Machine Learning Engineer Permanent

When you join us, you’ll be part of a global team harnessing the power of scientific testing and data-driven insights to build a healthier future.

ALS GeoAnalytics combines geoscience expertise with advanced machine learning to accelerate mineral exploration and unlock resource value. Our GeoAnalytics platform integrates deep learning, data processing, and predictive modeling to generate high-quality geological insights for clients worldwide.

We’re looking for a Machine Learning Engineer to help design, build, and maintain our machine learning infrastructure — from model training and experimentation to deployment and inference. You’ll work on a mix of batch and real-time ML services, including deep learning models for computer vision and geospatial analysis.

Develop, deploy, and maintain machine learning microservices and pipelines for model training, serving, and inference

Build and operate ML workflows using AWS Lambda, EC2, ECS, and Fargate for scalable compute orchestration

Design and maintain serving infrastructure for real-time and batch inference workloads

Build and maintain ML experimentation workflows using MLflow, Jupyter Notebooks, and Conda

Train and optimize deep learning models using PyTorch or TensorFlow for supervised, unsupervised, and computer vision tasks

Optimize training and inference performance using CUDA and NVIDIA GPU environments

Collaborate with data scientists and geologists to integrate trained models into production APIs

4+ years of experience in machine learning or applied data engineering roles

• Strong proficiency in Python, with experience using ML and scientific libraries such as PyTorch, TensorFlow, scikit-learn, and scikit-image
• Experience running ML workloads on AWS, including Lambda, EC2, ECS, Fargate, or SageMaker
• Excellent collaboration skills and ability to work across ML, backend, and product teams

Experience with computer vision methods relevant to geoanalytics, including image recognition, segmentation, and feature detection

Experience using SageMaker, Kubeflow, or Airflow for experiment tracking, training workflows, or model lifecycle management

Familiarity with Hugging Face models and frameworks for computer vision

Background in geospatial or geological data modeling and spatial tooling (PostGIS, GDAL/OGR, geopandas)

At ALS GeoAnalytics, you’ll join a cross-disciplinary team at the intersection of geology and AI. You’ll have the opportunity to design and deploy ML systems that directly impact real-world exploration outcomes. Individual compensation is determined by factors such as job-related skills, relevant experience, education and/or training.

Comprehensive benefit package specific to your work status (including extended medical, dental, and vision coverage, access to company perks, life and disability insurance, retirement plan with company match, employee assistance and wellness programs).

Additional vacation days for years of service.

Business support for education or training after 9 months with the company.

Learning & development opportunities (unlimited access to e-learnings and more).

The ALS team is a diverse and dedicated community united by our passion to make a difference in the world.

At ALS, you’ll be supported to develop new skills and reach your full potential. We invest in our people with programs and opportunities that help you build a diverse career with us.

We want everyone to have a safe, flexible and rewarding career that makes a positive impact on our people, the planet and our communities.

Qualified candidates will be considered without regard to race, colour, religion, national origin, military or veteran status, gender, age, disabilities, sexual orientation, gender identity, pregnancy and pregnancy-related conditions, genetic information and any other characteristics protected by the law. We invite resumes from all interested parties, including women, First Nations, Metis and Inuit persons, members of minority groups, and persons living with disabilities.

Accommodation is available on request for candidates taking part in all aspects of the selection process.

To be eligible to work at ALS you must be a Citizen or Permanent Resident of the country you are applying for, or either hold or be able to obtain, a valid working visa.