Software Engineer, II - Data Engineering

At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business. A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family , we are focused solely on developing software for automated trucks to transform how the world moves freight. Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.

Create robust and resilient pipelines to process massive daily volumes of data created by vehicle fleets and simulation environments

Build and support scalable pipelines as part of Torc’s Data Factory to delivery data for ML training at scale

Scale Torc’s data lake through a distributed storage system, data crawling and discovery

Promote and protect the integrity of data through validation, versioning, data provenance, and governance

Support the expansion of Torc’s data lake through acquisition of additional data sets from internal and external sources

Contribute to the design, architecture and delivery of cloud-based solutions

Collaborate with teams specializing in perception, planning, control, mapping and vehicle testing to develop solutions that support product delivery

Support the implementation of emerging cloud-based capabilities that can extend our technology stack and improve our ability to build, deploy and test safety-critical software for self-driving vehicles

Participate in the team’s on-call rotation to support our deployed systems during business hours

Managed services powered by AWS (Lambda, SFN, Batch, EventBridge, Athena, Glue)

Linux / Bash

Docker

Terraform

Python

React/Javascript

On-Call Tooling (Datadog, AWS Cloudwatch)

CI/CD Tooling (Jenkins, GitHub Actions)

Bachelor’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 4+ years of experience or;

Master’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 0-3+ years of experience.

Experience deploying, troubleshooting, monitoring and maintaining Linux systems

Experience building and maintaining workloads in public cloud environments

Knowledge of different database architectures, including but not limited to relational and NoSQL databases, vector stores, data warehousing and clustered, distributed data stores

Practical experience with Linux and general bash scripting

Practical experience with Docker and containerization

Implementation of workflow patterns using directed acyclic graphs (Apache Airflow, AWS Step Functions)

A strong commitment to test-driven development patterns, continuous integration and delivery, and infrastructure as code

Strong organizational, time management, and communication skills working with a team orientation and collaborative style

Experience with the Databricks platform, particularly for serving data, visualizations and jobs

Experience with scaling data for ML and AI workloads using Ray

Experience with pandas, numpy and other Python-based data analysis libraries and tooling

Deep knowledge of AWS serverless architectures (Lambda, Batch, ECS Fargate, Glue, Athena)

Experience with data storage and acquisition patterns for robotics and advanced driver assistance systems

Own end-to-end architecture and delivery of cloud-based solutions.