Machine Learning Engineer, PEDM
Keeper SecuritySalary not specified
- Full Time
- Junior (1 to 2 years)
$117,000 – $171,000Compensation
Junior (1 to 2 years)Experience Level
Full TimeJob Type
UnknownVisa
Public Safety TechnologyIndustries
Position Overview
- Location Type: Remote
- Job Type: Full-Time
- Salary: $117K - $171K
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. We are 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. 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.
Requirements
- 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
- Experience writing Python in a team environment
- Ability to take on complex problems, learn quickly, iterate, and persist towards a good solution
- Effective communication skills, able to communicate at the level of your audience and seek to understand and be understood
- Basic SQL knowledge
- Basic Git knowledge
Responsibilities
- Support the machine learning model lifecycle.
- Improve model performance and address model drift.
- Take on complex problems and iterate towards solutions.
- Communicate effectively with team members.
Company Information
- Company: Flock Safety
- Industry: Public Safety Technology
- Funding: Over $700M in venture capital (Investors: Tiger Global, Andreessen Horowitz, Matrix Partners, Bedrock Capital, Meritech Capital Partners, and Initialized Capital)
- Valuation: $7.5B
- Mission: Reduce crime in the United States by 25% in the next three years.
- Culture: Supportive team, inclusive environment, bias towards action.
Skills
Machine Learning
TensorFlow
PyTorch
scikit-learn
Deep Learning
Supervised Learning
Unsupervised Learning
Python
SQL
Git
Problem-Solving
Communication
Flock Safety
License plate reader cameras for crime prevention
About Flock Safety
Flock Safety provides a system aimed at enhancing public safety through crime prevention while ensuring privacy and reducing bias. The main product is a network of license plate reader cameras that capture essential vehicle information, which helps in solving crimes. These cameras utilize machine learning technology to ensure that the data collected is objective and ethically used. Flock Safety serves a variety of clients, including neighborhoods, businesses, and law enforcement agencies in over 1,000 cities. The company operates on a subscription model, where clients pay for the installation, maintenance, and access to data and analytics. This approach not only generates a steady revenue stream but also allows clients to benefit from ongoing updates and support. Flock Safety's goal is to create safer communities by providing effective crime prevention tools that respect individual privacy and foster trust between the public and law enforcement.
Atlanta, GeorgiaHeadquarters
2017Year Founded
$372.2MTotal Funding
SERIES_ECompany Stage
Government & Public Sector, Enterprise Software, AI & Machine LearningIndustries
1,001-5,000Employees