Pear VC

You will lead key pieces of product design, including creating wireframes, prototypes, and polished UI. Additionally, you will work on landing pages, user dashboards, and technical documentation. | We are looking for a designer with good taste, clear thinking, and a bias to ship. Comfort with Figma and the ability to explain design choices in plain language are essential. | We’re looking for a hands-on designer to lead key pieces of our product. This role is in person, 5 days/week in San Francisco with the potential of contract to full-time hire. Rate: $50–$100/hr All levels of experience are encouraged to apply. What you’ll work on Product UI/UX — wireframes → prototypes → polished UI Landing page — clear story, strong visuals User dashboard — simple, data-friendly layout Technical docs — clean architecture and readable components What we’re looking for Good taste, clear thinking, and a bias to ship Comfortable in Figma (auto-layout, components, basic prototyping) Can explain design choices in plain language Portfolio or samples required — class and internships projects are ok About us Growl is a contextual ad engine that personalizes chat content to serve the right creative at the right moment. Janak — MIT B.S./M.S.; built grid-scale AI at AutoGrid (acquired by Schneider Electric) Sahil — Published researcher; led AI infrastructure at Google and Microsoft. We have raised $3.5+ million from top tier VC (Pear and Audacious ventures). How to apply: Email your portfolio link to hello@withgrowl.com with subject “Product Designer — SF.” Include your availability and a sentence on the project you’re proudest of.

Design, build, and scale AWS-based infrastructure and data pipelines supporting AI-driven features including data ingestion, orchestration, and observability. | 4+ years in platform or data engineering with proficiency in Python, Bash, YAML, containerization, cloud architecture, infra-as-code, and exposure to ML/AI workflows. | About the role You’ll own the foundation of Known’s product infrastructure across mobile, web, and agentic AI systems. From data pipelines to cloud infra, you’ll design, build, and scale the platform that powers matching, voice, and scheduling features. Responsibilities Design and manage AWS-based infrastructure, codified in Terraform. Build and maintain data ingestion/orchestration pipelines (Airflow, Dagster, or equivalent). Administer and optimize PostgreSQL (with pgvector) and data warehouse environments. Support data modeling and schema design for user profiles, matching, and conversation logs. Collaborate with AI/ML engineers to productionize models (training, inference, monitoring). Implement observability (logging, metrics, alerts) across the stack. Requirements 4+ years in platform, infra, or data engineering. Proficiency in Python, Bash, YAML; experience with containerization (Docker, Kubernetes). Strong knowledge of cloud architecture, data pipelines, and infra-as-code. Exposure to ML/AI workflows and feature stores a plus. Example Projects Stand up a data lake + warehouse for storing structured behavioral signals. Build ingestion from app + third-party APIs (e.g. Stripe, OpenAI, Twilio). Scale infra for real-time voice agent calls and user profile matching.

Design, build, and scale AWS-based infrastructure and data pipelines, support data modeling, collaborate with AI/ML engineers, and implement observability across the stack. | 4+ years in platform, infrastructure, or data engineering with proficiency in Python, Bash, YAML, containerization, cloud architecture, and infra-as-code; ML/AI workflow exposure is a plus. | About the role You’ll own the foundation of Known’s product infrastructure across mobile, web, and agentic AI systems. From data pipelines to cloud infra, you’ll design, build, and scale the platform that powers matching, voice, and scheduling features. Responsibilities • Design and manage AWS-based infrastructure, codified in Terraform. • Build and maintain data ingestion/orchestration pipelines (Airflow, Dagster, or equivalent). • Administer and optimize PostgreSQL (with pgvector) and data warehouse environments. • Support data modeling and schema design for user profiles, matching, and conversation logs. • Collaborate with AI/ML engineers to productionize models (training, inference, monitoring). • Implement observability (logging, metrics, alerts) across the stack. Requirements • 4+ years in platform, infra, or data engineering. • Proficiency in Python, Bash, YAML; experience with containerization (Docker, Kubernetes). • Strong knowledge of cloud architecture, data pipelines, and infra-as-code. • Exposure to ML/AI workflows and feature stores a plus. Example Projects • Stand up a data lake + warehouse for storing structured behavioral signals. • Build ingestion from app + third-party APIs (e.g. Stripe, OpenAI, Twilio). • Scale infra for real-time voice agent calls and user profile matching.

Design, build, and scale AWS infrastructure and data pipelines, administer PostgreSQL and data warehouses, collaborate with AI/ML teams, and implement observability. | 4+ years in platform or infra engineering, proficiency in Python, Bash, YAML, containerization, cloud architecture, infra-as-code, and exposure to ML/AI workflows. | 🚀 Infra / Platform Engineer About the role You’ll own the foundation of Known’s product infrastructure across mobile, web, and agentic AI systems. From data pipelines to cloud infra, you’ll design, build, and scale the platform that powers matching, voice, and scheduling features. Responsibilities Design and manage AWS-based infrastructure, codified in Terraform. Build and maintain data ingestion/orchestration pipelines (Airflow, Dagster, or equivalent). Administer and optimize PostgreSQL (with pgvector) and data warehouse environments. Support data modeling and schema design for user profiles, matching, and conversation logs. Collaborate with AI/ML engineers to productionize models (training, inference, monitoring). Implement observability (logging, metrics, alerts) across the stack. Requirements 4+ years in platform, infra, or data engineering. Proficiency in Python, Bash, YAML; experience with containerization (Docker, Kubernetes). Strong knowledge of cloud architecture, data pipelines, and infra-as-code. Exposure to ML/AI workflows and feature stores a plus. Example Projects Stand up a data lake + warehouse for storing structured behavioral signals. Build ingestion from app + third-party APIs (e.g. Stripe, OpenAI, Twilio). Scale infra for real-time voice agent calls and user profile matching.

Build and iterate on mobile features with React Native, maintain backend APIs in Node.js/TypeScript, integrate third-party APIs, contribute to React frontend components, and collaborate with AI/ML engineers. | 4+ years as fullstack or frontend/backend engineer with strong TypeScript, React, React Native, Node.js skills, API design and integration experience, and a startup mindset. | About the role You’ll work across the Known product surface: mobile features, web backend, and API integrations. You’ll ship quickly, leverage AI coding tools (e.g. Cursor, Copilot), and help us deliver a polished, consumer-grade experience. Responsibilities Build and iterate on mobile features with React Native. Extend and maintain backend APIs in Node.js/TypeScript. Integrate with third-party APIs (OpenAI/Anthropic, reservations, payments, messaging). Contribute to frontend components in React (web app). Collaborate with AI/ML engineers to expose model-powered features via APIs/UI. Requirements 4+ years as a fullstack or frontend/backend engineer. Strong with TypeScript, React, React Native, Node.js. Experience with API design, integration, and scaling. Startup mindset: comfortable working across the stack and learning fast. Example Projects Build mobile onboarding flow with AI-assisted profile setup. Integrate payments and reservations APIs for seamless date planning. Create personalized UI components powered by ML model outputs.

As a Software Engineer at Advex, you will build the core product and scale the platform for large companies. You will also contribute to the architectural roadmap, laying the foundation for the Advex platform. | Candidates should have 2 to 5 years of industry experience in full stack and deep learning, with a proven track record of delivering complex projects. Experience in end-to-end ML application development is essential, and prior startup experience is a bonus. | Job Overview At Advex, we're working on solving the hardest problem in all of deep learning – data collection. In order to train a reliable AI model, you need access to the right training data. The inability to gather the right data has been the primary obstacle in global adoption of computer vision in mission critical industries like manufacturing and industrial automation. At Advex, we've reimagined a new way to develop AI models by transforming generative models into data agents. Our technology improves model performance by 300%+ for our Fortune 500 customers in just a few hours! About Us Advex is a seed stage tech startup backed by Construct Capital, PearVC, and the founders of Dropbox and Gradient Ventures. Our team comes with over a decade of industry and research experience from top organizations and labs like Caltech, Berkeley AI Research Lab, Google Brain, Waymo, and Qualcomm. Role Description As a SWE at Advex, you will play a pivotal role in shaping the company's technical direction. Your hands-on involvement will include working with our team to (1) build our core product and scale our platform into the hands of some of the largest companies in the world (2) contribute heavily to the architectural roadmap, laying out the foundation for the Advex platform. Tech Stack: React, TypeScript Python, Rust We are looking for individuals who can lead, are autonomous, and can make decisions with limited information. About You We are seeking a candidate who embodies the following qualifications and characteristics: 2 to 5 years of industry experience in full stack and deep learning Experiences in end to end ML application development, including data engineering, model tuning, and model serving Prior experience working at a startup (bonus) Deep Learning expertise includes (bonus) Computer vision Diffusion Proven track record of rapidly delivering complex project within tight deadlines Our Values Extreme Ownership – Own your piece to an unreasonable level – if that piece succeeds or fails, for whatever reason, the buck stops with you. Fierce Velocity – Rome was not built in a day, but they were laying bricks every hour. The Best Part is No Part – Simplicity over complexity. Be Epsilon Greedy – Greatness cannot always be planned; be willing to explore novel ideas even if things don’t work out. Customer Obsessed – Our customers are the backbone of humanity. It is our duty to improve and make them better in order to exponentially improve the lives of billions of people. Feedback is the breakfast of champions – Embrace feedback. A healthy team is one where constructive feedback is welcomed and expected. Argmax (team) – The only way to win is together! One Team. One dream. Note: we are a company founded by immigrants, and we are committed to providing support to immigrant workers throughout their journey. This includes offering assistance to international students and workers with various types of visas, such as OPT, H1, EB, and more.

Collaborate with structural engineers to build a system for building data collection and reasoning, develop a large geospatial database, write and review code, support technical integrations and customers. | 5+ years catastrophe modeling experience or PhD, structural engineering or risk analysis background, Python programming, database knowledge, strong communication skills, and ability to work onsite in San Francisco Bay Area. | About Us: Rising disasters—from earthquakes to wildfires—are destabilizing the property insurance market, yet carriers often rely on outdated, incomplete data. ResiQuant is changing that. Founded by Stanford PhDs and backed by a $4M seed round led by LDV Capital, we fuse structural engineering with advanced, agentic AI to expose critical vulnerabilities that standard sources miss. Our multi-hazard platform delivers building-level insights so insurers across the U.S. can underwrite disaster-exposed properties with confidence, maintain coverage in high-risk regions, and reward resilience where it matters most— paving the way for a safer, more sustainable future. About You: We're seeking an individual who is passionate about the mission of the company to join us as Catastrophe Engineer with focus on disaster exposure. We prize candidates who share our company's vision and are ready to help foster an inclusive and collaborative culture. As a lean seed startup, we need someone with a scrappy, hands-on approach, eager to evolve alongside our team, and support the company in all stages of growth. The ideal candidate is excited to apply their knowledge in catastrophe modeling, data science, and software development, to shape the trajectory of a groundbreaking company. Qualifications: • 5+ years of experience with the major catastrophe models used by insurance companies (RMS and Verisk) for hurricane, earthquake, severe convective storm, and wildfire modeling. OR PhD in relevant field. • Technical understanding about why buildings survive or fail during hurricanes and wildfires. • Understanding of statistical concepts and practical experience applying them (in A|B testing, causal inference, ML, etc.). • Experience in programming/modeling in Python. • Knowledge of database systems. • Background in structural engineering and/or risk analysis. What will make you stand out: • Proficiency/Experience in software development. • Proficiency/Experience working with multimodal data sources (e.g., voice, imagery, text) for AI model training. • Proficiency/Experience collecting and interpreting data from interviews. • Experience using Multi-modal LLMs. What drives us: • Impact: we are driven by a shared mission to address a paramount challenge of our time • Resolve: we believe that hard work and resilience yield extraordinary outcomes • Urgency: we are motivated to outpace rapid urbanization and escalating disaster impacts Why join RQ: • Opportunity to be involved in an early-stage startup and build the culture you want to see. Chance to pioneer and disrupt the $200B property insurance industry • Experience firsthand the tangible impact of what you build. Day to day: • Collaborate with experienced structural engineers in building a system that collects data and reasons about buildings as a structural engineer • Participate in product ideation and development. • Architect and develop a large geospatial database to host multimodal building data and context that will grow over time. • Write, test, document, and review code according to RQ’s development standards that you would help to define. • Support the founders in technical integrations with customer systems • Support customers using the ResiQuant platform and handle domain specific questions What we offer: • Competitive salary commensurate with experience • Equity in the company as a founding member • Vibrant tech startup environment • Competitive company 401(k) program with company matching • Health insurance • Working on the challenge of our generation with other passionate people Ideal Engineer Profile • Location: San Francisco Bay Area (In person) • Bachelors: Civil or Mechanical Engineering, or Math with relevant experience • Masters: Structural engineering, Risk Analysis, or Catastrophe modeling. • Experience in catastrophe modeling using RMS and/or Verisk models for most perils • Experience managing large data set of building and associated data • Experience in programming and data analysis with Python • Persistence and adaptability working through setbacks and change of directions. • Skilled at delegating tasks while staying hands-on with critical development. • Excellent written and verbal communication skills, with the ability to convey complex ideas clearly to diverse audiences.