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# Machine Learning Engineer

- **Company:** Coactive Systems Inc.
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, Software Applications, Microsoft Azure, Big Data, C++ (Programming Language), Cloud Computing, Cloud Engineering, Data Systems, Apache Hadoop, Apache Hive, Python (Programming Language), Machine Learning, Cloud Services, Tensorflow, Unstructured Data, Workflow Management Systems, Enterprise Software Applications, Pytorch, System Availability, Apache Spark, Kubernetes, Information Technology, Production Code, Terraform
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25303_8f9a0dffae2b69df14c23881fe8d086a

## About the Role

* BS (or higher) in Computer Science or related fields, or equivalent experience.
 * 5+ years experience writing production-grade code in Python, Java, C++, or similar language.
 * 5+ years experience building application software on cloud native platforms (AWS, Azure or GCP). Experience building enterprise applications is a plus.
 * Experience building and maintaining pipelines for large scale ML training, monitoring, and serving (PyTorch, Tensorflow, TFX).
 * Experience in developing data-intensive applications (Apache Spark, Hadoop, Hive).
 * Experience with orchestration tools (Kubernetes) and infrastructure as code (Terraform) is a big plus.

## Description

As a software engineer, you will work coactively with the best in ML and data systems, building the foundation for understanding unstructured image and video data.

What you'll do:

 * Productionize the cutting edge techniques in data-centric AI (active learning, multimodal intelligent search) and representation learning at scale using latest foundation models.
 * Collaborate with a world-class team of engineers, researchers, and scientists to create algorithms built on top of machine learning models to enable efficient, scalable search and analysis on large scale unstructured data.
 * Build infrastructure to enable training and serving large scale machine learning models on image and video datasets.
 * Tackle challenging problems at the intersection of cloud infrastructure and machine learning.
 * Build observability and monitoring infrastructure (with Open Tracing) to ensure high availability of cloud services.
 * Up-skill the team by advocating to shape engineering best practices and company culture as we grow.