Machine Learning EngineerAlsglobal • Vancouver, Metro Vancouver Regional District, CA
Machine Learning Engineer
Alsglobal • Vancouver, Metro Vancouver Regional District, CA
29 days ago
Job type
- Permanent
Job description. 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 on-line and provide a resume & cover letter that best demonstrate your motivation and ability to meet the requirements of this role.### Introduce YourselfWe’re all about people – so show us who you are and why you're passionate about working with us by submitting your resume, and we’ll keep it on file for future opportunities.
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Machine Learning Engineer • Vancouver, Metro Vancouver Regional District, CA
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