About Us
About You
You are a hard-working, motivated and responsible individual that enjoys working on challenging problems and building well-engineered systems. You are excited to use the latest computer vision and machine learning techniques to process visual information (images) in a continuously running CV/ML pipeline. Your attention to detail and responsible nature make you an ideal person to transform basic concepts into working solutions within our ML-based image understanding pipelines. You are excited by the prospect of working with real-world customer images to solve pressing needs with the solutions you build.
What You'll Do
Reporting to the Chief ML Scientist as a Machine Learning Engineer, you will:
- Design, implement, test, and deploy computer vision and machine learning algorithms that analyze images to extract valuable insights into the inventory and assets for our customers.
- Conduct guided research and development applying state-of-the-art methods in ML and computer vision to collaboratively identify and solve problems in the logistics space, such as:
- Rack occupancy estimation and empty bin detection
- Counting boxes on racks
- Improving OCR for small and blurry text
- Detecting and pallets and inferring properties such as color or position in rack
- Implement and update existing business logic as needed to use the results of the ML pipelines to compare against customer inventory data.
- Lead the data management process, which involves defining the instructions for data annotation, presenting the instructions to the cloud factory team, and working with them iteratively to clear any doubts and improve the overall quality of annotations.
- Support MLOPs and MLQA in continuously evaluating, scaling, and improving the organization's full-featured and growing inference suite.
- Contribute high quality improvements and fixes to our ML processing tools and pipelines.
What You'll Need
- BS in Computer Science/Engineering, or equivalent experience.
- Strong fundamentals in algorithms, mathematics, statistics, and computer science.
- Proficiency in production-grade Python with ML and computer vision ecosystem.
- Strong software engineering skills.
- Proficiency in Python and the Python ML and computer vision ecosystem (Pytorch, OpenCV, Pandas, etc).
Bonus points for...
- Familiarity building or managing ML pipeline tools and technologies.
- Extended degree or academic/personal exposure to advanced ML for computer vision.
- Experience working with ML training and inference in cloud environments, with technologies such as Google Vertex, Amazon Sagemaker, etc
Compensation and Benefits
- Competitive salary
- Comprehensive health insurance
- Parental leave
- Flexible schedule
- Unlimited paid time off
0 applies
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