Staff Machine Learning Scientist - Remote

Overview

Flock Safety is an all-in-one technology solution to eliminate crime and keep communities safe. Our intelligent platform combines the power of communities at scale - including cities, businesses, schools, and law enforcement agencies - to shape a safer future together. Our full-service, maintenance-free technology solution is trusted by communities across the country to help solve and deter crime in the pursuit of safer communities for everyone.

Our holistic public safety platform is comprehensive and intelligent, providing the actionable evidence needed to solve, deter and reduce crime across neighborhoods, schools, businesses and entire cities. Without compromising transparency or privacy, we are turning unbiased data into objective answers.

Flock strives to offer a career-defining experience where you can also make an impact on your community. While safety is a serious business, we are a supportive team that is optimizing the remote experience to create strong and fulfilling relationships even when we are physically apart. Our group of hard-working employees thrive in a positive and inclusive environment, where a bias towards action is rewarded.

We have raised over $700M in venture capital from investors including Tiger Global, Andreessen Horowitz, Matrix Partners, Bedrock Capital, Meritech Capital Partners, and Initialized Capital. Now surpassing a $7.5B valuation, Flock is scaling intentionally and seeking the best and brightest to help us meet our goal of reducing crime in the United States by 25% in the next three years.

In Short

• Lead the advancement of core embedding-based retrieval systems.
• Focus on scientific aspects of modeling and fine-tuning multimodal models.
• Work on unifying text and image representations.
• Improve model performance and ensure extensibility across evolving product use cases.
• Deliver fast, accurate, and scalable search experiences.
• 7+ years of industry experience in Machine Learning.
• Strong proficiency in PyTorch.
• Demonstrated ability to customize model architectures.
• Comfortable working independently and solving open-ended modeling problems.
• Encouraged to apply even if not meeting all qualifications.

Requirements

• Deep domain knowledge in computer vision, natural language processing, or recommendation systems.
• Experience with embedding-based retrieval and contrastive learning.
• Solid engineering fundamentals in Python.
• Familiarity with Git, SQL, and Bash.
• Experience with model compression techniques is a bonus.
• Proficient with multi-GPU and distributed training workflows.

Benefits

• Competitive starting salary and stock options.
• Inclusive and collaborative work environment.
• Opportunity to make an impact on community safety.
• Career-defining experience with support for remote work.
• Transparent and collaborative interview process.