# Data & ML Pipeline Software Engineer

**Company:** [Applied Intuition](https://hotfix.jobs/companies/applied-intuition)
**Location:** Sunnyvale, CA
**Role:** Data Engineering
**Salary:** $125k – $222k/yr
**Experience:** 3+ years
**Skills:** Python, Spark, Airflow, Kafka, Distributed Systems, ETL, Machine Learning, Data Pipelines, ML Infrastructure
**Posted:** 2026-04-21

> Builds large-scale data processing pipelines and ML infrastructure to automate data curation, model training, and iteration for autonomous vehicles using real-world and simulation data. Requires 3-5 years experience in data/ML infra, Python, and frameworks like Spark/Airflow/Kafka.

## Job Description

## Responsibilities
- Build and maintain large-scale data processing pipelines (ETL) for ingesting and curating driving datasets.
- Design and implement systems that automate data selection, labeling, training, and testing loops.
- Collaborate with modeling teams to improve training efficiency and model performance across iterations.
- Develop the core infrastructure that closes the loop between real-world test results and new model deployments.
- Use engineering expertise to help vehicles learn from data at scale, improving safety and performance.
- Mentor junior engineers and contribute to defining best practices for data-centric development.

## Requirements
- Bachelor's or higher degree in Engineering such as Computer Science, Electrical Engineering, Software Engineering.
- 3–5 years of experience in software or data infrastructure engineering.
- Expertise in building and scaling data pipelines, distributed systems, or ML infrastructure.
- Proficiency in **Python** and strong knowledge of data frameworks (**Spark**, **Airflow**, **Kafka**, etc.).
- Experience working with large-scale datasets and understanding data-driven development cycles.
- Familiarity with machine learning workflows or model training/deployment, especially automation of those processes.
- Strong systems thinking and ability to work across multiple parts of the stack (data, infra, and ML).
- Interest in seeing the direct impact of infrastructure work on vehicle performance.

## Nice to Have
- Experience with automotive (AV) or robotics systems.
- Previous work on ML platforms for large-scale products (e.g., Ads, Recommendation, or Autonomy pipelines).
- Experience with highly automated ML training workflows.
- Prior contributions to systems that connect data-driven model iteration loops ("data flywheel").
- Ability to move fast, learn quickly, and mentor others while growing with the team.

## Compensation
- Base salary range: **$125,000 - $222,000 USD** annually.
- Equity, comprehensive health/dental/vision/life/disability insurance, 401k with employer match, learning/wellness stipends, paid time off.

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