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18 Zoom Start Jobs

Senior Machine Learning Engineer

Zoom Start India

8-12 years

Remote

1 vacancy

Zoom Start

posted 12d ago

Job Role Insights

Key skills for the job

Medical Coding Python SQL Machine Learning Customer Support CCTV Monitoring

+ 3 more

Job Description

What you can expect
As a Sr. Machine Learning Engineer at Zoom, you will play a key role in developing and deploying ML models for Go To Market business use cases. You will design, implement, and optimize scalable ML models, build APIs and deploy to production. You will mentor and coach Ml engineers in the team and collaborate with enterprise architects in shaping ML ecosystem. Your work will have a direct impact on sales, success, customer support resulting into Zooms growth and driving customer satisfaction and retention.

About the Team
The Data Team drives data-informed decision-making at Zoom, supporting product development with behavioral insights and helping go-to-market teams with risk and buying propensity scores. We aim to deliver better products and sales outcomes while ensuring compliance with privacy and regulatory requirements for millions of users globally.

What we re looking for

Possess a BS/MS in Computer Science with at least 8+ years of experience in Software Engineering, Machine Learning, AI, or Data Science
Possess excellent knowledge of data structures and algorithms with expert level coding using object-oriented principles in Java or Python
Demonstrate an expert-level SQL skills for querying and manipulating data using Snowflake, along with experience in ML algorithms such as regression, classification, and clustering.
Have practical experience with ML frameworks such as Scikit-learn, TensorFlow, PyTorch and MLOps tools such as MLflow, Kubeflow, or SageMaker
Experience with deep learning models/neural networks for forecasting and scoring models is highly valued
Demonstrate hands-on experience with cloud data technologies such as Snowflake, Databricks, Apache Spark, and Apache Airflow
Have a good understanding of API frameworks such as FAST API and containerization and cloud infrastructure (Docker, Jenkins, CI/CD process)
Experience implementing model monitoring including data, feature, and model drift; an advantage if these have been used to trigger automatic model retraining
Experience deploying, maintaining, and monitoring models in production pipelines, with expertise in data engineering, feature engineering, and model evaluation techniques.
Show excellent communication skills and technical leadership ability to work with cross-functional geo distributed environment