Machine Learning Engineer

Join to apply for the

Machine Learning Engineer

role at

ALS

Get AI-powered advice on this job and more exclusive features.

At ALS, we encourage you to dream big.

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.

What You’ll Do

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

What You Bring

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

Understanding of MLOps principles and experience managing model lifecycles using MLflow

Strong understanding of supervised and unsupervised learning, including deep learning

Experience working with GPU-accelerated environments using CUDA

Familiarity with Jupyter Notebooks, Conda, and reproducible development workflows

Excellent collaboration skills and ability to work across ML, backend, and product teams

Nice to Have

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

Experience with dataset labeling and management tools such as Label Studio, Labelly, or Superpixel

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

Experience with Kubernetes or other container orchestration platforms

Familiarity with Hugging Face models and frameworks for computer vision

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

Why Join Us

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. We value curiosity, experimentation, and engineering excellence — giving you room to innovate while contributing to a platform that’s transforming the mining and exploration industry.

Our Benefits Includes

An estimated annual salary of $110,000 to $130,000 at the time of posting. Individual compensation is determined by factors such as job-related skills, relevant experience, education and / or training.

Structured wage increases.

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).

Please note : Benefits vary based on employee status.

Working at ALS

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

Our values are important to us, and shape how we work, how we treat each other and how we recognise excellence.

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.

Everyone Matters

ALS is proud to be an equal opportunity employer and is committed to fostering an inclusive work environment where the strengths and perspectives of each employee are both recognised and valued.

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.

ALS also welcomes applications from people with all levels of ability. Accommodation is available on request for candidates taking part in all aspects of the selection process.

Eligibility

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.

How To Apply

Please apply online and provide a resume & cover letter that best demonstrate your motivation and ability to meet the requirements of this role.

Seniority level

Mid‑Senior level

Employment type

Full-time

Job function

Engineering and Information Technology

Industries

International Trade and Development

Referrals increase your chances of interviewing at ALS by 2x

#J-18808-Ljbffr