Job Description

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

As a Staff Machine Learning Engineer, Multimodal Modeling, you will lead the advancement of our core embedding-based retrieval systems, with a primary focus on the scientific aspects of modeling. This includes fine-tuning and extending multimodal models (e.g., CLIP, SigLIP) to improve performance, generalization, and cross-modal alignment. You’ll work on unifying text and image representations, improving model performance, and ensuring extensibility across evolving product use cases. Your work will be central to Flock’s ability to deliver fast, accurate, and scalable search experiences powered by state-of-the-art vision-language systems.

The Skillset 

• 7+ years of industry experience in Machine Learning with a focus on representation learning, multimodal modeling, or embedding-based retrieval.

• Deep domain knowledge in at least one area: computer vision, natural language processing, or recommendation systems.

• Strong proficiency in PyTorch, with experience fine-tuning foundation models and adapting pretrained vision-language models to real-world tasks.

• Demonstrated ability to customize and extend model architectures, training loops, loss functions, and data pipelines to deliver impact.

• Experience with embedding-based retrieval, including contrastive learning, multimodal alignment, and designing evaluation methods for vector similarity search and embedding quality.

• Solid engineering fundamentals in Python, with familiarity in Git, SQL, and Bash.

• Comfortable working independently and navigating ambiguity, with a track record of solving open-ended modeling problems.

Bonus if You Have

• Familiarity with model compression techniques, such as distillation, quantization, and architecture pruning, to improve inference efficiency and deployability.

• Experience with vector search infrastructure, including provisioning, maintaining, and querying large-scale vector databases (e.g., FAISS, Weaviate, Pinecone)

• Proficient with multi-GPU and distributed training workflows, to scale training of large multimodal models efficiently

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.

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 Senior Data Engineer at Flock Safety. 

The First 30 Days

• Meet the team & cross-functional stakeholders 

• Understand the system architecture for freeform search and the ownership of the various components

• One major cultural component within Flock’s engineering teams is the “first day push”. The first day push focuses setup and onboarding to the things that matter to deliver value.

The First 60 Days 

• Gain familiarity and performing R&D

• Begin to automate the systems for training, evaluation, testing, and model release

90 Days & Beyond 

• Own long-term maintenance

• Become a leader for the team offering hand-ons help

• Begin exploratory work

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 conversation, you’ll meet with a recruiter to chat through your background, what you could bring to Flock, what you are looking for in your next role, and who we are. 

2. Engineering Manager Interview: You will meet with Engineering leadership to really dive into the role, the team, expectations, and what success means at Flock. You should expect the interview will cover your product experience, guiding strategy, stakeholder communication, & launch experience. This is your chance to really nerd out with someone in your field. 

3. Panel: Learn more about the team, responsibilities, and workflows. You should be prepared to speak about past projects, how you collaborate and communicate with others, and how you live our values. Depending on the team and role you are interviewing for, you may meet with several teammates as well as cross-functional partners.

4. The Executive Review: An opportunity to meet leaders within the ML organization. They will be looking to get to know you better, understand your motivations, and understand your background. Be prepared to ask well-thought-out questions about the company, culture, and more. 

Salary & Equity

In this role, you’ll receive a starting salary of $200,000-240,000 as well as stock options. Base salary is determined by job-related experience, education/training, as well as market indicators. Your recruiter will discuss this in-depth with you during our first chat.

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.

At Flock Safety, we compensate our employees fairly for their work. Base salary is determined by job-related experience, education/training, as well as market indicators. The range above is representative of base salary only and does not include equity, sales bonus plans (when applicable) and benefits. This range may be modified in the future. This job posting may span more than one career level.

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