2023 Machine Learning Engineer – New Grad 458 views

Zoomies help people stay connected so they can get more done together. They set out to build the best video product for the enterprise, and today help people communicate better with products like Zoom Contact Center, Zoom Phone, Zoom Events, Zoom Apps, Zoom Rooms, and Zoom Webinars.

They’re problem-solvers, working at a fast pace to design solutions with the customers and users in mind. Here, you’ll work across teams to deliver impactful projects that are changing the way people communicate and enjoy opportunities to advance your career in a diverse, inclusive environment.

What You Will Do

Be part of a team whose focus is to solve cutting edge AI problems and deploy models that constantly advance the state-of-the-art. You will be working across various NLP areas like STT, translation, summarization, sentiment analysis, TTS, and other interesting challenges that are challenging at Zoom’s scale.

Responsibilities

• Build and deploy state of the art ML models for NLP use cases
• Build large scale training and inference pipelines
• Build and scale realtime ML services which enable Zoom’s products
• Take ML models from Research all the way to production
• Build metrics, dashboards to measure both ML and system performance
• Work closely with the Research teams build required tools and services to make them productive
• Work closely with the product and operations teams to integrate ML services seamlessly into the products
• Work closely with various teams on data acquisition, cleanup and related tooling

Qualifications

• Currently pursuing a Master’s or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or related STEM field with an expectation that degree will be obtained by July 2023 or earlier
• Strong coding skills in Python, C/C++, or Java
• Experience with one or more of the following: Natural Language Processing, text understanding, classification, ranking systems or similar
• Experience in Machine Learning toolkits (TensorFlow, PyTorch)
• Familiarity with large-scale data processing and distributed systems
• Proven mathematical knowledge; understanding of machine learning, statistics
• Relevant professional experience with applied data analytics and predictive modeling

Bonus Qualifications

• Experience framework such as MLflow, Kubeflow, Airflow, Seldon Core, TFServing etc
• Experience in distributed training and performance optimization on GPU’s
• Expertise in crafting Data Models for high performance and scalability
• Autoscaling, containers, performance tuning and optimization
• Experience with Deep Learning for NLP
• Strong verbal and written communication skills