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Temporary Data Integrity Engineer

Smart Design
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We are searching for a temporary data integrity engineer to join our team. This will be an onsite role that requires this candidate to work in our Brooklyn studio. The role will last 4 months, with the potential to transition to a full-time position.

As a data integrity engineer, you will join a team of machine learning engineers, data scientists and backend developers in developing an exciting new computer vision home product.

Your role will be to interface with the engineers above while also being responsible for the integrity of our cloud-sourced data through a platform we have built using Meta’s “Segment Anything Model”. Additionally, this new team member will work on custom data models for the commercial food storage community. This role should be for anyone that is trying to get their foot in the door with machine learning, computer vision and live inference.

You Will

  • Collaborate in daily standups and weekly sprint planning to align on priorities, surface risks, and execute toward sprint goals
  • Curate and prune datasets using our Segment Anything platform, preparing high-quality batches for annotation
  • Own annotation job specifications, continuously refining instructions to improve accuracy and consistency of labeled data
  • Analyze computer vision outputs post-annotation to assess quality, identify gaps, and inform next steps
  • Define and prioritize data needs based on model performance, confidence scores, and data weighting metrics
  • Iterate on and improve existing food storage and spoilage detection models through ongoing experimentation

 

Naturally, you'll have:

  • A bachelor’s degree in Computer Science, Data Science, Machine Learning, or a related field
  • Strong working proficiency in Python, Anaconda, and common data visualization libraries
  • Experience or familiarity with data annotation workflows and platforms, including Meta’s Segment Anything Model
  • Hands-on experience with PyTorch-based computer vision frameworks such as YOLO or DETR
  • Familiarity with classical ML approaches (e.g., Random Forests) as well as transformer-based architectures
  • Strong attention to detail, particularly in post-annotation analysis and model evaluation

 

A plus if you have:

  • Comfort working within AWS Infrastructure
  • Experience working on IoT projects and multi-disciplinary teams
  • Knowledge of food science and industry

Rates will be determined based on experience but ranging from $30-50/hour.

Direct candidates only; NO THIRD PARTY RECRUITERS PLEASE.

We are committed to creating an inclusive culture and are proud to be an equal opportunity employer. At this time, we are unable to sponsor for this position.