--- title: 'Founding AI/ML Engineer at hellobabs.ai' canonical: 'https://feeny.ai/job/founding-ai-ml-engineer-hellobabs-ai-san-francisco-se5qehpafhkb' type: 'job' last_seen: '2026-09-10' --- # Founding AI/ML Engineer at hellobabs.ai - **Company:** hellobabs.ai - **Location:** San Francisco, CA - **Employment:** full-time - **Work type:** onsite - **Posted:** 2025-11-05 - **Last confirmed live:** 2026-09-10 - **Apply:** https://jobs.gem.com/hellobabs-ai/am9icG9zdDriqyExynqwKjf8sNeTcE_T ## Job description ## About Babs Babs is building the smart operating system for modern families. Most AI tools are designed for work life, but managing home life is its own full-time job filled with coordination, communication, and constant context switching. Babs acts as a second brain that brings order to everyday life by connecting calendars, tasks, and messages into one intelligent system. Our edge is in our ability to make complex systems feel simple. Our strength is our team — driven, thoughtful builders united by a mission to bring order to everyday life and give people the clarity of an organized mind. Our mission is to give people the power to live organized lives and organized minds. Our vision is to build joyful, connected communities. That begins with creating systems and workflows that help people feel more present and effective in their daily lives. When households run smoothly, they have more capacity to connect, contribute, and strengthen their communities. ## The Role We’re looking for an Founding AI Engineer to design, build, and scale the intelligence layer that powers Babs. You’ll work on the infrastructure that connects large language models, vector databases, and real-world data into a seamless, adaptive system. This role sits at the intersection of machine learning infrastructure, data systems, and applied product engineering. You’ll be responsible for how Babs learns, remembers, and improves — turning context into intelligence and feedback into reinforcement. You’ll help us move from AI-assisted features to a truly AI-native product that feels personal, contextual, and trustworthy. ## What You’ll Do - Design and implement retrieval and memory systems using vector databases and semantic search - Build and maintain RAG pipelines that combine structured and unstructured data - Develop feedback loops and evaluation systems to measure and improve model output quality - Explore reinforcement learning (RL) and fine-tuning approaches that adapt model behavior to user context - Integrate and experiment with multiple LLMs and APIs, choosing the right tool for each task - Collaborate with platform and product engineers to bring intelligence into real features - Create observability and evaluation systems for AI latency, accuracy, and reliability - Contribute to architectural decisions that shape Babs’ long-term AI infrastructure Our Ideal Candidate Has - 4 or more years of experience working with LLMs, machine learning infrastructure, or applied AI systems - Strong experience with Python and frameworks like LangChain, LlamaIndex, or equivalent orchestration tools - Deep understanding of retrieval-augmented generation, embeddings, and vector databases (such as Pinecone, Weaviate, or FAISS) - Familiarity with evaluation frameworks, feedback loops, and reinforcement learning techniques - Experience building and scaling data or ML pipelines in production environments - Curiosity about user behavior and how models can be tuned to better serve real human needs - A thoughtful, practical approach to experimentation and iteration — you ship and learn Bonus Points For - Experience designing model evaluation frameworks or AI Evals - Contributions to open-source AI infrastructure projects - Familiarity with prompt optimization, tool calling, and agentic workflows - Experience with multi-modal models (text, image, or speech) - Knowledge of GCP, Firebase, or event-driven architectures - A background in consumer or productivity products ## Compensation & Benefits - Base salary range: $150,000 – $225,000 and equity, depending on experience and expertise - Competitive compensation package including equity - Comprehensive medical, dental, and vision coverage - Flexible PTO and a work culture built on trust and autonomy - A team that values craftsmanship, collaboration, and purpose over fluff If you’re excited by the idea of building the intelligence layer behind a product that helps people live with more clarity and calm, we’d love to meet you — even if you don’t check every box. We care about curiosity, integrity, and a shared belief in what we’re building. ## About hellobabs.ai ## Company Overview - **One-liner**: Babs is an AI-powered household operating system that proactively extracts events, deadlines, and to-dos from family emails (Gmail) to help parents manage their family’s operational load. - **Entity Type**: Private (Funding stage not publicly disclosed; currently in free private beta) - **Headquarters**: United States (Remote/Hybrid; team also in Belgium) - **Founded**: Not publicly available - **Founders**: Liz Meyerdirk (Founder & CEO) ## Core Business - **Primary industry**: Consumer productivity software / AI-powered personal assistant - **Target customers**: B2C – primarily parents (especially the parent who manages the family’s schedule, communications, and logistics) - **Mission or purpose statement**: “A household is real work – and real work deserves real tools.” Babs aims to give families the same kind of operational systems that corporate enterprises have. ## Products & Services - **[Babs App]**: An AI assistant (iOS, Android, and web) that connects to Gmail with read-only access, scans household emails (school newsletters, activity updates, coach communications, camp confirmations), and automatically surfaces events, deadlines, and action items in a clean feed. Users tap to add to their calendar or to-do list. Builds context over time about family members, schools, activities, and important senders. Type: SaaS / mobile app. ## Market Standing - **Valuation/Market Cap**: Not disclosed - **Key Metric**: Total funding not publicly available; currently free to users (private beta with waitlist) - **Notable Investors/Partners**: Not publicly listed - **Growth Signals**: Small but focused team (4 employees); private beta generating waitlist interest; product addresses a clear pain point for busy families; emphasis on privacy (no data selling, no AI model training on user data) differentiates from larger competitors. ## Competitive Advantages - **Proactive, not reactive**: Unlike chatbots or manual-entry apps, Babs reads emails and extracts actionable items without user input. - **Contextual intelligence**: Builds persistent knowledge about the family (kids, schools, activities, senders) so it improves over time. - **Privacy-first**: Read-only Gmail access; no data sold or used for advertising; third-party AI services contractually prohibited from training on user data. - **Focus on the “operational load” parent**: Designed specifically for the person who coordinates the household, not a generic calendar or task app. ## Strategic Focus - **Current priorities**: Building a product worth paying for before monetizing; expanding beyond Gmail to other email providers; adding native desktop apps (macOS, Windows); refining AI extraction accuracy and user experience. - **Growth direction**: Word-of-mouth and waitlist-driven; likely to introduce a paid subscription once the product matures. ## Why Work Here - **Culture highlights**: Mission-driven team tackling a real, underserved problem for families; small team (4 people) means high ownership and impact; emphasis on privacy and user trust. - **Remote/hybrid policy**: Hybrid workspace (employees engage in a combination of remote and on-site work; typical time on-site not specified). Team distributed across United States and Belgium. - **Notable perks or engineering culture**: Early-stage environment with opportunity to shape product and culture; focus on building thoughtful, user-respecting AI. ## Sources 1. [hellobabs.ai/careers](https://www.hellobabs.ai/careers) 2. [hellobabs.ai/about](https://www.hellobabs.ai/about) 3. [hellobabs.ai/faq](https://www.hellobabs.ai/faq) 4. [linkedin.com/company/hello-babs](https://linkedin.com/company/hello-babs) 5. [builtin.com/company/babs-ai](https://builtin.com/company/babs-ai) ## Other roles at hellobabs.ai - [Founding Full Stack Product Engineer](https://feeny.ai/job/founding-full-stack-product-engineer-hellobabs-ai-san-francisco-avv5tssnjb0b) — San Francisco, CA