Who is Flock?

Flock Safety provides the first public safety operating system that empowers private communities and law enforcement to work together to eliminate crime. We are committed to protecting human privacy and mitigating bias in policing with the development of best-in-class technology rooted in ethical design, which unites civilians and public servants in pursuit of a safer, more equitable society. 

Our Safety-as-a-Service approach includes affordable devices powered by LTE and solar that can be installed anywhere.  Our technology detects and captures objective details, decodes evidence in real-time and delivers investigative leads into the hands of those who matter. 

While safety is a serious business, we are a supportive team that is optimizing the remote experience to create strong and fun relationships even when we are physically apart. Our flock of hard-working employees thrive in a positive and inclusive environment, where a bias towards action is rewarded. Flock Safety is headquartered in Atlanta and operates nationwide. We have raised over $380M in venture capital including a recent Series E round led by Tiger Global.  Now surpassing a 3B 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 Role

As a Machine Learning Engineer on the Vision Team, you will research and develop the models and algorithms that allow our devices to decode evidence like a detective. The ideal candidate is someone with experience in developing machine learning and custom algorithms for video processing and other related computer vision domains in diverse environments.

How you'll make an impact: 

• Frame open-ended, real-world problems into well defined ML problems
• Develop data pipelines to create appropriate datasets and model feedback
• Leverage cutting-edge research and technology to create custom solutions
• Design and run experiments to test new ideas or improvements to existing models
• Build visualization and monitoring tools to evaluate the quality of our data and models
• Collaborate across teams and product to deliver solutions that fit within business and organizational requirements
• Review code of other Machine Learning Engineers

We're looking for people who:

• 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.)
• Experience with Computer Vision modeling, such as Object Detection, Multi-Object Tracking, etc.
• Good understanding of Deep Learning and Traditional ML (supervised and unsupervised) algorithms
• Experience writing Python in a team environment
• 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

Feeling uneasy that you haven’t ticked every box? That’s okay, we’ve felt that way too. Studies have shown women and minorities are less likely to apply unless they meet all qualifications. We encourage you to break the status quo and apply to roles that would make you excited to come to work every day.

Why Join Us?

Can you imagine a world without crime? We can. Our mission is simple, to eliminate crime. We pride ourselves on building a community of low-ego and easy to work with people. What makes Flock Safety special is a combination of interesting work, a compelling mission, and a chance to change the trajectory of your career. We are at a unique inflection point where, after a few (or many!) short years here, we know you will accelerate your career and look back fondly on your time with us and the work you did to make your community safer.

💰Salary & Equity: In this role, you’ll receive a starting salary of $170,000-$195,000 as well as stock options

🌴Use what you need PTO: We seriously mean it, plus 11 company holidays and your birthday off!

⚕️Fully-paid health benefits plan for employees: including Medical, Dental, and Vision and an HSA match. 

👪Family Leave: We provide 16 weeks of 100% paid leave for primary caregivers and 12 weeks of 100% paid leave for secondary caregivers. 

🍼Fertility & Family Benefits: We have partnered with Maven, a complete digital health benefit for starting and raising a family. We will reimburse $10,000 a year for adoption, surrogacy, or infertility.

🧠Mental Health: All employees receive an annual subscription to Headspace

💖Caregiver Support: We have partnered with Cariloop to provide our employees with caregiver support 

💸Carta Tax Advisor: Employees receive 1:1 sessions with Equity Tax Advisors who can address individual grants, model tax scenarios, and answer general questions. 

💻WFH Stipend: $150 per month to cover the costs of working from home.

📚L&D Stipend: $250 per year to use on Audible, Calm, Masterclass, Duolingo, Grammarly and so much more.

🏠Home Office Stipend: A one-time $750 to help you create your dream office.

🏢Coworking Space: If you’re not local to our ATL HQ, we’ll provide $250 a month to get you set up with an All Access Membership to WeWork (or a local coworking space in your area).

🐾Pet Insurance: We’ve partnered with Pumpkin to provide insurance for our employee’s fur babies. 

Flock is an equal opportunity employer. We celebrate diverse backgrounds and thoughts and welcome everyone to apply for employment with us. We are committed to fostering an environment that is inclusive, transparent, and collaborative. Mutual respect is central to how Flock operates, and we believe the best solutions come from diverse perspectives, experiences, and skills. We embrace our differences and know that we are stronger working together.

If you need assistance or an accommodation due to a disability, please email us at careers@flocksafety.com. This information will be treated as confidential and used only to determine an appropriate accommodation for the interview process.