Founding Machine Learning Engineer at Poesis | San Francisco

About Stand Insurance Stand Insurance is rethinking how property risks are understood and managed. By combining advanced physics with artificial intelligence, the team models catastrophic risks at the asset level and automates underwriting and risk mitigation before losses happen. Instead of simply delivering insurance, Stand builds a scalable risk engine that aims to deliver real-world impact and stay in markets where others exit. Traditional property insurance often relies on outdated data and manual workflows, accepting damage as a given. Stand takes a different path: simulating real-world catastrophes for individual properties, turning those simulations into actionable steps, and automating operations around those insights. The result is a platform that can underwrite risks others avoid, while reducing operational friction. Role Overview: Machine Learning Engineer – Data Pipeline This role centers on building and maintaining the tools behind Stand’s data annotation pipeline. Areas of focus include computer vision, human-in-the-loop management, quality assurance, and economic optimization. The main goal: increase automation and lower cost-per-policy, while keeping quality high. Early on, work will involve hands-on management of the pipeline, quality checks, and close coordination with the annotation team. As experience grows, the focus will shift to developing advanced data science and machine learning systems, especially around quality instrumentation, automated QA, predictive labeling, and computer vision models. Over time, the role will evolve into shaping a systems-driven, automation-focused framework for the entire annotation lifecycle. Key Responsibilities Pipeline Operations and Reliability Monitor and maintain the daily health of the annotation pipeline Set up escalation protocols and frameworks for categorizing failures Lead the transition from manual to automated operations Quality Instrumentation Design validation systems that align with downstream model metrics Develop anomaly detection models for annotation workflows Automate tasks to cut down on manual QA effort Vendor and Annotator Performance Define and track performance metrics for vendors and annotators Location San Francisco

About Atomic SemiAtomic Semi is revolutionizing the semiconductor industry by creating a compact, high-speed semiconductor fabrication facility. Leveraging existing technology and innovative simplifications, we are committed to developing our own tools to enable rapid iteration and continuous improvement.We are assembling a select group of talented, hands-on engineers across various disciplines—mechanical, electrical, hardware, computer, and process engineering. Our mission is to maintain ownership of the entire technological stack, from atomic structures to architectural design. Our optimistic team is dedicated to pushing the boundaries of technology.We believe that smaller, faster, and self-created solutions are superior. Our lab is equipped with advanced 3D printers, diverse microscopes, e-beam writers, and general fabrication tools. If we identify any gaps, we will create the necessary innovations ourselves.Founded by Sam Zeloof and Jim Keller, Atomic Semi combines Sam's garage chip-making expertise with Jim's 40 years of leadership in the semiconductor industry.About the RoleAs a Data & Machine Learning Engineer, you will develop systems that utilize fabrication data to enhance, monitor, and optimize our manufacturing processes. This role primarily involves converting raw data into actionable insights that drive improvements in yield, reliability, and throughput.

Join Matter Intelligence as a Data and Machine Learning Infrastructure Engineer, where you will play a pivotal role in shaping the future of data-driven decision-making. You will be part of a dynamic team focused on building and optimizing infrastructure that supports innovative machine learning applications. Your expertise will help us enhance our data pipelines and ensure seamless integration of machine learning models into production.

Join Hilbert, a pioneering data science-driven growth engine that empowers B2C teams with predictive insights into user behaviors, revenue drivers, and sustainable growth strategies. Our innovative approach compresses lengthy decision-making processes into mere minutes.Trusted by Fortune 10 enterprises and beloved brands like FreshDirect, Blank Street, and Levain Bakery, Hilbert is the backbone of their growth strategies. We are also collaborating with leading AI companies to push the boundaries of what’s possible.We are seeking a talented Data Scientist who possesses a deep understanding of B2C business challenges, develops actionable models using real-world data, and delivers impactful analyses that facilitate significant growth outcomes — all with the initiative and urgency typical of a founder.This is not a role where you simply receive tasks; you will take ownership of problems from start to finish — from problem framing and modeling to measuring impact — for enterprise clients where the stakes are high and feedback is rapid. If you understand the nuances of churn analysis for different sectors, can create effective recommendation systems from sparse data, and can clearly communicate your causal analysis to clients, we want to meet you.ROLE OVERVIEWYou will closely collaborate with the founding team, engineering, product, and go-to-market teams to enhance the data science systems integral to Hilbert. Daily responsibilities include building models, conducting experiments, analyzing data, and producing analyses that influence key decisions. Our focus is B2C, and the challenges we tackle — such as demand forecasting, customer lifecycle management, personalization, and activation — require an individual who can translate business contexts into effective modeling choices. You will thrive in a high-autonomy, high-ambiguity environment where data is often messy, incomplete, or scarce.Key Responsibilities:Develop ML models that enhance core product features: recommendation systems, search relevance, customer segmentation, demand forecasting, and activation optimization.Contribute to configurable, multi-tenant model architectures that adapt to various customer contexts and business needs, avoiding the need for custom solutions for each case.Build effective models using available data — leveraging limited, noisy, or sparse datasets while determining the appropriate level of complexity.Design and implement rigorous A/B tests and recognize when causal inference methods are necessary.

About UsAt XOXO AI, we are at the forefront of innovation, crafting intelligent interfaces that seamlessly integrate into everyday life. As a dynamic research lab comprised of dedicated engineers, designers, and researchers, we tackle unique challenges that extend beyond the workplace.Having achieved significant breakthroughs in infrastructure, architecture, and model layers, we are looking for passionate builders to help us realize our vision through the development of robust interface and application layers.About the RoleWe seek a talented Data/Machine Learning Engineer to establish our data infrastructure and production-ready ML systems, ensuring our product is responsive, dependable, and intelligent. This full-cycle role involves designing high-throughput pipelines, defining resilient data models, and deploying low-latency feature and model serving that can withstand real-world demands.You will collaborate closely with our founders and the early engineering team to transition prototypes into production, transforming complex real-world signals into reliable datasets and real-time functionalities that enhance core product experiences.What You’ll DoDevelop and manage high-throughput batch and streaming pipelines for analytics, training, and product signals.Lead real-time feature pipelines and online feature serving for low-latency inference.Design and oversee dimensional data models, skillfully managing schema evolution to avoid disrupting downstream consumers.Optimize model serving infrastructure to meet stringent latency and reliability service level objectives (SLOs).Establish and enforce event schemas, telemetry standards, and data contracts across multiple teams.Collaborate with engineering, product, and research teams to translate ambiguous product requirements into measurable, sustainable systems.

Join Anthropic as a Machine Learning Systems Engineer within our Encodings and Tokenization team, where you'll play a pivotal role in refining and optimizing our tokenization systems across Pretraining and Finetuning workflows. By bridging the gap between our Pretraining and Finetuning teams, you will help shape the essential infrastructure that enhances how our AI models learn from diverse data. Your contributions will be crucial in ensuring our AI systems remain reliable, interpretable, and steerable, driving forward our mission of developing beneficial AI technologies.

Join Hilberts as a Machine Learning Engineer / Data Scientist in our San Francisco office, where you will leverage cutting-edge technology to drive enterprise-level solutions. You will work collaboratively with cross-functional teams to design, develop, and implement machine learning models that enhance our data-driven decision-making processes.

About NationGraphAt NationGraph, we are revolutionizing the accessibility and usability of public sector data for businesses targeting municipalities, state agencies, educational institutions, and specialized districts. Our advanced data intelligence engine extracts actionable insights from millions of public sector sources, empowering organizations to make informed decisions. Established in 2024, our mission is to democratize information, ensuring that public data is genuinely accessible to everyone. Discover more at nationgraph.comOur TeamComprises seasoned entrepreneurs who have successfully built, scaled, and exited multiple companies.Developed robust software infrastructure capable of processing billions in transactions.Supported by top-tier venture capitalists and seasoned operating partners with a track record of investing in and nurturing iconic brands.Role OverviewDesign and implement end-to-end machine learning pipelines.Extract and mine data from various online sources through large-scale web crawling and scraping techniques to enhance our models and insights.Convert unstructured text data into structured knowledge using natural language processing (NLP), entity recognition, and bespoke models.Develop and refine text classification models to systematically organize intricate datasets.Enhance retrieval-augmented generation (RAG) systems utilized in our product offerings.Drive our data strategy by identifying and integrating new data sources.Tackle open-ended technical challenges, fostering a culture of learning and collaboration within the team.Primarily utilize Python and SQL for development.QualificationsA strong quantitative background in fields such as computer science, physics, mathematics, or engineering.Solid foundation in mathematics and statistics.A PhD in a quantitative discipline.Expertise in Python programming.Proactive ownership mentality with the ability to address complex technical challenges to create commercial value.A genuine enthusiasm for continuous learning, growth, and uncovering insights from complex datasets.Strong problem-solving, communication, and collaboration abilities in a dynamic work environment.

Join Hive as a Senior Machine Learning Engineer and help shape the future of AI! We are seeking passionate individuals who excel at developing and deploying cutting-edge deep learning models. In this role, you will work with large-scale datasets to create innovative machine learning solutions, collaborating closely with a talented team of engineers to push the boundaries of artificial intelligence. Ideal candidates will have a proven track record of building and scaling machine learning projects from conception to production, along with a strong commitment to continuous learning and personal ownership in their work.

Join Orchard as a Machine Learning Engineer and play a pivotal role in transforming data into actionable insights. In this dynamic position, you will leverage your expertise in machine learning algorithms and data analysis to develop innovative solutions that enhance our products and services.We are looking for a proactive team player who thrives in a fast-paced environment and possesses strong problem-solving skills. You will collaborate with cross-functional teams, engage with large datasets, and contribute to the design and implementation of machine learning models.

About Scribd:At Scribd Inc. (pronounced 'scribbed'), we're on a mission to ignite human curiosity. Join our innovative team as we craft a diverse world of stories and knowledge, democratizing the exchange of ideas and empowering collective intelligence through our four flagship products: Everand, Scribd, Slideshare, and Fable.This job posting is for an exciting, open position within our organization.We foster a culture where authenticity and boldness thrive, facilitating open debates and commitments as we embrace the unexpected. Every team member is empowered to take initiative, prioritizing the needs of our customers.In terms of workplace structure, we prioritize a balance between personal flexibility and communal connections. Our Scribd Flex initiative allows employees, in collaboration with their managers, to determine their daily work styles that best suit their individual needs while promoting intentional in-person interactions to enhance collaboration and company culture. Therefore, occasional in-person attendance is mandatory for all employees, regardless of their location.What do we seek in our new team members? We value 'GRIT'—the intersection of passion and perseverance toward long-term goals. At Scribd Inc., we believe in harnessing the potential that GRIT unlocks and encourage each employee to adopt a GRIT-driven approach to their work. This means we are looking for individuals who can set and achieve Goals, deliver Results in their responsibilities, contribute Innovative ideas, and positively impact the broader Team through collaboration and a positive attitude.About Our Machine Learning Team:Our Machine Learning team is pivotal in developing the platform and product applications that drive personalized discovery, recommendations, and generative AI functionalities across Scribd, Slideshare, and Everand. The ML team operates on the Orion ML Platform, providing essential ML infrastructure such as a feature store, model registry, model inference systems, and embedding-based retrieval (EBR). Our Machine Learning Engineers collaborate closely with the Product team to integrate machine learning into user-facing features, including real-time personalization and AskAI LLM-powered experiences.

Join our innovative team at Shepherd as a Machine Learning Engineer. In this role, you will leverage your expertise to develop cutting-edge AI solutions that drive our business forward. You will work closely with cross-functional teams to design, implement, and optimize machine learning algorithms that enhance our products and services.

Join Middesk as a Machine Learning Engineer and contribute to cutting-edge projects that leverage machine learning to drive business insights. You will collaborate with a dedicated team of data scientists and engineers, developing algorithms and models that enhance our product offerings and improve user experience.

About Our TeamJoin the innovative Sora team at OpenAI, where we are at the forefront of developing multimodal capabilities for our foundation models. Our hybrid research and product team is dedicated to seamlessly integrating multimodal functionalities into our AI solutions, ensuring they are dependable, user-centric, and aligned with our vision of benefiting society at large.Role OverviewAs a Machine Learning Engineer specializing in Distributed Data Systems, you will be instrumental in designing and scaling the infrastructure that facilitates large-scale multimodal training and evaluation at OpenAI. Your role will involve managing complex distributed data pipelines, collaborating closely with researchers to convert their requirements into robust, production-ready systems, and enhancing pipelines that are essential for Sora's rapid iteration cycles.We are seeking detail-oriented engineers with extensive experience in distributed systems who thrive in high-stakes environments and excel in building resilient infrastructure.This position is located in San Francisco, CA, and follows a hybrid work model, requiring three days in the office each week. We also provide relocation assistance for new team members.Key Responsibilities:Design, implement, and maintain data infrastructure systems, including distributed computing, data orchestration, distributed storage, streaming infrastructure, and machine learning systems, with a focus on scalability, reliability, and security.Ensure our data platform can scale exponentially while maintaining high reliability and efficiency.Collaborate with researchers to gain a deep understanding of their requirements, translating them into production-ready systems.Strengthen, optimize, and manage critical data infrastructure systems that support multimodal training and evaluation.You Will Excel in This Role If You:Possess strong experience with distributed systems and large-scale infrastructure, coupled with a keen interest in data.Exhibit meticulous attention to detail and a commitment to building and maintaining reliable systems.Demonstrate solid software engineering fundamentals and effective organizational skills.Thrive in environments characterized by ambiguity and rapid change.About OpenAIOpenAI is a trailblazing AI research and deployment organization committed to ensuring that general-purpose artificial intelligence serves humanity. We continuously push the boundaries of AI capabilities and strive to create technology that benefits everyone.

Join Whatnot as a Machine Learning Platform Engineer, where you'll play a pivotal role in shaping the future of our AI-driven solutions. In this dynamic position, you will collaborate with cross-functional teams to design, implement, and optimize machine learning platforms that drive efficiency and innovation.Your expertise will be critical in enhancing our data processing capabilities and deploying robust machine learning models at scale. If you are passionate about leveraging cutting-edge technology to solve complex challenges, we want to hear from you!

Join Us as a Founding Data Scientist and Machine Learning EngineerAmplify Your ImpactYou have achieved remarkable milestones in your career—delivering impactful models, influencing key metrics, and showcasing the transformative potential of data science and machine learning. You have positively affected products that touch millions of lives.Now, envision the possibility of enhancing the entire app ecosystem by extending your influence across numerous products and companies, making every app in users’ pockets smarter, more engaging, and indispensable.Your expertise can empower product teams to innovate faster, captivate users, and drive revenue growth, thanks to the intelligence you develop once and deploy universally.We share this ambition; we have successfully achieved it multiple times at leading organizations like Uber, Apple, Meta, Google, and Chime. Our contributions have generated tens of billions of dollars in impacts for essential products relied on by billions, and we are poised to elevate our influence further.If this resonates with the journey you seek, we invite you to continue reading.Our MissionDashboards recount the past; teams require insights for their next move. Palladio AI serves as the intelligence layer between raw data and decisive action, illuminating product opportunities that translate into genuine growth levers and guiding actions so product teams can iterate with confidence and speed rather than wade through noise.Your RoleYou will be part of a team crafting foundational systems in behavioral modeling, causal inference, forecasting, agentic platforms, and beyond. Your contributions will extend these domains: developing ML and AI models to identify and highlight product opportunities, deploying learning loops that enhance with each release. In essence, you will convert fundamental data science principles into a scalable product across various industries.Beyond technical challenges, you will create a platform that aids real people in making informed decisions, transforming data into clarity and clarity into actionable progress.Your ProfilePassion for Craft and Excellence. You dive into complex datasets, prototype swiftly, and refine until insights shine.Impact-Driven Mindset. 6+ years of experience in production ML/DS; you harmonize scientific rigor with a practical approach—“it ships today, iteration follows.”

Lila Sciences is seeking a Principal Machine Learning Engineer based in San Francisco, CA. This position centers on designing and building advanced machine learning algorithms to support scientific progress in healthcare and agriculture. Role overview The Principal Machine Learning Engineer will develop and implement new algorithms that strengthen Lila Sciences’ product capabilities and support data-driven decisions. The work will directly affect both internal business outcomes and broader scientific initiatives. Collaboration and impact This role involves close collaboration with engineers and data scientists on projects that address a range of technical and scientific challenges. The solutions created will have a direct influence on the future of healthcare and agriculture by applying advanced analytics and machine learning techniques.

Key Responsibilities:Serve as a pivotal member of the leadership team, shaping strategy and vision for the organization.Establish the functional and research roadmap to drive business growth.Guide, mentor, and expand the data science team, fostering professional development.Utilize high-quality, diverse datasets from Fortune 500 companies to extract actionable insights for our clients.Design, prototype, and refine innovative architectures in Natural Language Processing (NLP), including Dual-Encoders, Retrieval-Based Ranking Engines, and Generative Models.Establish thought leadership in the industry by sharing insights through blogging and speaking engagements at conferences.

Join our dynamic team at Jobs for Humanity as a Machine Learning Data Scientist, where you will harness the power of data to drive innovative solutions for underserved communities. Your expertise will play a crucial role in developing algorithms and models that enhance accessibility and improve lives.As a key member of our team, you will collaborate with cross-functional teams to identify opportunities for leveraging data to create impactful products. If you are passionate about using your data science skills for a greater good, we want to hear from you!