Who is Flock?

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.

The Opportunity:

Flock Safety is a leading public safety company dedicated to eliminating crime through a full-service offering of hybrid hardware and software systems. As a Machine Learning Engineer you will support the machine learning model lifecycle that allows our devices to decode evidence like a detective and define how crime is eliminated. As an ML Engineer on the Maintenance Team, you will play a key role in improving model performance and addressing model drift. The ideal candidate is someone who is passionate about taking cutting edge research and technology to solve new problems, and enjoys working with the entire lifecycle of Machine Learning software.

The Skillset:

• 2+ years Experience writing Python in a production environment

• BS/MS in Computer Science, Mathematics, Physics, Engineering, or proof of equivalent software engineering experience (PhD’s welcome)

• Experience solving problems using Machine Learning frameworks (Tensorflow, PyTorch, scikit-learn, etc.)

• Good understanding of Deep Learning and Traditional ML (supervised and unsupervised) algorithms

• Able to take on complex problems, learn quickly, iterate, and persist towards a good solution

• Effectively communicate, at the level of your audience, and seek to understand and be understood

• Basic SQL knowledge

• Basic Git knowledge

• Experience with linear algebra, probability, and statistics preferred
  

90 Days at Flock

We are a results-oriented culture and believe job descriptions are a thing of the past. We prescribe to 90 day plans and believe that good days lead to good weeks, which lead to good months. This serves as a preview of the 90 day plan you will receive if you were to be hired as a Software Engineer at Flock Safety. 

The First 30 Days

• Onboard and Integrate:

  • Familiarize yourself with the company's mission, products, and development processes.

  • Build relationships with key stakeholders to understand their needs and expectations. Meeting with a member of the following teams:

    • Machine Learning

    • Data Engineering

    • Product

• Complete improvements/experiments pertaining to customer issues.

The First 60 Days 

• Regularly monitor and analyze the performance of deployed machine learning models

• Work with ML Maintenance team to prioritize and resolve customer issues

90 Days & Beyond 

• Ability to perform role with little guidance with transparency.

• Communicating across multiple teams to solve problems efficiently.

• Be comfortable picking up engineering tasks of larger size and more ambiguity.

The Interview Process 

We want our interview process to be a true reflection of our culture: transparent and collaborative. Throughout the interview process, your recruiter will guide you through the next steps and ensure you feel prepared every step of the way. 

1. Our First Chat: During this first c