Description

You will build and deploy machine learning solutions for complex data problems, owning the lifecycle from model training to production infrastructure.

This role is remote.

Responsibilities

• Fine-tune and retrain off-the-shelf computer-vision models, primarily YOLO-based, for object detection.
• Optimize models for edge deployment using techniques like quantization and distillation.
• Containerize FastAPI-based web services using Docker and publish results to message brokers.
• Operate and maintain ML infrastructure within a production architecture utilizing Kubernetes and Google Cloud Platform.
• Develop and optimize ETL processes for large datasets, ensuring pipeline speed and efficiency.

Required Skills

• 8+ years of experience in data science, big data engineering, or a similar field.
• Expertise in YOLO-based models and relevant ML frameworks.
• Proficiency with Docker for containerization.
• Experience with Kubernetes and Google Cloud Platform (GCP).
• Strong programming skills in Python, Scala, or R.
• Proficiency with big data technologies including Spark, Hadoop, Hive, and NoSQL databases (Cassandra, MongoDB).
• Expertise in statistical analysis, data mining, and predictive analytics.
• Ability to handle large datasets and perform data pipeline optimization.

Key Skills

Education

Not specified