Data Scientist III

Data Scientist III

Equinix is the world’s digital infrastructure company, operating 240+ data centers across the globe and providing interconnections to all the key clouds and networks. Businesses need one place to simplify and bring together fragmented, complex infrastructure that spans private and public cloud environments. Our global platform allows customers to place infrastructure wherever they need it and connect it to everything they need to succeed.

We are a fast-growing global company with 20 years of consecutive quarterly growth*. Through our innovative portfolio of high-performance products and services, we have created the largest, most active global ecosystem of 10,000+ companies, including 2,100 networks and 3,000+ cloud and IT service providers in 32 countries spanning six continents.  

A career at Equinix means you will collaborate on work that impacts the world and be surrounded by endless opportunities to learn new skills and grow in varied directions. We embrace diversity in thought and contribution and are committed to providing an equitable work environment. that is foundational to our core values as a company and is vital to our success. 

*As of Quarter 4 2022

Job Summary
Watched a movie online? accessed an email? Used a cloud? Odds are that you are already been using Equinix data centers in some form.
Equinix operates International Business Exchange™ where information driven world lives and thrives. Equinix IBXs provide a platform where many of the world’s best brands are launching their next break through innovations.

As an Full stack Data Scientist you will be responsible to build, optimize our AI/ML systems. You will be evaluating existing machine learning (ML) processes, performing statistical analysis to resolve data set problems, and enhancing the accuracy of our AI software's capabilities.

Responsibilities

• Research and implement appropriate AI algorithms and tools

• Envision, implement, and deliver production-level Classical Machine Learning models(Regression, Classification and clustering), NLP models (Sentiment, Summarization, Chatboat/QA, Info Retrieval), Computer Vision( Image Classification, Object Detection, Semantic Segmentation and Instance Segmentation using Yolo V7, DDRNet, RFTM using pre-trained datasets(Coco, Cityscapes)

• Deploy ML models into production using cutting edge deployment strategies, conduct A/B tests to objectively measure improvements

• Keep innovating and optimising the machine learning workflow, from data exploration, model experimentation/prototyping to production

• Apply cutting edge technologies and tool chain in big data and machine learning to build machine learning platform on Cloud (ML ops)

• Building Features, running tests, performing statistical analysis, and interpreting test results

• Proficient in any of the deep learning frameworks such as PyTorch, TensorFlow, Keras

• Develop a model pipeline in a Dev env , check in to Git, use GitHub actions, containerise the application and deploy it to VM, App Engine or K8 Cluster

Qualifications

• 1+ years with PhD, 2+ Years with Masters and 4+ Years with Bachelors in Data Science, Computer Science or Machine Learning

• Experience coding in Python (needed)

• Excellent understanding of software engineering principles and design patterns

• Experience in one of the cloud platforms 

• Ability to communicate the results of analysis

• Highly effective time management, communication, and organisational skills

Equinix is committed to ensuring that our employment process is open to all individuals, including those with a disability. If you need assistance in applying for an open position, you may send an email to [email protected] Please provide your contact information and let us know how we can assist you.

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 consideration of race, color, religion, creed, national or ethnic origin, ancestry, place of birth, citizenship, sex, pregnancy / childbirth 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 / organizational affiliation, status as a victim or family member of a victim of crime or abuse, or any other status protected by applicable law.