Machine Learning Engineer

Job Description

Role

As a skilled computational machine learning engineer you will translate cutting‑edge research and complex algorithms into robust, scalable, and production‑ready analytics software. You will work hand‑in‑hand with the ML & Analytics Team and the Geophysics Team to develop end‑to‑end geophysical modelling solutions.Responsibilities

• Collaborate with the ML & Analytics Team and geophysical subject‑matter experts to build, test, and maintain Nomad computational software and quantum gravity sensor data processing pipelines.
• Take novel computational techniques and algorithm prototypes designed by our research team and engineer them into reliable, performant software modules.
• Build robust data ETL pipelines and software scaffolding.
• Develop comprehensive unit and integration tests to ensure scientific accuracy and reliability of the codebase.
• Contribute to DevOps and MLOps practices, including containerisation (Docker), CI/CD pipelines, and future deployments on cloud platforms (AWS).
• Work with technology and deployment experts to build the software tools needed for highly efficient surveying techniques.

Requirements

• Exceptional machine learning/computational software development skills in Python (required).
• Strong background in DevOps and MLOps, including version control (Git), CI/CD, API design, unit testing, data and experiment tracking, and object‑oriented programming (required).
• Strong quantitative intuition and proven ability to translate complex mathematical concepts from domains such as machine learning, signal processing, and statistical simulation into high‑quality, efficient code (required).
• Demonstrated experience with Python libraries: SciPy, NumPy, JAX, PyTorch, TensorFlow, Matplotlib, Plotly, PyMC, multiprocessing.
• 3+ years of professional experience in a computational software development or data‑intensive role, OR a portfolio of personal projects that demonstrates an equivalent level of skill and a passion for building complex scientific software.
• A degree in a quantitative field such as Computer Science, Engineering, Physics, or Mathematics.
• Experience applying machine learning techniques to solve real‑world scientific or engineering problems.
• Excellent communication of complex ideas and problem solving within fast‑paced team environments.
• History of thriving in diverse environments that value honesty, open communication, and strong bonds between team members.

Are you interested in this position?

Apply by clicking on the “Apply Now” button below!

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