• A strong Git Hub portfolio or active contributions to open‑source ML projects.

• Location: Lake Oswego, OR;
  In-Office
• Travel Requirement: 0%

At Trimble, we're not just a company that "does good"—we are a team dedicated to making a tangible, positive Real-World Impact
. We build innovative solutions designed to solve the world's most critical challenges. From construction sites to transportation hubs, our work tangibly improves how people live, build, move, and grow.

You'll work on projects that truly matter:
Our purpose‑driven culture means you'll be helping to build and deliver solutions that make work faster, safer, and more sustainable for millions of people worldwide. Our impact is tangible, from connected machines that save fuel to data‑driven insights that reduce waste.

Collaborate with like‑minded people:
Our strong internal culture is a "hidden gem." You will work with a collaborative, supportive team that shares your purpose and fosters a genuine sense of belonging. We're a company of "visionary pragmatists" who think boldly and build things that work.

Be an owner:
Trimble thrives on individuals who take initiative and embrace ownership. You'll find an entrepreneurial spirit where success is often "self‑authored," empowering proactive "doers."

Trimble provides the…