Principal Machine Learning Engineer (MLE)

About the Role

The AI Sidekick team is a key part of Equinix's innovation strategy, and as a Principal Machine Learning Engineer, you will play a critical role in driving the development of AI-powered solutions. You will collaborate with cross-functional teams, including product management, engineering, and design, to identify opportunities for machine learning and AI applications.

Equinix is committed to creating a culture of innovation and continuous learning, and as a Principal Machine Learning Engineer, you will have the opportunity to work with a talented team of professionals who are passionate about machine learning and AI.

What You Will Do

• 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

What We Are Looking For

• 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
• Ability to work in a fast-paced environment and adapt to changing priorities
• Strong problem-solving skills and attention to detail

Nice to Have

• Experience with containerization using Docker and Kubernetes
• Knowledge of Agile development methodologies and version control systems such as Git
• Experience with data visualization tools such as Tableau or Power BI
• Familiarity with cloud-based data warehouses such as Snowflake or Redshift

Benefits and Perks

• Competitive salary and bonus structure
• Comprehensive health insurance package, including medical, dental, and vision coverage
• 401(k) retirement plan with company match
• Flexible work arrangements, including remote work options and flexible hours
• Professional development opportunities, including training and conference attendance
• Access to the latest technologies and tools, including cloud platforms and machine learning frameworks
• Collaborative and dynamic work environment with a team of experienced professionals
• Recognition and reward programs for outstanding performance and contributions
• Paid time off and holidays, including a generous vacation package

• Tip: Make sure to highlight your experience with machine learning frameworks such as PyTorch and TensorFlow, as well as your proficiency in Python.
• Tip: Practice explaining technical concepts and results to non-technical stakeholders, as strong communication skills are essential for this role.
• Tip: Be prepared to discuss your experience with cloud platforms, including GCP, Azure, and AWS, and how you have optimized ML workflows for performance and scalability.
• Tip: Showcase your problem-solving skills and attention to detail, as these are critical for success in this role.
• Tip: Research Equinix's innovation strategy and be prepared to discuss how you can contribute to the development of AI-powered solutions.
• Tip: Be prepared to discuss your experience with data visualization tools and your ability to communicate complex technical concepts to non-technical stakeholders.
• Tip: Highlight your experience working in a fast-paced environment and adapting to changing priorities, as this is essential for success in this role.