Overview Who are we? Equinix is the world’s digital infrastructure company®, shortening the path to connectivity to enable the innovations that enrich our work, life and planet. A place where tech thinkers and future builders turn bold ideas into breakthrough experiences, we welcome your unique perspective. Help us challenge assumptions, uncover bias, and remove barriers—because progress starts with fresh ideas. You’ll find belonging, purpose, and a team that welcomes you—because when you feel valued, you’re empowered to do your best work. Job Summary As a Machine Learning Engineer, you will design, build, deploy, and scale machine learning and generative AI systems that power real-world products. You will work closely in the AI Sidekick team and with business teams to translate advanced ML and LLM capabilities into reliable, production‑grade solutions across multi‑cloud environments including GCP, AWS, and Azure. This role blends applied machine learning, software engineering, and MLOps, with a strong focus on building robust, scalable systems rather than purely academic research. Responsibilities Design, develop, and deploy machine learning and Large Language Model (LLM)–based solutions for production use cases Collaborate with Generative AI Center of Excellence leaders and business stakeholders to evaluate buy vs. build decisions for generative AI applications Develop end-to-end ML pipelines, covering data ingestion, feature engineering, model training, evaluation, deployment, and monitoring Architect and implement LLM-powered systems that integrate agents and services across multiple cloud platforms into a unified solution Optimize ML workflows for performance, scalability, reliability, and cost efficiency in cloud environments (GCP, Azure, AWS) Implement and maintain MLOps best practices, including CI/CD, model versioning, experiment tracking, and automated retraining Work extensively with deep learning frameworks such as PyTorch and TensorFlow Containerize ML services and deploy them using Docker, Kubernetes, App Engine, or virtual machines Apply strong knowledge of NLP fundamentals, including transformers, attention mechanisms, embeddings, and text preprocessing Deploy and manage models in production, conduct A/B testing, and measure performance improvements using statistical methods Develop features, run experiments, analyze results, and translate insights into actionable improvements Build and deploy classical ML models (regression, classification, clustering), NLP applications (sentiment analysis, summarization, Q&A, chatbots, information retrieval), and computer vision solutions (image classification, object detection, segmentation using models such as YOLOv7, DDRNet, RFTM with datasets like COCO and Cityscapes) Qualifications PhD with 5+ years, Master’s with 6+ years, or Bachelor’s with 7+ years of experience in Machine Learning, Computer Science, Data Science, or a related field Strong proficiency in Python for machine learning and production systems Solid understanding of software engineering fundamentals, system design, and design patterns Hands-on experience with at least one major cloud platform (GCP, Azure, or AWS) Experience building and deploying production-grade ML systems Strong communication skills with the ability to explain technical concepts and results to both technical and non-technical stakeholders Excellent time management, collaboration, and organizational skills Compensation and Benefits This posting is for a backfill position, meaning it is to fill an existing vacancy within our organization. The targeted pay range for this position in the Canada - Toronto location is CAD 154,000 – 232,000 per year. Our pay ranges reflect the minimum and maximum target for new hire pay for the full-time position determined by role, level, and location. The pay range shown is based on our compensation structure in place at the time of posting and may be updated periodically based on business needs. Individual pay is based on additional factors including job-related skills, experience and/or education. The targeted pay range listed reflects the base pay only and does not include bonus, equity, or benefits. Employees are eligible for bonus, and equity may be offered depending on the position. Equinix Benefits As an employee, you become important to Equinix’s success. We offer competitive benefits aligned with our core values: competitive, inclusive, sustainable, connected and efficient. Benefits are designed to be competitive within the current marketplace and may vary by location. Some benefits require eligibility and may change at Equinix discretion. Employee Assistance Program : An Employee Assistance program is available to all employees. EEO Statement : Equinix is committed to an open employment process for all individuals, including those with a disability. Equinix is an Equal Employment Opportunity and, in the U.S., an Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to unlawful considerations of race, color, religion, creed, national or ethnic origin, ancestry, place of birth, citizenship, sex, pregnancy or related medical conditions, sexual orientation, gender identity or expression, marital or domestic partnership status, age, veteran or military status, physical or mental disability, medical condition, genetic information, political or organizational affiliation, status as a victim or family member of a victim of crime or abuse, or any other status protected by applicable law. AI in Hiring : We use artificial intelligence in our hiring process. Learn more about this practice here. #J-18808-Ljbffr