Senior Machine Learning Engineer

Job description

HoneyBook is the leading AI-powered business management platform for service-based business owners. Designed to enhance - not replace - independent professionals. HoneyBook’s AI-powered tools help businesses attract leads, connect with clients, book projects, and manage payments more efficiently. With AI seamlessly integrated into every workflow, entrepreneurs can focus on their craft while scaling their businesses with confidence. Since its founding in 2013, HoneyBook has powered over 25 million client relationships and processed more than $12 billion in transactions, helping independent businesses grow faster and smarter. Our culture is built on five core values that inform everything we do. We encourage collaboration, feedback, ownership, and maintain a growth mindset. We know experience comes in many forms - some visible on your resume, others not. No one candidate will be a 100% perfect match to our description, so if you thrive in a fast-paced, intellectually curious environment and have relevant experience, we encourage you to apply. We're looking for a ML Engineer to join our Data team in Tel Aviv. Our team sits at the heart of HoneyBook's data stack - we build and maintain the infrastructure, pipelines, and AI-powered systems that DS, product, marketing and other stakeholders rely on to move fast and make smart decisions. **What you'll work on:** - **Integrate and productionize LLM-based systems:** from prompt registries and model gateways to agentic workflows - with a focus on reliability, observability, and cost efficiency. - **Own our core MLOps infrastructure:** build and maintain our feature store, vector database, training and monitoring tools, etc.- so DS and product teams can ship AI features without infrastructure becoming the bottleneck. - **Build AI-powered Python** **microservices** that integrate LLMs, scraping, pipelines and internal data into product features used by hundreds of thousands of businesses. - **Collaborate deeply** with data scientists, engineers and product managers to turn ideas into reliable, scalable ML systems, iterating quickly from prototype to production. - **Own initiatives end-to-end:** from design doc to production deployment, including monitoring, documentation, and handoff. **Here is what is needed:** - **4+ years** of production engineering experience, with at least **3 years** working on data-intensive systems in Python. - Mindset of ownership, curiosity, and can-do attitude in a fast‑moving environment. - Hands-on experience with LLM-based systems in production - prompt management, scale, cost optimization, latency, and reliability. - Distributed systems fluency - event-driven architecture, idempotency, backpressure, schema evolution. - Workflow orchestration experience, both batch and streaming. - Comfortable with ambiguity - scoping unclear requests, making speed vs. robustness tradeoffs, communicating transparently when things change. - Strong collaboration and communication skills in Hebrew and English **Nice to have:** - Experience with MLOps tooling (feature stores, training pipelines, model serving, or equivalent). - SQL and data warehouse fluency (DBT, Snowflake, or equivalent). ***The good stuff:*** ***Mission-driven:** You'll be joining more than just another startup. Our members’ success is at the heart of everything we do.* ***Impact:** We move quickly and encourage every employee to push the envelope. Our best ideas come from out-of-the-box thinking and innovation; be ready to fail fast and often!* ***Compensation:** We offer a competitive salary and meaningful equity grants.* ***Benefits & perks:** From wellness programs to exceptional family leave policies, the health and happiness of our employees are foremost.* ***Our core values:*** ***People come first:** We prioritize people as we explore opportunities and work through challenges.* ***Raise the bar:** We push for greatness—for ourselves, each other, and our members.* ***Own it:** Trust and ownership let us make decisions with confidence.* ***We love what we do:** We bring passion to our work and love what we create for our members.* ***Keep it real:** Authenticity, respect, and transparency are at our core.* *The opportunity at HoneyBook is huge. Our primary customers today are creative businesses that generate $150M in revenue per year in the US. Founded in 2013, HoneyBook is based in San Francisco and Tel Aviv, has raised $498M, and is funded by Tiger Global Management, Norwest Venture Partners, Aleph, Hillsven Capital, OurCrowd, Durable Capital Partners LP, Vintage Investment Partners, Battery Ventures, Citi Ventures, Zeev Ventures, and 01 Advisors.* **Follow us on** [**LinkedIn**](https://www.linkedin.com/company/honeybook/)**,** [**BuiltIn**](https://builtin.com/company/honeybook) **and** [**Instagram**](https://www.instagram.com/wearehoneybook/) **to catch the latest stories about HoneyBook.** Applicant Information When you apply for a job or an independent contractor/agent position with HoneyBook, we collect the information that you provide in connection with your application. This includes name, contact information, professional credentials and skills, educational and work history, and other information that may be included in a resume or provided during interviews (which may be recorded). This may also include demographic or diversity information that you voluntarily provide. We may also conduct background checks and receive related information. We use applicants’ information to facilitate our recruitment activities and process applications, including evaluating candidates and monitoring recruitment statistics. We use successful applicants’ information to administer the employment or independent contractor relationship. We may also use and disclose applicants’ information (a) to improve our Services, (b) as otherwise necessary to comply with relevant laws, (c) to respond to subpoenas or warrants served on HoneyBook, and (d) to protect and defend the rights or property of HoneyBook or others. Access our [Privacy Policy](https://www.honeybook.com/terms/privacy) .