Machine Learning Engineer

Job Description

The role requires a creative, out-of-the-box thinker, capable of independent work while also engaged with a multidisciplinary team to provide the best outcomes. You will be responsible for end-to-end geophysical modelling development and will be engaged daily in tasks like:

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

Requirements

It’s not about specifically where you have come from nor what qualifications you have. What truly matters is that you are an impossibly fast learner and are passionate about building exceptional computational software. People with competitive applications could have skills and experience such as:

• Exceptional machine learning/computational software development skills in Python (required).
• A strong, demonstrated background in DevOps and MLOps, including version control (Git), CI/CD, API design, Unit testing, data and experiment tracking, and object-oriented programming (required).
• A strong quantitative intuition and the proven ability to translate complex mathematical concepts from domains like machine learning, signal processing, and statistical simulation into high-quality, efficient code (required).
• Demonstrated experience with Python Libraries: Scipy, Numpy, JAX, Pytorch, Tensorflow, Matploylib, 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 in applying machine learning techniques to solve real-world scientific or engineering problems.
• A demonstrated ability to effectively communicate complex ideas and problem solve within fast-paced team environments.
• A history of thriving in diverse environments that value honesty, open communications, 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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