Machine learning engineer • toronto on
We’re looking for an experienced Machine Learning Platform Engineer who will bring focus and subject-matter expertise around designing and implementing machine learning infrastructure and automatio... Show more
If you're looking to make a significant impact and shape the future of the AEC industry, this is the role for you.AI is the future of design and make, and Autodesk is pioneering the transformation ... Show more
Lead with purpose and keep growing.Vanguard’s Enterprise AI & Research (EAiR) team is building the next generation of AI capabilities that will power enterprise-scale products and experiences acros... Show more
Machine Learning Software Engineer.AI solutions in a production environment.The ideal candidate will work closely with data scientists, engineers, and business stakeholders to turn data-driven insi... Show more
Despite massive investments in planning, forecasting, and analytics, retailers still face the same operational issues—out-of-stocks, bad master data, margin leakage, and inconsistent execution acro... Show more
As a Senior Machine Learning Engineer on the AI Core team, you will be primarily responsible for designing, building, and applying machine learning models and agentic systems that power AI-driven a... Show more
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North America’s leading provider of integrated entertainment, sports content, and casino gaming experiences.From casinos and racetracks to online gaming, sports betting and entertainment content, w... Show more
We are currently seeking talented individuals for a variety of positions, ranging from junior to senior levels, and will evaluate your application in its entirety.Layer 6 is the AI center of excell... Show more
Assistant Manager, Superintendent or Assistant Superintendent.GENERAL DESCRIPTION / PURPOSE:.Machine Operator 1 (MO1), a field based position, is responsible for operating, maintaining, and repairi... Show more
As a Staff Machine Learning Engineer - VoIP Infrastructure you will:.Contribute to the design, development and implementation of VoIP infrastructure, telephony platforms, and observability features... Show more
Tiger Analytics is an advanced analytics consulting firm.We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data.Our consultants b... Show more
Annapurna Labs, considered as secret sauce behind the success of AWS, is responsible for silicon development.The Product: AWS Machine Learning accelerators are at the forefront of AWS innovation an... Show more
We’re looking for an enthusiastic software developer who’s excited by the opportunity of working on challenging problems at the intersection of machine learning and the financial services industry.... Show more
As a Machine Learning Engineer, you will help develop tailored user experiences using advanced LLMs, Knowledge Graphs, personalization, and predictive analysis.You will collaborate with other engin... Show more
About Fusemachines Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI.Leveraging proprietary AI Studio and AI Engines, the com... Show more
At eBay, we're more than a global ecommerce leader — we’re changing the way the world shops and sells.Our platform empowers millions of buyers and sellers in more than 190 markets around the world.... Show more
At Red Hat we believe the future of AI is open and we are on a mission to bring the power of open-source LLMs and vLLM to every enterprise.Inference team accelerates AI for the enterprise and bring... Show more
We are seeking a highly skilled Senior Machine Learning Engineer to lead the design, development, and implementation of advanced machine learning systems.In this role, you will be instrumental in a... Show more
Job Description
What's the opportunity?We’re looking for an experienced Machine Learning Platform Engineer who will bring focus and subject-matter expertise around designing and implementing machine learning infrastructure and automation tools (MLOps and DevOps). This is a unique opportunity to grow in the world of machine learning infrastructure and work with a team of passionate individuals committed to the mission of bringing ML to enterprise.At RBC Borealis, you’ll be joining a team that works directly with leading researchers in machine learning, has access to rich and massive datasets, and offers the computational resources to support ongoing development in areas such as reinforcement learning, unsupervised learning and computer vision. You can find out more about our research areas at rbcborealis.com.Your responsibilities include:Deploying and operating the GenAI platform across OpenShift/Kubernetes;
Managing large language model deployments (Cohere Command, Llama, Mistral) on GPU infrastructure (NVIDIA A100/H100), and configuring RAG pipelines with serving frameworks like vLLM, NVIDIA NIM, and TensorRT-LLM;
Monitoring GPU utilization, model performance metrics, and resource allocation across the platform;
Implementing observability stacks—Prometheus, Grafana, Pushgateway, and structured logging pipelines—to surface platform health, performance, and security signals;
Designing and implementing best practices and standards for data and machine learning pipelines across the organization;
Supporting platform users and cross-functional teams through infrastructure design guidance, thorough documentation, and collaboration across multiple RBC locations;
Building highly scalable, resilient on-premise systems for hosting machine learning systems using state-of-the-art technologies;
Strong experience designing and operating distributed/ML systems plus deep Kubernetes/OpenShift knowledge (Helm, operators, custom resources, RBAC, troubleshooting);
Proven history building DevOps/CI/CD pipelines (GitHub Actions), multi-stage Docker images, registry mirroring, and infrastructure automation in restricted enterprise environments;
In-depth knowledge of various stages of the machine learning application deployment process;
Proficiency with programming languages such as Python, Bash, or Rust;
Solid grasp of software engineering best practices—testing (unit/integration), coding standards, code reviews, source control—and implementing production monitoring, alerting;
Hands-on experience building and deploying hybrid environments on-premises enterprise environments;
Familiarity with the Large Language Model (LLM) inference and serving such as VLLM or similar;
Become part of a team that thinks progressively and works collaboratively. We care about seeing each other reach full potential;
A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock options where applicable;
Leaders who support your development through coaching and managing opportunities;
Ability to make a difference and lasting impact from a local-to-global scale.
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