Parallel Systems is an early-stage startup company developing the future of intermodal transportation. Our mission is to decarbonize freight while improving supply chain logistics and safety. We are developing vehicles and software to create new autonomous and electric transportation systems for existing rail infrastructure.

At Parallel Systems, we value the team as much as the mission. We want to work with talented people that are humble, motivated, and persistent. Our most successful team members are self-starters and collaborate with others to reach our collective goals.

Parallel is looking for engineers with experience working on ML infrastructure, data pipelines, and other engineering automation projects to join a fast-paced team building tooling and infrastructure for ML projects. Build robust infrastructure that supports a rapid development lifecycle, including tools supporting data collection, model evaluation and debugging, validation, deployment and monitoring of production systems.

Responsibilities

- Design and implement large scale data processing pipelines for images and other sensor inputs.
- Design and implement tools that facilitate ML research, development and deployment
- Work closely with the Perception team and other internal ML customers to build infrastructure that drives productivity and performance improvements

Requirements

- Bachelor's degree in an engineering, math, or related field
- 5+ years experience developing distributed computing or data infrastructure
- Experience with distributed data processing frameworks such as Spark, Flink, or Apache Beam
- Experience with Pytorch or similar deep learning frameworks (e.g. TensorFlow, Apache MXNet)
- Strong software engineering fundamentals

Preferred

- MS or PhD in Computer Science or equivalent practical experience
- Experience with cloud computing. AWS EC2, etc
- Experience building infrastructure for applied ML. (Docker, Kubernetes)
- Experience with distributed data warehouse platforms such as BigQuery, Snowflake, or Databricks
- Experience with scientific computing libraries such as numpy, pandas, or scikit-learn.
- Knowledge of machine learning applied to computer vision is a plus.

About Parallel Systems

Parallel Systems is an equal opportunity employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to any discriminatory factor protected by applicable federal, state or local laws. We work to build an inclusive environment in which all people can come to do their best work.