Applied Machine Learning Engineer

As an Applied Machine Learning Engineer, you will take end-to-end ownership of complex machine learning and data science problems across the physical AI space.

This is a high-impact role for someone with a strong technical foundation and a generalist mindset who can move from problem framing and experimentation through deployment and ongoing support.

You will work closely with engineering, product, and client-facing teams to turn machine learning methods into production-ready solutions that can be trusted in real customer environments.

The role blends research depth with practical delivery, and requires someone who can align stakeholders and communicate technical decisions clearly.

Who you are

• 3+ years of experience in data science, machine learning, or applied AI, with evidence of delivering high-impact production ML systems

• Background in engineering, physics, chemistry, or another STEM discipline connected to complex physical systems

• Experience with anomaly detection, optimization, reliability-focused modelling, or related approaches in industrial settings

• Experience working with sparse, noisy, or imperfect real-world data from engineering labs or other applied environments

• Experience deploying and supporting ML systems in production, including cloud-based environments

• Experience working with time-series, high-dimensional, or imperfect real-world datasets

• Comfortable working cross-functionally with engineering, product, and customer-facing teams, and able to explain technical decisions clearly to different audiences

• Experience building or experimenting with agents or autonomous systems

Wondering if you’re a good fit?

We believe in investing in our teammates, and value candidates who can bring their own diversified experiences to our teams, even if you aren't a 100% skill or experience match.

If some of what we've outlined about describes you, we’d love to hear from you.