Software Systems Engineer, Data Pipelines

Fyusion is a leading machine learning and computer vision company focused on automotive inspections and related applications. Our patented 3D format enables anyone to capture and display interactive 3D images using their smartphone, and enables significant added functionality with deep visual understanding and machine learning-driven analysis.

Founded in 2014, Fyusion is now part of the Cox Automotive family. Our team includes some of the world's top researchers and developers in light field imaging and AI, continuing to push boundaries and innovate at the highest level from our San Francisco research center.

The Damage Analysis Team is the part of the Fyusion Research Department that designs and develops the technology at the core of Fyusion’s products for automated inspection. This team works at the intersection of deep learning and computer vision, providing the best approaches for an objective assessment of a car's condition, both for fixed and mobile imaging solutions.

This role will work with our best-in-class Research and Engineering teams for improving and enriching our data pipelines. This is a high-impact role that will give the opportunity to shape products used millions of times per month and that are revolutionizing the car buying experience.
Here's the day to day:

  • Automate, patch and otherwise develop data processing systems written in Python/C++ and orchestrated using Docker/Kubernetes
  • Maintain data storage and retrieval systems, while consistently responding to needs for enhanced sorting, searching, and transformation
  • Work with embedding spaces, keeping vector search operations fast and insightful
  • Ensure the integrity and security of all proprietary data using industry best practices and up-to-date standards
  • Track progress in model training pipelines and ensure that benchmarks are being met and exceeded
  • Maximize the productivity vs cost for compute resources, both cloud and on-prem
  • Troubleshoot ML inference by identifying training bottlenecks and outliers in training data
  • Present analysis and insights with clear descriptions and visual aids as needed
Here's what we're looking for:

  • 5+ years of experience in data engineering, data pipelines, ML Ops, or similar field
  • Proficiency in Python, working knowledge (or better) of C++
  • Solid programming fundamentals: programming paradigms, design patterns, data structures and algorithms, complexity analysis, concurrency
  • Experience with data indexing and retrieval toolsets (example: ELK stack).  You can explain in great detail how these tools work under-the-hood and the tradeoffs associated with their use
  • Experience using containers and with container orchestration (Docker/Kubernetes preferred)
  • Knowledge of ML model training techniques, trade offs, and pitfalls
  • Knowledge of vector search: similarity metrics, encoding embeddings, ANN search algorithms
  • Software development best practices: version control (Git), designing and maintaining automated tests, giving and receiving code review, taking an active role in regular release cycles
Bonus points for:

  • Math fundamentals: statistics, linear algebra, calculus
  • Experience with data science tools: SciPy, R, Matlab or similar
  • Open source contributor for a relevant tool
Here's what we can offer you:

A competitive compensation, health, vision and dental benefits with premiums paid by Fyusion, unlimited PTO plan, company holidays (including your birthday), and the chance to be part of a pioneering technology team!

We offer some amazing perks for those working from our SF HQ: commuter benefits, company catered lunches, a fully stocked snack pantry, tons of company off-sites, and a pup friendly workplace.

If you read this job description and saw your name all over this, apply! If you read this, and think that you might need some help hitting all of the points, please apply! We have an entire team who is happy to help and share our knowledge with you.

The benefits do not apply to contract or internship positions.

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