Senior Deep Learning Engineer

Job Title:
Senior Deep Learning EngineerLocation:
Remote (Toronto, Canada)Type:
Full-timeAbout KORE
KORE is an AI startup revolutionizing the exploration mining industry. We build advanced AI systems that help transform complex visual, geospatial, and technical data into actionable insights for real-world mining exploration workflows.We are looking for a highly motivated
Senior Deep Learning Engineer
to join our team and work on cutting-edge applied AI problems across computer vision, multimodal learning, and deep learning.This role is ideal for someone with strong machine learning fundamentals who wants to work on real-world applications where research, modeling, experimentation, and practical deployment all matter.This is a
remote position, with our head office located in
Toronto, Canada .About the Role
As a Senior Deep Learning Engineer at KORE, you will focus primarily on developing, improving, and validating deep-learning models for real-world industrial applications. We are looking for someone who understands neural networks beyond treating them as a black box. The ideal candidate has strong fundamentals in machine learning, deep learning, optimization, model evaluation, and data-driven experimentation. You should be comfortable reasoning about why models work, why they fail, and how to improve them. You will work closely with engineering, product, and domain experts to turn complex real-world data into practical AI systems that can support exploration mining workflows.Responsibilities
Design, train, fine-tune, and evaluate deep learning models for real-world applications.Develop modeling approaches across areas such as computer vision, multimodal learning, self-supervised learning, representation learning, and related deep learning domains.Build and improve model architectures, training strategies, loss functions, data pipelines, and evaluation methods.Analyze model behavior, failure modes, data quality issues, and performance trade-offs.Deploy models into a cloud environment, optimize for latency and accuracy.Take ownership of deep learning projects from problem definition through experimentation, validation, and production readiness.Required Qualifications
Bachelor’s or Master’s degree in Computer Science, Machine Learning, Mathematics, Statistics, Engineering, or a related technical field.5+ years of professional experience building deep learning systems or machine learning models for real-world applications.Experience in Python, learning frameworks such as PyTorch, TensorFlow, JAXStrong fundamentals in machine learning, neural networks, optimization, probability, statistics, and model evaluation.Hands-on experience training, fine-tuning, debugging, and improving deep learning models.Strong experience in at least one major deep learning domain, such as computer vision, NLP, multimodal learning, self-supervised learning, representation learning, or related areas.Strong problem-solving skills, scientific thinking, and ability to work independently in a fast-moving startup environment.Nice to Have
Experience with cloud platforms such as Azure, AWS, or Google Cloud Platform.Experience training, fine-tuning, or deploying Vision-Language Models.Experience with MLOps or LLMOps practices and tools.Experience with model serving and inference engines such as vLLM, SGLang, NVIDIA Triton Inference Server, or similar.Familiarity with model serving, monitoring, versioning, and experiment tracking tools.Experience with distributed training, large-scale datasets, or inference optimization.Interest in applying AI to mining, geology, geospatial data, natural resources, or other industrial domains.Why Join KORE
Work on challenging applied AI problems with real-world industry impact.Focus deeply on modeling, experimentation, and applied research rather than only infrastructure.Join a startup applying deep learning to an important and technically complex domain.Collaborate with experienced AI, engineering, and industry experts.Contribute directly to products that can transform exploration mining workflows.Work remotely while staying connected to a Toronto-based team.Take ownership of meaningful technical challenges in a fast-moving startup environment.We thank all applicants for their interest;
however, only those selected for an interview will be contacted.
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