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# Senior Software Engineer - ML Infrastructure

- **Company:** Applied Intuition
- **Location:** Sunnyvale, CA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $153,000.0 - $222,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Machine Learning, Open Source Technology, Tensorflow, Software Engineering, TorchServe, Pytorch, Deep Learning, Information Technology, Triton Inference Server, Machine Learning Operations, Data Pipelines
- **Published:** November 5, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-software-engineer-ml-infrastructure-sunnyvale-ca--fff133fa-eae6-44a0-bcf8-b0c39cb58ccd

## About the Role

Software Engineering, Agriculture, Construction, Artificial Intelligence (AI), United States Military, Operating Systems, Trucking, Mining Industry, Automotive Repair and Maintenance, Schedule Development, * A Bachelors degree in Computer Science, Software Engineering, or equivalent

 * 3+ years of professional experience
 * Experience with building software components to address production, full-stack machine learning challenges. This is not purely a research problem
 * Opinions about building a company-wide platform for ML training, evaluation, and deployment
 * Knowledge of the open source landscape with judgment on when to choose open source versus build in-house
 * Excellent analytical and problem-solving skills

Nice to have:

 * Experience with developing, running, and managing orchestration systems like Airflow and Flyte that non engineers can use to build data pipelines.
 * Experience with ML modeling frameworks (PyTorch, Tensorflow, etc.), and model serving platforms (TorchServe, TensorFlow Serving, NVIDIA Triton inference server, etc.)

## Description

We are looking for both infrastructure engineers with expertise in machine learning pipelines and ML engineers that want to work beyond modeling to join the Data & ML infra group. This role will work across the entire ML lifecycle (dataset generation, training frameworks, compute, evaluation, and deployment) and work directly with modeling teams. This team is a good fit if you are excited to work on broad, ambiguous problems and develop across the entire ML stack. At Applied Intuition, we encourage all engineers to take ownership over technical and product decisions, closely interact with external and internal users to collect feedback, and contribute to a thoughtful, dynamic team culture.

At Applied Intuition, you will:

 * Design and implement distributed cloud GPU training approaches for deep learning model training and evaluation
 * Build end-to-end machine learning pipelines and integrate them into core product workflows
 * Encourage change, especially in support of ML engineering best practices, and maintain a high standard of excellence
 * Collaborate with engineers across the entire company to solve complex data problems at scale