Senior Machine Learning Engineer at Kiddom | San Francisco

Join Our Innovative Team at KiddomAt Kiddom, we are revolutionizing education through our cutting-edge platform that champions student equity and growth. We seamlessly integrate high-quality instructional materials with engaging digital learning experiences. Our robust curriculum management tools empower schools and districts to effectively manage their curriculum, leading to personalized learning experiences that cater to the unique needs and aspirations of local communities. Our high-quality curriculum is enriched with insightful data analytics for teachers and leaders, fostering continuous improvement in instructional strategies, school programming, and professional development.Your Role and ResponsibilitiesAs a vital member of Kiddom’s AI team, you will play a critical role in developing the backbone of our search, recommendation, and insights systems. Your contributions will directly enhance the experience of teachers and students by providing timely insights, personalized content, and intelligent assistance tailored to their needs.

About KiddomKiddom is an innovative educational platform committed to fostering student equity and growth by seamlessly integrating high-quality instructional materials with engaging digital learning experiences. Our unparalleled curriculum management tools empower schools and districts to take charge of their curriculum, resulting in customized learning experiences that cater to the distinct needs of local communities. With robust data insights for teachers and leaders, Kiddom drives ongoing improvements in instructional decisions, school and district programming, and professional development.Join us in our mission to transform K-12 education through the integration of cutting-edge AI and meaningful learning outcomes. As a Machine Learning Researcher, you will be instrumental in expanding the possibilities of AI in the educational landscape. Your contributions will help personalize teaching experiences for educators and enhance student outcomes. This role merges technical expertise with the opportunity to create a lasting impact on educators and students across the nation.

At Kiddom, we are revolutionizing the educational landscape by leveraging advanced technology to enhance learning experiences. Our innovative platform integrates top-tier curriculum with state-of-the-art AI and modern SaaS infrastructure, empowering schools to provide truly personalized education at scale. By offering educators real-time insights and versatile tools, we enable them to prioritize what truly matters—driving student growth and ensuring equity.We are not merely creating educational technology; we are challenging an industry that has been slow to embrace innovation. As a Senior Product Manager, you will play a pivotal role at Kiddom, collaborating closely with engineers, designers, AI researchers, and educators to develop transformative experiences that redefine what is achievable in the classroom.If you excel in navigating uncertainty, thrive in a culture that values ownership, and are passionate about the intersection of human impact and cutting-edge technology, this is your opportunity to drive meaningful change.

About KiddomKiddom is an innovative educational platform dedicated to fostering student equity and growth by seamlessly integrating high-quality instructional materials with engaging digital learning. Our comprehensive curriculum management tools empower schools and districts to take charge of their curriculum, creating customized learning experiences that align with the distinct needs and aspirations of local communities. By providing robust insights for teachers and leaders, Kiddom drives continuous improvement in instructional decisions, school programming, and professional development.We are on a mission to revolutionize education through the power of technology. Our goal is to create a holistic platform that supports educators and learners alike with state-of-the-art tools and data-driven insights. We are seeking a skilled Staff Software Engineer to join our team and spearhead the architecture and development of scalable, frontend-focused solutions.As a Lead Software Engineer - Frontend at Kiddom, you will be instrumental in designing and delivering comprehensive product features with a strong focus on frontend architecture. Your role will involve scoping, building, and optimizing product features and addressing complex challenges at scale. You will work collaboratively with other senior engineers, select the most suitable tools and technologies, and implement robust, production-grade software solutions.Note: Please complete the application questions in full. Failure to do so will result in automatic disqualification.

Join Kiddom as a Senior Data Engineer and play a pivotal role in transforming the educational landscape through innovative technology. Our mission is to enhance learning experiences with an advanced curriculum, AI, and a robust SaaS infrastructure that empowers schools to provide personalized education at scale. Our platform delivers real-time insights and versatile tools that allow educators to prioritize student growth and equity effectively.At Kiddom, we don’t just create technology; we spearhead innovation in an industry ripe for change. Our dedicated team collaborates across engineering, design, research, and education to craft experiences that redefine possibilities for both learners and educators.If you excel in dynamic environments, cherish high-ownership cultures, and are passionate about merging human impact with cutting-edge technology, this is your opportunity to make a meaningful difference.Role Overview:As a Senior Data Engineer, you will be an integral part of our Data Architecture team, responsible for building and enhancing Kiddom’s data systems. You will focus on improving our core architecture for curriculum graphs and analytics while supporting various teams across the organization in utilizing the Kiddom data platform, ensuring student data privacy and security are paramount.Your role will involve close collaboration with departments such as Product, Engineering, and Analytics to understand their data requirements. You will define and document data workflows, pipelines, and transformation processes to ensure clarity and facilitate knowledge sharing.We seek a candidate with exceptional communication skills who can convey complex technical ideas to non-technical stakeholders. A solid understanding of PII compliance and best practices in data handling and storage is essential. If you possess strong problem-solving abilities and a talent for optimizing performance while ensuring data integrity and accuracy, we would love to hear from you!

Join Kiddom as a Senior Backend Software EngineerAt Kiddom, we are revolutionizing the education landscape by providing a platform that champions equity and growth for all students. Our innovative approach integrates top-tier instructional materials with engaging digital learning tools, allowing schools and districts to take charge of their curriculum. With our exceptional curriculum management capabilities, we deliver personalized learning experiences that cater to the specific needs and aspirations of local communities. Our robust data insights empower educators and leaders to enhance instructional strategies, improve school programs, and foster professional development.We are seeking a dedicated Senior Backend Software Engineer to join our dynamic team, where you will play a crucial role in creating the next generation of scalable backend services. Your responsibilities will include the design, development, and maintenance of high-performance systems that underpin our applications.The ideal candidate will possess significant experience in backend technologies and system architecture, coupled with a genuine passion for addressing complex challenges faced by our users. Mentoring fellow engineers and sharing your expertise will be key aspects of this role. A strong affinity for education, an understanding of teachers' needs, exceptional product insight, and a commitment to Kiddom's mission and vision are essential.

At Causal Labs, we are on a groundbreaking mission to develop general causal intelligence—artificial intelligence that not only predicts future events but also determines the most effective actions to influence those outcomes.To achieve this monumental goal, we are constructing a Large Physics Foundation Model (LPM). Our focus is on domains governed by physical laws, which inherently exhibit cause-and-effect relationships, setting them apart from traditional visual or textual data.Weather serves as the ideal training environment for our LPM, being one of the most extensively observed physical systems available. It provides immediate, objective feedback from sensory observations and boasts data scales significantly larger than those currently employed to train existing language models.Our team at Causal Labs includes leading researchers and engineers with backgrounds in self-driving technology, drug discovery, and robotics, hailing from prestigious organizations such as Google DeepMind, Cruise, Waymo, Meta, Nabla Bio, and Apple. We firmly believe that achieving general causal intelligence will represent one of the most critical technological advancements for our civilization.We are seeking innovative researchers eager to confront unsolved challenges in the field.This role presents an opportunity to create powerful models rooted in observable feedback and verifiable ground truths. If you possess experience in pioneering research and training large-scale models from the ground up in areas such as language and vision models, robotics, or biology, we invite you to join our mission.

About AlljoinedAt Alljoined, we are pioneering the future of communication between humans and technology by developing non-invasive methods to decode brain activity. By leveraging cutting-edge deep learning techniques on extensive EEG datasets collected through cost-effective hardware, we aim to interpret images, text, and video, with a long-term vision of understanding internal thoughts. Our capabilities are industry-leading, and we are fully vertically integrated. Our mission is to create a universal consumer interface that revolutionizes daily interactions both at home and in the workplace.We are on the lookout for exceptional researchers to expand our elite team, dedicated to creating the next transformative interface that enhances individual lives and contributes positively to society.About the RoleWe invite you to apply for the position of Machine Learning Researcher within our core R&D team. In this role, you will be responsible for conceptualizing and executing advanced machine learning models for EEG-based neural decoding, disseminating impactful research, and establishing the foundational infrastructure for our brain decoding systems. You'll collaborate with top-tier experts in neural decoding and AI, driving innovation in brain-computer interfaces.Key ResponsibilitiesResearch & Model Development:Craft, train, and enhance state-of-the-art deep learning models for neural decoding, utilizing the latest advancements in machine learning architectures such as transformers and diffusion models.Investigate innovative methodologies for modeling high-frequency time-series EEG datasets alongside various other data modalities.Convert research findings into production-ready code that seamlessly integrates with our proprietary brain-computer interface stack.Collaboration & Publication:Work in tandem with a multidisciplinary team of neuroscientists and ML engineers to develop scalable, end-to-end neural decoding solutions.Publish research outcomes in leading ML and AI conferences such as NeurIPS, ICML, ICLR, and CVPR, and actively engage in open-source communities as appropriate.

At Thinking Machines Lab, our ambition is to enhance human potential by advancing collaborative general intelligence. We envision a future where individuals have the tools and knowledge to harness AI for their distinct requirements and aspirations.Our team comprises dedicated scientists, engineers, and innovators who have contributed to some of the most renowned AI products, including ChatGPT and Character.ai, along with open-weight models like Mistral, and influential open-source projects such as PyTorch, OpenAI Gym, Fairseq, and Segment Anything.About the RoleWe are seeking an Infrastructure Research Engineer to architect, optimize, and sustain the computational frameworks that facilitate large-scale language model training. You will create high-performance machine learning kernels (e.g., CUDA, CuTe, Triton), enable effective low-precision arithmetic operations, and enhance the distributed computing infrastructure essential for training expansive models.This position is ideal for an engineer who thrives in close collaboration with hardware and research disciplines. You will partner with researchers and systems architects to merge algorithmic design with hardware efficiency. Your responsibilities will include prototyping new kernel implementations, evaluating performance across various hardware generations, and helping to establish the numerical and parallelism strategies crucial for scaling next-generation AI systems.Note: This is an evergreen role that remains open continuously for expressions of interest. We receive numerous applications, and there may not always be an immediate opportunity that aligns with your qualifications. However, we encourage you to apply, as we regularly assess applications and will reach out as new positions become available. You are also welcome to reapply after gaining additional experience, but please refrain from applying more than once every six months. Additionally, you may notice postings for specific roles catering to particular projects or team needs. In such cases, you are encouraged to apply directly alongside this evergreen listing.What You’ll DoDesign and develop custom ML kernels (e.g., CUDA, CuTe, Triton) for key LLM operations such as attention, matrix multiplication, gating, and normalization, optimized for contemporary GPU and accelerator architectures.Conceptualize compute primitives aimed at alleviating memory bandwidth bottlenecks and enhancing kernel compute efficiency.Collaborate with research teams to synchronize kernel-level optimizations with model architecture and algorithmic objectives.Create and maintain a library of reusable kernels and performance benchmarks that serve as the foundation for internal model training.Contribute to the stability and scalability of our infrastructure, ensuring it meets the growing demands of AI development.

About KiddomKiddom is an innovative educational platform committed to fostering student equity and growth by integrating high-quality instructional materials with engaging digital learning experiences. Our platform offers exceptional curriculum management capabilities, empowering schools and districts to take charge of their educational content. This results in tailored learning experiences that cater to the unique needs and aspirations of local communities. With detailed insights into teacher and leader performance, Kiddom drives continuous improvement in instructional strategies, school/district programs, and professional development.At Kiddom, we are passionate about revolutionizing education through state-of-the-art technology. Our mission is to create a comprehensive platform that equips educators and learners with advanced tools and data-driven insights. We are seeking a skilled Lead Software Engineer specializing in Frontend development to join our team and spearhead the design and implementation of scalable, frontend-centric solutions.As the Lead Software Engineer - Frontend, you will be pivotal in architecting and delivering full-stack product features with a focus on frontend architecture. Your responsibilities will include defining, building, and optimizing product features and addressing complex challenges at scale. You will collaborate with senior engineers to select optimal tools and technologies while implementing robust, production-ready software solutions.

About Liquid AIFounded as a spin-off from MIT CSAIL, Liquid AI specializes in creating versatile AI systems designed for optimal performance across various deployment platforms, including data center accelerators and on-device hardware. Our technology emphasizes low latency, minimal memory consumption, privacy, and dependability. We collaborate with leading enterprises in sectors such as consumer electronics, automotive, life sciences, and financial services. As we experience rapid growth, we are on the lookout for exceptional talent to join our team.The OpportunityThe Data team at Liquid AI drives the development of our Liquid Foundation Models, focusing on pre-training, vision, audio, and emerging modalities. With the stagnation of public data sources, the effectiveness of our models increasingly relies on specially curated datasets. We are seeking engineers with a machine learning mindset who can efficiently gather, filter, and synthesize high-quality data at scale.At Liquid AI, we regard data as a research challenge rather than an infrastructural issue. Our engineers conduct experiments, design ablations, and assess how data-related decisions impact model quality. We will align you with a team where you can experience rapid growth and make a significant impact, be it in pre-training, post-training reinforcement learning, vision-language, audio, or multimodal applications.While we prefer candidates in San Francisco and Boston, we are open to considering other locations.What We're Looking ForWe are in search of a candidate who:Thinks like a researcher and executes like an engineer: You should be able to formulate hypotheses, conduct experiments, and evaluate results. Our engineers produce research-level code while our researchers implement production systems.Learns quickly and adapts: You will be working in rapidly evolving modalities, so the ability to quickly grasp new domains and thrive in ambiguity is essential.Prioritizes data quality: We hold data quality in high regard; tasks such as filtering, deduplication, augmentation, and evaluation are key responsibilities, not afterthoughts.Solves problems autonomously: Data engineers operate within training groups (pre-training and multimodal). While collaboration is crucial, we expect ownership and self-direction.The WorkDevelop and maintain data processing, filtering, and selection pipelines at scale.Establish pipelines for pretraining, midtraining, supervised fine-tuning, and preference optimization datasets.Design synthetic data generation systems utilizing large language models (LLMs), structured prompting, and domain-specific generative techniques.

Join Handshake as a Machine Learning Research Scientist and contribute to groundbreaking projects that leverage advanced algorithms and data analysis to drive innovation. In this role, you will collaborate with a dynamic team to design, implement, and evaluate machine learning models that enhance our products and services. Your expertise will be pivotal in unlocking new insights from data, improving user experiences, and shaping the future of our technology.

Company Overview:At Specter, we are pioneering a software-defined control plane for the physical realm, beginning with safeguarding American enterprises through comprehensive monitoring of their physical assets.Our innovative approach leverages a connected hardware-software ecosystem built on advanced multi-modal wireless mesh sensing technology. This breakthrough enables us to reduce the deployment costs and time for sensors by a factor of 10. Our ultimate goal is to establish a perception engine that provides real-time visibility of a company’s physical environment and facilitates autonomous operations management.Co-founders Xerxes and Philip are dedicated to empowering our partners in the rapidly evolving landscape of physical AI and robotics. Join our dynamic and rapidly expanding team comprised of talents from Anduril, Tesla, Uber, and the U.S. Special Forces.Position Overview:We are seeking a Perception AI Engineer who will be instrumental in transforming sensor data pipelines into actionable insights for our clients.Key Responsibilities:Implement and deploy a range of deep-learning models, including vision, vision-language, and large language models, within our sophisticated distributed perception system.Design and scale a production-ready data collection, labeling, and model retraining platform.Lead the design of a multimodal software user interface.

Join the Center for AI Safety (CAIS), a pioneering research and advocacy organization dedicated to addressing the societal-scale risks posed by artificial intelligence. We tackle the most pressing challenges in AI through rigorous technical research, innovative field-building initiatives, and proactive policy engagement, in collaboration with our sister organization, the Center for AI Safety Action Fund.As a Research Scientist, you will spearhead and conduct transformative research aimed at enhancing the safety and dependability of cutting-edge AI systems. Your responsibilities will include designing and executing experiments on large language models, developing the necessary tools for training and evaluating models at scale, and converting your findings into publishable research. You will work closely with CAIS researchers and external partners from academia and industry, utilizing our compute cluster for large-scale model training and evaluation. Your research will focus on critical areas such as AI honesty, robustness, transparency, and the detection of trojan/backdoor behaviors, all aimed at mitigating real-world risks associated with advanced AI technologies.

At Exa, we are revolutionizing the way AI applications access information by building a cutting-edge search engine from the ground up. Our team is dedicated to developing a robust infrastructure capable of crawling the web, training advanced embedding models, and creating high-performance vector databases using Rust to facilitate seamless searches.As part of our ML team, you'll be instrumental in training foundational models that refine search capabilities. Our mission? To deliver precise answers to even the most complex queries, effectively transforming the web into an incredibly powerful knowledge database.We are seeking a talented Machine Learning Research Engineer who is passionate about crafting embedding models that enhance web search efficiency. Your responsibilities will include innovating novel transformer-based architectures, curating extensive datasets, conducting evaluations, and continuously improving our state-of-the-art models.

bland is looking for a Machine Learning Researcher with a focus on audio. This position is based in San Francisco and centers on advancing how machines process and understand sound. The team works on pushing the boundaries of audio technology for a range of platforms. Responsibilities Research and develop new machine learning techniques for audio applications Contribute to projects that improve audio processing and analysis Collaborate with colleagues to bring research ideas into real-world audio products Location This role requires working onsite in San Francisco.

About MercorMercor sits at the forefront of labor markets and artificial intelligence research, collaborating with premier AI laboratories and enterprises to harness the human intelligence crucial for AI evolution.Our expansive talent network empowers the training of cutting-edge AI models, akin to how educators impart knowledge to students—sharing insights, experiences, and contexts that transcend mere code. Currently, our network comprises over 30,000 experts, generating collective earnings exceeding $2 million daily.At Mercor, we are pioneering a unique category of work where expertise fuels AI progress. Realizing this vision necessitates a bold, fast-paced, and deeply dedicated team. You will collaborate with researchers, operators, and AI firms that are at the vanguard of transforming systems that redefine society.As a profitable Series C company, Mercor is valued at $10 billion and maintains an in-office presence five days a week at our new headquarters in San Francisco.About the RoleIn your capacity as a Research Engineer at Mercor, you will operate at the intersection of engineering and applied AI research. You will play a pivotal role in post-training and Reinforcement Learning from Human Feedback (RLVR), synthetic data generation, and large-scale evaluation workflows essential for advancing frontier language models.Your contributions will help train large language models to adeptly utilize tools, exhibit agentic behavior, and engage in real-world reasoning within production environments. You will be instrumental in shaping rewards, conducting post-training experiments, and constructing scalable systems to enhance model performance. Your responsibilities will also include designing and evaluating datasets, creating scalable data augmentation pipelines, and developing rubrics and evaluators that expand the learning potential of LLMs.

About KiddomKiddom is an innovative educational platform dedicated to enhancing student equity and growth by integrating high-quality instructional materials with engaging digital learning experiences. Our exceptional curriculum management capabilities enable schools and districts to take charge of their educational programs, leading to personalized learning outcomes that address the specific needs and aspirations of local communities. Additionally, Kiddom's comprehensive curriculum is enriched with valuable insights for teachers and educational leaders, facilitating continuous improvements in instructional strategies, school programming, and professional development.About the Role: In the role of Senior Engineering Manager, you will report directly to the VP of Engineering while overseeing multiple teams of skilled engineers. This position merges technical leadership with strategic influence, granting you the opportunity to refine Kiddom's systems and procedures to support our scaling initiatives. You will engage with cutting-edge technologies, including Python, Golang, Node.js, JavaScript/TypeScript, Kubernetes, and AWS, tackling complex technical challenges that have a meaningful impact on educators, administrators, and students alike. Your capacity to inspire and drive transformation throughout the engineering organization will be crucial as we embrace new technologies and AI advancements to enhance our efficiency and that of our users.This role can be based in New York City or San Francisco, requiring 2-3 days in the office each week.

Join us at Physical Intelligence as a Research Scientist, where you will be at the forefront of innovation in machine learning and robotics. We are in search of exceptional researchers across all experience levels who demonstrate a strong track record of impactful research results. Ideal candidates will possess a solid foundation in both practical implementation and theoretical frameworks, showcasing a blend of system-building capabilities and significant conceptual, algorithmic, or theoretical advancements. We value diverse backgrounds and encourage applications from both traditional academic researchers and those with unique, unconventional experiences.We are committed to fostering a diverse and inclusive workplace. In accordance with the San Francisco Fair Chance Ordinance, we welcome applications from qualified individuals with arrest and conviction records.

OverviewPluralis Research is at the forefront of Protocol Learning, innovating a decentralized approach to train and deploy AI models that democratizes access beyond just well-funded corporations. By aggregating computational resources from diverse participants, we incentivize collaboration while safeguarding against centralized control of model weights, paving the way for a truly open and cooperative environment for advanced AI.We are seeking a talented Machine Learning Training Platform Engineer to design, develop, and scale the core infrastructure that powers our decentralized ML training platform. In this role, you will have ownership over essential systems including infrastructure orchestration, distributed computing, and service integration, facilitating ongoing experimentation and large-scale model training.ResponsibilitiesMulti-Cloud Infrastructure: Create resource management systems that provision and orchestrate computing resources across AWS, GCP, and Azure using infrastructure-as-code tools like Pulumi or Terraform. Manage dynamic scaling, state synchronization, and concurrent operations across hundreds of diverse nodes.Distributed Training Systems: Design fault-tolerant infrastructure for distributed machine learning, including GPU clusters, NVIDIA runtime, S3 checkpointing, large dataset management and streaming, health monitoring, and resilient retry strategies.Real-World Networking: Develop systems that simulate and manage real-world network conditions—such as bandwidth shaping, latency injection, and packet loss—while accommodating dynamic node churn and ensuring efficient data flow across workers with varying connectivity, as our training occurs on consumer nodes and non-co-located infrastructure.