Why This Job is Featured on The SaaS Jobs
This Staff Machine Learning Engineer role stands out in the SaaS ecosystem because it sits at the intersection of productized AI and production search, using multimodal foundation models as a core capability rather than a side experiment. The listing signals a platform that blends software with real world data sources, where reliability, privacy constraints, and deployment realities shape modeling choices as much as benchmarks do.
For a long term SaaS career, the work maps closely to challenges that recur across modern subscription products: building retrieval systems that scale, setting evaluation standards that can be monitored over time, and turning research progress into maintainable pipelines. Experience fine tuning models, automating training and release workflows, and aligning cross functional expectations around quality and latency tends to transfer well to other SaaS teams operating ML driven features.
The role is best suited to an experienced ML engineer who prefers owning ambiguous modeling problems end to end, from architecture and loss design through to operationalization. It will fit someone who enjoys partnering with engineering leadership and stakeholders, and who is comfortable being accountable for systems that must keep working as product use cases evolve.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
Who is Flock?
Flock Safety is the leading safety technology platform, helping communities thrive by taking a proactive approach to crime prevention and security. Our hardware and software suite connects cities, law enforcement, businesses, schools, and neighborhoods in a nationwide public-private safety network. Trusted by over 5,000 communities, 4,500 law enforcement agencies, and 1,000 businesses, Flock delivers real-time intelligence while prioritizing privacy and responsible innovation.
We’re a high-performance, low-ego team driven by urgency, collaboration, and bold thinking. Working at Flock means tackling big challenges, moving fast, and continuously improving. It’s intense but deeply rewarding for those who want to make an impact.
With nearly $700M in venture funding and a $7.5B valuation, we’re scaling intentionally and seeking top talent to help build the impossible. If you value teamwork, ownership, and solving tough problems, Flock could be the place for you.
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 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 Staff Machine Learning Scientist 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
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.
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.
Engineering Manager Interview: You will meet with Engineering leadership to really dive into the role, the team, expectations, and what success means at Flock. This interview will cover technical questions related to the role, your product experience, guiding strategy, stakeholder communication, & launch experience. This is your chance to really nerd out with someone in your field.
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.
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.
The Perks
🌴Flexible PTO: We seriously mean it, plus 11 company holidays.
⚕️Fully-paid health benefits plan for employees: including Medical, Dental, and Vision and an HSA match.
👪Family Leave: All employees receive 12 weeks of 100% paid parental leave. Birthing parents are eligible for an additional 6-8 weeks of physical recovery time.
🍼Fertility & Family Benefits: We have partnered with Maven, a complete digital health benefit for starting and raising a family. In 2025, Flock will provide a $ 50,000-lifetime maximum benefit related to eligible adoption, surrogacy, or fertility expenses.
💖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.
💚ERGs: We want all employees to thrive and feel like they belong at Flock. We offer three ERGs today - Women of Flock, Flock Proud, and Melanin Motion. If you are interested in talking to a representative from one of these, please let your recruiter know.
💻WFH Stipend: $150 per month to cover the costs of working from home.
📚Productivity Stipend: $300 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.
If an offer is extended and accepted, this position requires the ability to obtain and maintain Criminal Justice Information Services (CJIS) certification as a condition of employment. Applicants must meet all FBI CJIS Security Policy requirements, including a fingerprint-based background check.
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 recruiting@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.
Flock Safety is aware of fraudulent individuals and agencies falsely claiming to represent our company. All legitimate communication from Flock Safety will come from an email address ending in @flocksafety.com. We do not make job offers through messaging apps, social platforms, or unauthorized third parties, and we will never request payment or sensitive personal information during the hiring process. If you encounter suspicious outreach related to a Flock Safety role, please report it to recruiting@flocksafety.com
