machine learning engineer

Equinix operates as a global digital infrastructure company that facilitates connectivity to support innovations across various sectors.

• Lead the end-to-end design and architecture of scalable, production-ready AI/ML systems;
• Architect, build, and deploy a diverse portfolio of AI solutions ranging from classical ML models to generative AI and Agentic applications;
• Write clean, optimized, and maintainable production code;
• Design and optimize ML workflows and pipelines in cloud environments;
• Implement rigorous MLOps practices, including CI/CD, continuous training, model tracking, and automated deployment;
• Evaluate and integrate the newest frameworks and methodologies in the LLM/Agentic space;
• Influence senior leadership on technical roadmap and "build vs. buy" decisions;
• Partner with product teams, data engineers, and business stakeholders to translate business challenges into ML capabilities;
• Mentor junior to mid-level ML engineers and define coding standards.

• Master’s or PhD in Computer Science, Machine Learning, Data Science, Mathematics, or a related technical field;
• Extensive industry experience (8+ years) in designing, building, and running complex AI/ML projects in production;
• Expert-level proficiency in Python;
• Strong grasp of software engineering principles, system design, data structures, and cross-system integration;
• Deep hands-on knowledge of traditional machine learning algorithms, deep learning/GenAI ecosystems, and Agentic workflows;
• Extensive experience deploying scalable services on AWS, GCP, or Azure using Docker, Kubernetes, or serverless architectures;
• Excellent ability to communicate technical concepts to executive leadership and non-technical stakeholders.

• Employee Assistance Program;
• Pension scheme (PPK);
• Private Medical Insurance;
• Life and Accident Insurance;
• Annual leaves;
• Flex Wallet (flexible spending account);
• Multi-sport Card;
• Lunch Pass Card;
• Discount Portal;
• Statutory allowances and reimbursements (remote working, corrective glasses);
• Paid and unpaid leaves.