Equinix
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Bengaluru · On-site · 7-10 Yrs · 4 days ago
Enterprise Software & Network Solutions · 10000+ Employees · Redwood City, US
Equinix is the world’s digital infrastructure company®. We shorten the path to boundless connectivity anywhere in the world. Its digital infrastructure, data center footprint and interconnected ecosystems empower innovations that enhance our work, life and planet. Equinix connects economies, countries, organizations and communities, delivering seamless digital experiences and cutting-edge AI quickly, efficiently and everywhere. --- Fraudulent employment offers Equinix would like to inform you about ongoing scams involving fraudulent job listings that are being posted on third-party websites. These scams typically involve individuals impersonating Equinix employees and communicating with applicants primarily through email and chat applications such as WhatsApp, Telegram, or social media platforms like LinkedIn. In these scams, applicants may receive a counterfeit offer letter in exchange for personal identification information, which is falsely presented as part of a new-hire screening process. We want to emphasize that these communications and offers are entirely illegitimate and fraudulent. Please note the following key points to help you identify legitimate Equinix communications- All official correspondence from Equinix employees will originate from an “@equinix.com” email address. Our hiring process includes a comprehensive interview procedure, which consists of in-person meetings and phone interviews. Equinix will never request your Social Security or National ID number during the interview process, nor will we ask you to pay any fees or purchase. If you receive any suspicious messages claiming to be from Equinix, please do not engage with them and report the incident to us at careers@equinix.com.
Hiring: Engineering
What employees say
+ Very good perks, Excellent facilities provided to employees. ESOPS are life changing.
− There is no clear organization-wide direction for data analytics. Efforts are fragmented across teams, making alignment and long-term planning difficult. Frequent strategic changes
More reviews on the company profile.
Interview experience · Data Engineer
Contained 4 rounds, first round involving coding, second round involving technical questions based on resume, third round involving technical round with problem solving ability testing, final round being HR behavioral ro
Easy difficulty · Bengaluru · 15 reports
More interview insightsJob description
Overview
A place where bold ideas are welcomed, human connection is valued, and everyone has the opportunity to shape their future.
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
- Build and integrate agent-based workflows using platforms such as Google Agentspace, Microsoft Copilot, and Salesforce Agentforce
- 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
- (Good to have) 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
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Job application FAQ
Last updated 24 October 2026
- How do I apply for Principal AI Researcher at Equinix?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. Equinix may attach structured assessments to interview rounds after you apply.
- Does Feedback AI show a match score for this Principal AI Researcher role?
- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is Principal AI Researcher remote or on-site in Bengaluru, Karnataka?
- This listing is marked on_site with location Bengaluru, Karnataka. Confirm details on the job description before applying.
- What skills matter for this Principal AI Researcher role at Equinix?
- This is a principal Principal AI Researcher role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.