Backend Engineer at Known | San Francisco

Join Known as a Founding Machine Learning EngineerLocation: San Francisco, CA (In-Person)Salary: $200,000 - $375,000 Cash + EquityAt Known, we are revolutionizing the way people connect by utilizing advanced AI technology. Our mission is to enhance human relationships through intelligent matchmaking.Users engage with our AI voice assistant, sharing their per…

Join Known as a Founding Product Operations SpecialistLocation: San Francisco, CA (In-Person)Salary: $120,000 - $150,000 + EquityAt Known, we are revolutionizing the way people connect. Our mission is to empower humanity through the application of general intelligence to human relationships.Our users share their life stories with us, engaging with our AI voice agent for an average of 27 minutes, providing intimate insights that enhance our matchmaking process.Our talented team comprises engineers who have developed renowned AI-driven consumer products, including Uber Eats, Uber, and Afterpay.We embrace a culture of hard work, autonomy, and ownership, collaborating in our Cow Hollow office in San Francisco.Role OverviewWe are in search of exceptional product thinkers to take charge of Known’s product experience. Our goal is to become the Apple of dating, striving for a best-in-class user experience. You will work directly with the founders to craft transformative user interactions that positively impact lives.Your ResponsibilitiesYou will have the autonomy to own specific aspects of Known’s user experience based on your interests.Your focus may include:Collaborating with founders and engineering to implement user feedbackExperimenting with notifications and strategies for user retentionManaging user metrics, including onboarding, date conversion, and retention ratesDeveloping Human-In-The-Loop processes for waitlist approvals and matchmakingConducting QA for new app buildsCoordinating app store submissions and reviewsAt Known, you’ll be contributing to building connections that could lead to countless marriages and families.Our InvestorsWe are proudly backed by Eurie Kim and Kirsten Green at Forerunner Ventures (investors behind Decagon, Faire, and Oura), NFX, and PearVC.

Join Known as a Founding Product EngineerLocation: San Francisco, CA (In-Person)Compensation: $150,000 - $200,000 + EquityAt Known, we're redefining how humans connect by utilizing advanced AI technology. Our mission is to enrich lives by fostering authentic connections, guided by the stories our users share.Our users engage deeply with our AI voice agent, averaging 27 minutes of conversation, allowing us to gather profound insights into their lives.Our engineering team consists of innovators who have previously developed some of the most popular AI-driven consumer products such as Uber, Uber Eats, Afterpay, and Cash App.We thrive in a collaborative in-person environment located in Cow Hollow, San Francisco, where hard work and autonomy are highly valued.About the RoleWe are in search of exceptional product engineers to further enhance the Known mobile application. Your role will involve a strong design focus as we aim to be the Apple of dating. Our engineers are meticulous artisans dedicated to quality, as we prioritize a product that is both intentional and distinctly human-centered.You may be a great fit if youHave a primary focus as a React Native engineerHave experience building products with intricate audio and voice functionalitiesAspire to create technology that facilitates a million marriagesExhibit a high level of attention to detailOur InvestorsWe are proudly backed by renowned investors including Eurie Kim and Kirsten Green from Forerunner Ventures (the minds behind Decagon, Faire, and Oura), as well as NFX and PearVC.

About AbacusAt Abacus, we are revolutionizing the operations of accounting firms through innovative AI agents that automate the monotonous and repetitive tasks currently faced by teams. Our cutting-edge core engine integrates advanced Optical Character Recognition (OCR) and Large Language Models (LLMs) to provide genuinely intelligent back-office automation solutions. We have already established partnerships with significant enterprise clients, generating substantial revenue, and are proudly supported by leading investors. Having achieved this milestone as a compact team of two, we are eager to expand our workforce. If you are passionate about shaping the future of AI-driven operations and are ready to take on impactful technical challenges from the outset, this is your opportunity.The RoleWe are seeking our inaugural Founding Engineer to take charge of and enhance the core machine learning engine that powers Abacus. Reporting directly to the co-founders, you will work on-site from our San Francisco office. This is a unique chance to join a rapidly growing company as an early engineer, endowed with significant autonomy and influence over both product and technical direction.In your first 3–6 months, you will:Enhance and scale our ML extraction engine utilizing LLMs and OCR technologies.Take ownership of backend architecture and infrastructure decisions.Develop and launch innovative features that broaden the scope of automated workflows.In the following year, you will play a pivotal role in establishing the foundation of our engineering organization as we scale, while remaining hands-on and focused on delivering impactful results.What You’ll DoLead the development of our machine learning-driven document extraction engine.Architect backend systems with an emphasis on performance and scalability.Create and deploy new automation features tailored for tax firms.Work closely with the founders to align on product and user requirements.Contribute to defining our engineering culture and establishing the technical roadmap.What We're Looking ForEssential Qualifications:1–5 years of experience, preferably in environments with high ownership or early-stage ventures.Proficient backend development skills, especially in Python.Demonstrated ability as a 0→1 builder, whether through side projects, startup experience, or both.Commitment to work from our SF office, five days a week.Willingness to complete a technical assessment as part of the application process.

Founding Machine Learning EngineerLocation: San Francisco, CA Work Model: In-office 5 days a weekAbout UsAt Effective AI, we are pioneering the future of work. Our vision is to push the boundaries of AI beyond mere repetitive tasks, focusing instead on intricate knowledge work that requires expertise and multi-faceted reasoning. We are developing advanced AI Teammates that are designed to navigate complex workflows and collaborate seamlessly with human professionals. Our initial focus is on the trillion-dollar U.S. Property & Casualty insurance sector, a domain rich with complexity and data, making it an ideal arena for our innovations.We proudly secured $10 million in seed funding from prominent investors including Lightspeed Ventures and Valor Equity Partners.Our committed team is based in San Francisco and thrives on in-person collaboration to tackle these significant challenges.Your RoleAs a Founding Machine Learning Engineer, you will be an integral member of our founding team, responsible for architecting, training, and deploying the agent loops that power our AI Teammates from inception. You will address some of the most pressing challenges in agentic AI and natural language processing, developing AI solutions adept at performing essential insurance functions such as underwriting and claims processing.Your responsibilities will include:Architecting and Developing Core ML Pipelines: Design, train, and fine-tune cutting-edge language models (including reinforcement learning agents) to facilitate long-term task accomplishment and complex decision-making.Implementing Nuanced Reasoning: Integrate machine learning techniques that empower agents to make informed decisions based on ambiguous or incomplete data, akin to human expert reasoning and generalization.Building Intelligent, Tool-Using Agents: Engineer the ML systems that enable our agents to dynamically select and utilize a broad array of external tools—including APIs, databases, web searches, and Excel-based pricing algorithms—to gather necessary information and execute actions.Designing and Implementing Robust Evaluation Frameworks: Create and employ comprehensive evaluation metrics and systems to rigorously assess and benchmark agent performance, identify areas for enhancement, and guarantee reliability and safety in real-world insurance processes.Enabling Continuous Adaptation and Learning: Develop resilient ML pipelines and feedback loops that facilitate ongoing learning and adaptation.

Join tvScientific as a Machine Learning Engineer where you will leverage cutting-edge machine learning techniques to enhance our advertising platform. You will be responsible for developing and optimizing algorithms that drive effective ad targeting and analytics. Collaborate with cross-functional teams to integrate machine learning solutions that improve user engagement and maximize return on investment for our clients.

About Pax HistoriaPax Historia is pioneering a new genre of gameplay by leveraging cutting-edge generative AI technologies. Our innovative platform combines the strategic depth of grand strategy games with the limitless creativity of a sandbox environment, driven by a vibrant community that actively creates and modifies scenarios.Our user base generates hundreds of scenarios daily and engages in millions of game rounds each week, exhibiting rapid growth. We are proud to be supported by esteemed investors such as Y Combinator, Pace Capital, and Z Fellows. Your contributions will have an immediate impact on a product enjoyed by hundreds of thousands of players.Position OverviewWe are seeking a founding-level ML Systems Engineer to join our team in-person full-time in San Francisco (Dogpatch). You will have the opportunity to work closely with our cofounders to shape the future of our technology.Current Challenges:Closed-source models yield satisfactory game performance but come with high costs.Open-source models are more budget-friendly yet often underperform in our environment.Prompts and harnesses exhibit minimal variance across models.We have a functional internal evaluation system with significant opportunities for enhancement.Your Responsibilities:Establish and manage the necessary infrastructure for customizing harnesses and prompts tailored to individual AI models to optimize their performance.Develop domain-specific models aimed at narrowing or completely bridging the gap in performance between open and closed models.Optimize caching strategies to decrease expenses associated with closed-source models.Enhance the performance of closed-source models by training specialized endpoints.Assess and advance the effectiveness of embedding and reranking mechanisms in our applications.Facilitate the creation of new user experiences based on emerging world models.In Summary: Your work will directly enhance the affordability and enjoyment of the game.

About PoesisPoesis is a pioneering AI-native investment manager that is transforming the landscape of U.S. equities through innovative foundation models. We are developing cutting-edge AI systems designed to predict market trends and exceed the performance of traditional investment managers. This exciting work represents frontier research that is validated in real-world scenarios. Your contributions will play a crucial role in influencing investment strategies and enhancing portfolio outcomes.Location & WorkstyleLocated in the vibrant San Francisco Bay Area, near Stanford, we support a Hybrid work model, requiring several days on-site each week.Relocation assistance is available.About the RoleAs a Founding Machine Learning Engineer, you will be the first full-time ML hire at Poesis, responsible for translating research and data into scalable production models. You will develop the initial ML pipelines from the ground up, managing everything from data ingestion and preprocessing to model training, validation, and signal generation. This role is ideal for a hands-on professional who excels in coding, designing experiments, and quickly delivering validated results.You will collaborate closely with the CEO and Chief Scientist, taking ownership of both the implementation process and iterative improvements. As the system scales, you will help transition it into a full production platform and establish best practices for future team members.ResponsibilitiesDesign, develop, and maintain the foundational ML infrastructure for Poesis’ investment platform.Create reproducible pipelines for data ingestion, feature engineering, and model training.Establish backtesting and evaluation frameworks with defined performance metrics.Provide regular, detailed reports on model accuracy, feature significance, and overall portfolio impact.Work closely with the Chief Scientist to refine model hypotheses and assess production readiness.Ensure high code quality through version control, testing, reproducibility, and thorough documentation.Develop robust backtesting frameworks and model validation tools, incorporating walk-forward evaluation and risk management controls.Integrate with leading financial data providers such as Bloomberg, FactSet, Refinitiv, and CapIQ.Implement foundational MLOps practices, including model versioning, CI/CD, monitoring, and documentation.Define and refine “demo-able” workflows that link model outputs to investment decision-makers.

tvScientific seeks a Machine Learning Platform Engineer to help shape the company’s advertising technology. This position can be based in San Francisco, CA, or performed remotely from anywhere in the United States. Role overview This role focuses on building and refining machine learning models that drive the core of tvScientific’s advertising platform. The work combines technical skill with creative problem-solving to support the platform’s effectiveness. What you will do Develop and optimize machine learning models to enhance advertising performance Collaborate with team members to deliver solutions that balance innovation, scalability, and reliability Apply technical expertise to address challenges at the intersection of technology and creative thinking Location Candidates may work from San Francisco, CA, or remotely within the US.

About Taskrabbit:Taskrabbit is an innovative marketplace platform that seamlessly connects individuals with Taskers to manage everyday home tasks, including furniture assembly, handyman services, moving assistance, and much more.At Taskrabbit, we aim to transform lives one task at a time. We celebrate innovation, inclusion, and hard work, fostering a collaborative, pragmatic, and fast-paced culture. We seek talented, entrepreneurially minded, data-driven individuals who possess a passion for empowering others to pursue their passions. In partnership with IKEA, we are creating more opportunities for individuals to earn a consistent, meaningful income on their terms by establishing enduring relationships with clients in communities globally.Taskrabbit operates as a hybrid company, with team members located across the US and EU, and has been recognized as a Built In — Best Places to Work for 2022, 2023, and 2024, receiving accolades across various national and regional categories. Join us at Taskrabbit, where your contributions will be significant, your ideas appreciated, and your potential maximized!This position operates on a hybrid schedule, requiring two days of in-office collaboration per week. It can be based in our San Francisco office or our new New York City office (opening March 2026).About the RoleMachine Learning is a foundational element at Taskrabbit, and we are in search of an experienced Senior Machine Learning Engineer to join our team and help mold the future of ML/AI at Taskrabbit. This distinct, full-stack role is designed for someone who is enthusiastic about the entire machine learning lifecycle—from initial research and model development to constructing the robust infrastructure necessary for deploying and scaling your innovations.As a Senior Machine Learning Engineer, you will engage with exciting challenges that directly influence how users discover and interact with home services on the Taskrabbit platform. You will play a vital role in enhancing our capabilities in areas such as search ranking, content discovery, and recommendation systems. Collaborating closely with data scientists and fellow engineers, you will design and implement cutting-edge algorithms, ensuring the scalability, reliability, and optimization of our models in production alongside software engineers.

About VSCO At VSCO, we empower photographers with an innovative platform that provides essential tools, a vibrant community, and the visibility needed for creative and professional growth. We cultivate an authentic creative environment that welcomes photographers of all skill levels, offering a space that inspires opportunity, collaboration, and connection. Our mission is to support photographers in their journeys, enabling them to thrive and connect with fellow creatives and businesses through our comprehensive suite of tools, available on both mobile and desktop. We seek individuals who are passionate and proactive in advancing our mission. Our team members have the opportunity to make a significant impact, and we believe that collaborative efforts yield stronger results. Our core values are essential to our team culture and guide our hiring process. Learn more about what you can expect when joining VSCO on our Careers Page. About The Role As a Senior Machine Learning Engineer, you will harness the power of AI and machine learning to create innovative, reliable user-facing product features. You will leverage your extensive technical background and hands-on experience in deploying machine learning models to deliver impactful solutions based on real-world feedback. Your focus on measurable outcomes and customer satisfaction drives your work, blending innovation with practical implementation. You will be highly skilled in Python and adept across the data and machine learning stack, enabling you to develop and launch models efficiently while ensuring scalability and maintainability. Whether working with traditional algorithms or cutting-edge deep learning and generative AI, you will expertly navigate the complexity of each problem, managing every phase from defining the challenge to deployment and iterative improvement. Your dedication to software engineering excellence will inform your thoughtful approach to system design for machine learning, encompassing data quality, pipeline design, feature workflows, model serving, and ongoing monitoring and enhancement. By integrating machine learning deeply within our cohesive product experiences, you will collaborate effectively with cross-functional teams, aligning on objectives, defining success metrics, and driving meaningful outcomes. You will stay informed about the rapidly evolving AI landscape, maintaining a discerning perspective that allows your team to focus on significant advancements while avoiding distractions. The Day to Day Design and implement ML-powered features for search, discovery, personalization, and more.

Job OverviewJoin Eragon as a Machine Learning Engineer and lead the charge in transforming innovative AI models into scalable, production-grade systems. This position is pivotal in bridging research and real-world applications by designing and optimizing systems that enhance vital workflows throughout the enterprise.In collaboration with our research, product, and engineering teams, you will convert cutting-edge capabilities into dependable, high-performance systems ready for production.Key ResponsibilitiesModel Development & Deployment: Craft, refine, and deploy machine learning models within production settings.Systems Engineering: Architect scalable pipelines for training, inference, evaluation, and comprehensive monitoring.Performance Optimization: Enhance the latency, throughput, cost-efficiency, and reliability of ML systems.Data & Infrastructure: Manipulate large datasets and ensure seamless integration of models with internal systems and APIs.Cross-Functional Collaboration: Collaborate with product and engineering teams to provide end-to-end AI functionalities.Evaluation & Monitoring: Develop robust evaluation frameworks and feedback loops to ensure system effectiveness.

At Sciforium, we are pioneering the future of AI infrastructure by creating cutting-edge multimodal AI models and a proprietary, high-efficiency serving platform. With substantial financial backing and direct support from AMD engineers, our team is rapidly expanding as we develop the comprehensive stack that drives advanced AI models and real-time applications.About the RoleIn the capacity of a Machine Learning Engineer, you will engage with the entire foundation-model stack, encompassing pretraining and scaling, post-training and Reinforcement Learning, sandbox environments for evaluation and agentic learning, and deployment + inference optimization. You’ll have the opportunity to rapidly iterate on research ideas, contribute to production-grade infrastructure, and help deliver models capable of addressing real-world challenges at scale.Your ResponsibilitiesThis position offers diverse tracks - candidates can specialize or contribute across multiple areas. Key responsibilities include:Pretraining & ScalingTrain expansive byte-native foundation models utilizing vast, heterogeneous data sources.Formulate stable training methodologies and scaling laws tailored for innovative architectures.Enhance throughput, memory efficiency, and resource utilization across extensive GPU clusters.Establish and maintain distributed training infrastructures alongside fault-tolerant pipelines.Post-training & Reinforcement LearningBuild out post-training frameworks (SFT, preference optimization, RLHF/RLAIF, RL).Curate and produce specialized datasets aimed at enhancing specific model capabilities.Develop reward models and evaluation systems to facilitate ongoing improvements.Investigate inference-time learning and computational strategies to boost performance.Sandbox Environments & EvaluationCreate scalable sandbox environments for agent assessment and learning.Generate realistic, high-signal automated evaluations for reasoning, tool usage, and safety.Design both offline and online environments that support RL-style training at scale.Implement instrumentation for observability, reproducibility, and rapid iteration.Deployment & Inference OptimizationOptimize deployment strategies to ensure models are efficient and effective in real-world applications.

Join Strava, a leader in the sports technology sector, as a Machine Learning Engineer. In this exciting role, you will apply your expertise in machine learning and data science to develop innovative solutions that enhance the experience of millions of athletes worldwide. Collaborate with cross-functional teams to create algorithms that analyze vast datasets and provide actionable insights to our users.

At Lyft, we are driven by our mission to connect and serve our communities. We strive to foster a workplace where every team member feels valued and has the opportunity to excel. With over half a billion rides and counting, Lyft is tackling complex challenges on a grand scale, utilizing cutting-edge AI and Machine Learning technologies to enhance customer experiences. The Artificial Intelligence, Machine Learning, and Operations Research Platforms team (AIMLOR) is on the lookout for a Senior Machine Learning Engineer who will play a pivotal role in constructing AI Platform components that empower essential AI applications across Lyft. Mastery in Generative AI and platform development is crucial for this position. You will contribute to our platform that facilitates real-time, online, and offline AI and ML model execution, development, and iteration. Collaborating with a team of talented Machine Learning and Software Engineers, you will work on intricate problems and define solutions that make a direct impact on our systems throughout the organization. If you are enthusiastic about building an AI Platform at scale with applications spanning every aspect of our company, we want to hear from you. If you are a creative thinker with a strong background in AI and machine learning systems and are passionate about leveraging data to solve business challenges in a dynamic, innovative, and collaborative environment, we invite you to apply.

Join Reducto as a Machine Learning EngineerAt Reducto, we empower AI teams to harness real-world enterprise data with unparalleled precision.Much of the enterprise data—ranging from financial documents to healthcare records—remains trapped in unstructured formats such as PDFs and spreadsheets. Our vision models are designed to interpret these documents in a human-like manner, enabling the development of innovative products, training of machine learning models, and automation of processes on a large scale.Our rapid growth is a testament to our success, having achieved a staggering 7x year-over-year revenue increase, collaborating with numerous companies from prominent AI teams like Harvey, Vanta, and Scale to major enterprises including FAANG and leading trading firms.With over $100 million raised from esteemed investors such as A16z, Benchmark, and First Round Capital, we are on the lookout for a talented Machine Learning Engineer to assist in training and deploying models crucial for our core product's success.

About the RoleJoin us as a technical pioneer as we develop the machine learning and AI infrastructure that powers Known, an innovative dating platform that merges psychology, data analytics, and conversational AI. Your mission will be to create and deploy systems that deliver a truly magical experience—transforming how users find meaningful connections through personalized matching algorithms, adaptive recommendation systems, and engaging natural voice interactions.Collaborating closely with our founding team across product, platform, and design, you will play a crucial role in establishing the data and ML foundations that set Known apart from the competition. This hands-on position demands ownership of the research, prototyping, and production deployment processes.

About LightfieldLightfield is an innovative, AI-powered CRM that seamlessly integrates with your email, calendar, and meetings. It captures every interaction and transforms it into organized context, including accounts, tasks, follow-ups, and valuable insights, ensuring that nothing is overlooked.We are fundamentally reimagining CRM by focusing on the actual workflows of teams rather than imposing rigid systems. Lightfield learns from real-world usage, automating processes and surfacing insights that drive business growth. We’re creating the CRM platform we’ve always envisioned: fast, intelligent, and genuinely supportive.Supported by notable investors such as Greylock, Lightspeed, and Coatue, our team has a rich background, having previously developed Tome, a generative AI presentation tool utilized by over 25 million users. Many of us have experience with leading companies such as Llama, Instagram, Facebook Messenger, Pinterest, Google, and Salesforce.About the RoleAs a key member of Lightfield's AI/ML team, you will play a vital role in crafting the core experiences of our product, developing cutting-edge applications that delight our customers.Currently, our focus is on building a powerful, domain-specific AI that surpasses generic LLMs.We thrive on the challenge of creating groundbreaking AI products for professionals engaged in serious work, and we are eager to expand our AI/ML team to meet these ambitious goals.What You'll DoDevelop and deliver exceptional, unique AI experiences that sales teams will be excited to use.Collaborate with founders and executives to shape Lightfield's AI/ML strategy.Identify user needs suitable for AI/ML solutions, articulate challenges, and work closely with product leaders to devise solutions.Prototype innovative, LLM-powered experiences and guide their development into reliable product features.Contribute to building a world-class AI/ML engineering team through recruitment and mentorship.Who You ArePossess a BS or MS degree in Computer Science, Artificial Intelligence, or Applied Mathematics.Have over 5 years of experience in developing AI/ML products, particularly in Natural Language Processing (NLP).Demonstrate a solid understanding of deep learning AI/ML frameworks and cloud services.Bring hands-on experience in ML Operations (ML Ops).Bonus PointsExperience leading AI/ML product initiatives...

Machine Learning EngineerJoin our client, a pioneering company dedicated to developing state-of-the-art non-invasive technology for brain interfacing. They are at the forefront of creating an innovative ultrasound-based platform that not only stimulates but also images brain activity with unmatched precision and depth, paving the way for groundbreaking advancements in neurological treatments and health research.This integrated approach combines cutting-edge hardware, sophisticated real-time software systems, and applied neuroscience to produce scalable solutions that can enhance lives on a global scale.We are looking for a skilled Machine Learning Engineer to play a crucial role in designing and implementing the essential algorithms that will facilitate precise imaging and targeting of brain activity through ultrasound systems.