ML Engineer Intern at Zeitview

Zeitview (formerly DroneBase) is the leading intelligent aerial imaging company for high-value infrastructure, providing businesses with actionable, real-time insights through a single-source solution to recover revenue and reduce liability risk. Zeitview is the trusted data management platform for worldwide enterprise clients across industries such as renewable energy, insurance, telecommunications, construction, real estate, and critical infrastructure.

Job Description

As an ML (Machine Learning) Engineer Intern, you will help design and develop AI computer vision inference infrastructure across multiple industry verticals including solar, wind turbines, and commercial roofing. Your tasks will include:

• Deploying models in batch processing and real-time streaming architectures in a cloud environment.
• Designing and developing model monitoring frameworks to ensure proper functioning of deployed models.
• Collaborating with product managers and ML engineers to meet product specifications.
• Building, monitoring, and deploying machine learning inference pipelines in cloud environments like AWS.
• Optimizing machine learning inference pipelines for speed, scalability, and robustness.
• Writing documentation for running, testing, and using the developed models and programs.

Employer’s Minimum Job Requirements

• Experience with deploying computer vision models in a professional setting.
• Experience with deploying and monitoring machine learning models in production environments.
• Proficiency in Python, PyTorch, and AWS.
• Experience building scalable machine learning models for large data volumes.
• Experience working with aerial and/or geospatial imagery.
• Experience with Metaflow and PyTorch Lightning.

Qualifications

• Minimum Degree: Bachelor's in Progress
• Fields of Acceptable Study: Computer Engineering, Electrical Engineering, Statistics, Computer Science
• Passout Year: 2021/2022/2023/2024
• Job Location: Bengaluru, Karnataka, India
• Work Type: Full-time, Partially remote

Skills Required

• Deploying computer vision models
• Deploying and monitoring ML models in production
• Proficiency in Python, PyTorch, AWS
• Building scalable ML models for large data volumes
• Working with aerial/geospatial imagery
• Using Metaflow and PyTorch Lightning

ML Engineer Technical Coding Challenge

• Deploy a turbine preflagging model with given weights and a simple inference script.
• Use 50 anomaly images and 50 clean images.
• Deploy the model as an endpoint locally.
• Create a script to test model endpoints.
• Create model monitoring scripts.
• Create unit and integration tests for model deployment.
• Explain how to scale model deployment in a cloud infrastructure.

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