5 jobs found

Job Description Job Description Company Description The Bosch Research and Technology Center North America with offices in Sunnyvale, California, Pittsburgh, Pennsylvania, and Cambridge, Massachusetts is a part of the global Bosch Group (), a company with over 70 billion euro revenue, 400,000 employees worldwide, a very diverse product portfolio, and a history spanning over 125 years. The Research and Technology Center North America (RTC-NA) is dedicated to providing technologies and system solutions for various Bosch business fields, primarily in the field of artificial intelligence, energy technologies, internet technologies, circuit design, semiconductors and wireless, as well as advanced MEMS design. As a part of the global research, our AI research in Silicon Valley focuses on Foundation Models, Natural Language Processing, Computer Vision & Mixed Reality, Cloud Robotics, Big Data Visual Analytics, Explainable AI (XAI), Data Science, AI System Engineering, Time-series Analysis. We develop scalable, intelligent, and trustworthy AIoT solutions for Bosch products and services in application areas such as automated driving, advanced driver assistance systems (ADAS), robotics, smart manufacturing, enterprise AI, health care, smart home and building solutions. Originating from the AI research in Silicon Valley, our Foundation Model Powered AI Enablers group plays a pivotal role in shaping the future of industrial AI experiences for Bosch products and services. By fusing cutting-edge machine learning, data analysis, and interactive visualization technologies, we research and develop scalable and transparent AI & big data analytic solutions (e.g., audio, images, sensor logs) for a range of domains, including Industry 4.0 (I4.0), IoT, autonomous driving, and connected vehicles. Our award-winning team (IEEE VIS best paper & best paper runner-ups) actively collaborates with leading academic and industry groups to advance research ideas and disseminate findings in top AI conferences and journals, such as CVPR, ICCV, ICRA, ECCV, NeurIPS, ICLR, SIGGRAPH, TVCG. Job Description Job Responsibilites: Develop and lead research of AI projects that label, predict, classify, cluster, describe and fuse multi-sensor data (including acoustic, telemetry timeseries signals, vibration, radar, lidar, image, Wi-Fi, and ultrasound data), to improve / enable advance driver assistance system (ADAS) functionality in vehicles and AI functionalities in other Bosch products. Architect, design and validate multi-modal deep learning and Timeseries Foundation Models (TSFM) to work with multivariate time series signals. Must have a grasp of both low and high frequency models. Integrate and extend timeseries models to leverage information from other auxiliary modalities such as videos and images to enhance context understanding. Offer expert insights to the management team in relevant technology sectors, aiding in strategic planning, R&D trajectory, and investment decisions. Stay abreast of the latest technological innovations, document and disseminate research findings through high-caliber publications and/or patent submissions. Qualifications Basic Qualifications Ph.D. in Computer Science, Electrical Engineering, Information Technology or a related discipline OR Masters degree with 2-3 years of preferred professional experience Expertise with Time Series FMs (beyond the time series task of forecasting) In-depth experience in signal processing for sensor data and their integration with deep-learning methods Proficiency in Python, PyTorch (including libraries such as torchaudio, torchvision, torchmetrics), familiarity with PyTorch Lightning A strong publication record in relevant venues such as ICASSP, NeurIPS, InterSpeech, ICML, ICLR, KDD, ICRA, CVPR, ICCV, ECCV or equivalent contributions to the field such as patents or significant open-source projects Strong interpersonal, communication, and teamwork capabilities Preferred Qualifications 3+ years of experience in industrial research Experience with one or more of the following areas: data-centric AI, synthetic data generation, agentic AI Proficiency with version control systems (Git), integrated development environment (VSCode or PyCharm) and experience with experiment tracking tools (MLFlow) Familiarity with high-performance computing systems and job schedulers (Slurm, LSF) Hands-on experience in product development in the above-mentioned areas for consumer/enterprise markets Experience leading projects with small teams, demonstrating the ability to mentor junior researchers and interns, manage project timelines, and deliver results within time constraints Additional Information Your well-being matters at Bosch! We offer a competitive compensation and a benefits package designed to empower you in every area of your life. This includes premium health coverage, a 401(k) with generous matching, resources for financial planning and goal setting, ample paid time off, parental leave, and comprehensive life and disability protection. We're investing in your success! Equal Opportunity Employer, including disability / veterans Bosch adheres to Federal, State, and Local laws regarding drug-testing. Employment is contingent upon the successful completion of a drug screen and background check. Candidates who have been offered the position must pass both screenings before their start date. The U.S. base salary range for this full-time position is $165,000 - $ 195,000. Within the range, individual pay is determined based on several factors, including, but not limited to, work experience and job knowledge, complexity of the role, job location, etc. Your Recruiter can share more details about the specific salary range for this position during the interview process.

Job Description Job Description About the Institute of Foundation Models The Institute of Foundation Models is a dedicated research lab focused on building, understanding, using, and risk-managing foundation models. Our mission is to advance AI research, support the next generation of AI builders, and develop impactful systems that improve how frontier models are trained, evaluated, deployed, and governed. As part of our team, you will work closely with researchers, machine learning engineers, data scientists, software engineers, and product teams on some of the most important challenges in AI development. You will contribute to systems that help measure model quality, identify failure modes, and improve the reliability, safety, and readiness of model releases. The Role We are looking for an Eval360 - Error Analysis Engineer to help build, improve, and operate Eval360, an evaluation service that serves as a quality gate for AI models. This person will focus specifically on error analysis : understanding where models fail, why they fail, how those failures should be categorized, and how evaluation systems can better detect, measure, and prevent these issues before models are released. You will collaborate with researchers, machine learning engineers, product managers, data scientists, and platform teams to develop AI evaluation applications and internal tools based on next-generation AI research. You will be part of a cross-functional team responsible for the full software development lifecycle, from requirements gathering and system design to implementation, deployment, monitoring, debugging, documentation, and continuous improvement. The ideal candidate is comfortable working across the stack, including front-end interfaces for reviewing errors, back-end evaluation pipelines, data analysis workflows, model evaluation infrastructure, databases, dashboards, and APIs. This person should have strong software engineering skills, excellent analytical judgment, and the ability to turn ambiguous model failures into structured insights that improve evaluation quality. Key Responsibilities • Collaborate with researchers, machine learning engineers, data scientists, product managers, and internal stakeholders to implement innovative software solutions for Eval360 and related model evaluation workflows. • Build and improve Eval360 as an evaluation service that acts as a quality gate for model development, model comparison, and model release decisions. • Perform deep error analysis on model outputs, including identifying failure patterns, categorizing issues, tracing root causes, and proposing improvements to evaluation methodology. • Develop tools, workflows, and dashboards that make it easier for researchers and engineers to inspect model failures, compare model behavior, and understand quality regressions. • Design and implement client-side and server-side architecture for evaluation review systems, error analysis interfaces, reporting tools, and internal evaluation applications. • Develop responsive, usable interfaces that support error triage, annotation review, evaluation debugging, and model quality investigation. • Build and maintain back-end services, APIs, data pipelines, and integrations that support evaluation execution, results storage, analysis, and reporting. • Test software to ensure responsiveness, correctness, reliability, and efficiency across evaluation workflows. • Troubleshoot, debug, and upgrade evaluation systems, including identifying issues in data processing, evaluation metrics, model output handling, job orchestration, and user-facing analysis tools. • Create and maintain security, access control, and data protection settings for evaluation data, model outputs, annotations, and internal tooling. • Write clear technical documentation for Eval360 systems, error taxonomies, evaluation workflows, debugging procedures, and user-facing tools. • Work with researchers, data scientists, analysts, and machine learning engineers to improve evaluation quality, model diagnostics, and failure-mode visibility. • Keep track of new development tools, evaluation frameworks, model analysis methods, data quality techniques, and architectures relevant to AI evaluation systems. • Contribute to the design of error taxonomies, evaluation rubrics, quality thresholds, regression detection methods, and model readiness criteria. • Help ensure Eval360 produces reliable, interpretable, and actionable signals for model quality gates. • Contribute to research publications, technical reports, internal knowledge sharing, and external presentations where appropriate. • Contribute to intellectual property and thought leadership in AI evaluation, error analysis, model quality measurement, and evaluation infrastructure. • Perform all other duties as reasonably directed by the line manager that are aligned with these functional objectives. Academic Qualifications • Bachelor's degree in Computer Science, Machine Learning, Data Science, Software Engineering, Statistics, or a related technical field required. • Master's or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related field preferred. Professional Experience • Proven experience as a Software Engineer, Full Stack Developer, Machine Learning Evaluation Engineer, Data Scientist, AI Engineer, or similar role. • Experience building software systems for AI, machine learning, data analysis, evaluation, annotation, experimentation, or model monitoring. • Experience working with AI algorithms and the ability to develop systems that accommodate AI-related requirements. • Experience performing error analysis, model evaluation, data quality analysis, or failure-mode investigation for machine learning or language model systems. • Experience developing internal applications, dashboards, review tools, or web-based workflows for technical users. • Familiarity with common software stacks, including front-end frameworks, back-end services, databases, APIs, and cloud or internal infrastructure. • Familiarity with GitHub, Git, CI/CD workflows, and collaborative software development practices. • Knowledge of front-end languages and libraries such as HTML, CSS, JavaScript, TypeScript, React, Angular, or similar technologies. • Knowledge of back-end languages and frameworks such as Python, Java, C#, Node.js, FastAPI, Flask, Django, or similar technologies. • Familiarity with databases such as MySQL, PostgreSQL, MongoDB, or other structured and unstructured data stores. • Familiarity with evaluation frameworks, experiment tracking systems, data pipelines, or machine learning infrastructure is strongly preferred. • Ability to analyze complex model outputs and translate qualitative failures into structured, measurable categories. • Strong problem-solving and troubleshooting skills, especially for ambiguous technical issues involving models, data, metrics, and software systems. • Effective communication and collaboration skills, with the ability to work across research, engineering, data, and product teams. • Strong attention to detail and a high bar for evaluation quality, reliability, and interpretability. Preferred Qualifications • Experience with large language models, foundation models, multimodal models, or model evaluation systems. • Experience designing or using error taxonomies, evaluation rubrics, benchmark datasets, human evaluation workflows, or automated grading systems. • Experience with Python-based data analysis tools such as pandas, NumPy, Jupyter, or similar. • Experience with visualization or dashboarding tools for model quality analysis. • Experience with distributed systems, job queues, workflow orchestration, or large-scale data processing. • Experience working in a research environment or with fast-moving AI product and model teams. Salary Range The posted salary range represents the company's good faith estimate of the compensation for this position upon hire. The actual compensation offered may vary within this range depending on individual qualifications, including but not limited to relevant skills, experience, education, certifications, geographic location, and specific business needs. Visa Sponsorship This position is eligible for visa sponsorship. Benefits Include • Comprehensive medical, dental, and vision benefits • Bonus • 401K plan • Generous paid time off, sick leave, and holidays • Paid parental leave • Employee assistance program • Life insurance and disability insurance

Job Description Job Description Must be located near the Bay Area, with reliable transport to San Francisco, CA. About Us We are a well-capitalized stealth startup building robotic foundation models and world models for Physical AI. Founded by researchers from leading AI labs, our team works across robot hardware, data, infrastructure, and machine learning. The Role We are looking for a hands-on Robotics Systems Engineer to build and operate the robotic platforms behind our research. You will work across hardware, embedded systems, robot software, communications, calibration, data collection, evaluation, and deployment. This role is broader than mechatronics: you should be comfortable debugging the complete system, from sensors and actuators, close loop control, and learned-policy evaluation. Responsibilities Bring up, integrate, and maintain humanoids, robotic arms, and custom platforms. Debug mechanical, electrical, networking, communication, and software failures. Integrate and help design sensors, actuators, motor controllers, embedded devices, compute, wiring, and power systems. Develop robot drivers, hardware interfaces, diagnostics, and automation in Python or C++. Build distributed robotics software using ROS, ROS 2, ZMQ, and related technologies. Maintain teleoperation, robot data collection, dataset validation, and policy-evaluation software. Perform calibration, functional testing, reliability testing, and performance characterization. Develop logging, monitoring, health checks, and fault-recovery tools. Work with ML researchers to deploy and evaluate learned policies on physical robots. Improve system reliability, performance, safety, and maintainability. Use AI coding agents to accelerate implementation, testing, debugging, and documentation. Qualifications BS or MS in Robotics, Computer Engineering, Electrical Engineering, Mechanical Engineering, Mechatronics, Computer Science, or a related field. Experience integrating or operating complete robotic systems. Proficiency with Linux, Git, and Python or C++. Familiarity with ROS, ROS2, ZMQ or similar communication frameworks. Familiarity with sensors, actuators, embedded electronics, networking, and robot system design. Understanding of robot-learning workflows and their hardware and electronics requirements. Experience with robot data collection or evaluation software. Strong cross-stack debugging and problem-solving skills. Experience using AI coding agents such as Claude Code, Codex, or comparable tools, including reviewing and validating generated code. Comfortable working in a fast-moving environment and taking ownership of ambiguous problems. Nice to Have Experience with humanoids, manipulators, quadrupeds, or mobile robots. Experience with teleoperation or learned-policy deployment. Familiarity with CAN, EtherCAT, DDS, SPI, UART, or real-time systems. Embedded programming experience with STM32, ESP32, Raspberry Pi, Jetson, or similar platforms. Experience with camera, tactile, force-torque, encoder, or IMU integration and calibration. Familiarity with multimodal data synchronization, experiment tracking, and robotics evaluation metrics. CAD, machining, wiring, soldering, or rapid-prototyping experience. What You Will Gain Build advanced robots alongside experienced AI researchers and roboticists. Work across the complete robot-learning stack, from hardware to foundation models. Help shape the systems and engineering practices of an early-stage robotics company. Hiring Process Introductory conversation Technical interview One-day on-site assessment (paid at $40/hr). Initial six-month contract with strong potential for a longer-term opportunity. Logistics & Benefits Location: San Francisco, CA (South Beach/SoMa) - on-site 5 days a week Schedule: Full-time, 40 hours/week, including a 30-minute lunch break Employment: W-2, facilitated through Hire.io Compensation: $40+/hour, negotiable based on experience

Job Description Job Description The Company: Tutor Intelligence is a startup building the technology and processes to let robots go where they've never gone before: the average American factory. We understand that general-purpose and generally-intelligent robots are going to be built in our lifetimes , and we're combining human and artificial intelligence to lead the charge. As an AI software company who deploys its inventions directly into the facilities that need them, on state-of-the-art hardware, every line of code written at Tutor has a direct impact on the global, physical economy. We're seeking the thinkers, builders, and researchers who can help us responsibly deliver the future of automation. The Role: In this role you will close the loop between human instruction and robot automation. Models you create will be deployed to robots out in the field, in a tight feedback loop controlled by you. You will create and improve deep learning models such as CNNs, build a cloud-based data and model training platform, and find ways to help our robots optimize for speed and accuracy. For this role, we seek a pragmatic and competent engineer with domain expertise in computer vision and robotics, and a drive to proliferate robotic technologies. At Tutor, engineering is inherently cross-disciplinary and collaborative. We seek someone with a diverse background across the robotics stack, including anything from full stack web-dev to mechanical engineering. Our Culture: We believe that something truly special can happen when talented, motivated people work together; at Tutor, every member of our team is empowered to have real impact in everything that they do. We work collaboratively on just about everything we do - nobody has the full story, but we are all trying to, and need to work together to maximize our robots performance. Responsibilities: Train, fine tune, and deploy visual and language foundation models across our stack Manage data in databases and optimize the flow of information from our robots to maximize machine learning potential Skills Needed Knowledge of machine learning models, particularly visual models with an emphasis on recent advanced models such as SAM, DINO, etc. Strong software skills Full stack knowledge, ability to not only work on machine learning models in python but also to spin up inference infrastructure, web ui, and perform database operations General robotics knowledge & experience All offers include generous equity, fully covered health + dental, and unlimited PTO.

Description: At MetaMetrics, we believe every learner deserves the opportunity to succeed. Our mission is to empower educators, students, and families with trusted assessment solutions that provide meaningful insights and support learning. We're looking for a passionate and experienced Senior Psychometrician to help advance that mission. As a Senior Psychometrician, you will play a pivotal role in ensuring the validity, reliability, and fairness of our assessment products. Working alongside talented colleagues across research, product, engineering, and customer success, you'll apply rigorous psychometric principles to develop innovative assessment solutions that improve educational outcomes for millions of learners. This role offers the opportunity to influence the future of educational measurement while collaborating with a mission-driven team dedicated to making a lasting impact. The key responsibilities and qualifications for this position are outlined below. Please submit a cover letter that tells us why this opportunity interests you, highlights the experience and accomplishments that best prepare you for the role, explains why you believe you're a great fit for our mission and culture, and shares why you're excited to join our team. Essential Duties & Responsibilities Develops plans and executes psychometric projects and research according to priorities and resource availability. Directs the creation and maintenance of project schedules, communication with clients, evaluation of external data, and review of process and results produced by Research Analysts. Conducts independent linking/equating and research studies, supports the completion of studies by others, and develops white papers and research summaries. Implements and improves psychometric research methods and processes at MetaMetrics according to best practices, industry standards, and academic literature. Maintains awareness of psychometric literature and methods regarding test and delivery methods (e.g., fixed-form, computer adaptive, and linear-on-the-fly), statistical methods (e.g., simulation studies), and computational psychometrics (e.g., machine learning, Bayesian inference). Provides ad hoc or planned expert consultation to clients and their stakeholders (e.g., technical advisory committees) regarding methods, results, and interpretation of MetaMetrics products and services. Perform other duties as assigned. Supervisory Responsibilities None. Provides support only in accordance with the organization's policies and applicable laws. Requirements: Education and/or Experience: A doctoral degree (Ph.D.) or equivalent in educational statistics, measurement, psychometrics, or related field is required, along with 5+ years of experience as a practicing psychometrician. Extensive experience with educational assessment and standard psychometric procedures (e.g., item analysis and calibration, score equating, scale linking). Familiarity with education technology infrastructure and development, including relational databases, software development languages (e.g., C++), and technologies (REST APIs), and program management (e.g., Agile). Computer Skills: Extensive experience with standard office and productivity software (e.g., Google Suite, Microsoft Office). Proficiency with general statistical software (e.g., R; Python) and specialized psychometric software (e.g., WINSTEPS, FACETS). Other Qualities: Language Skills : Ability to read, analyze, and interpret common scientific and technical journals and reports. Ability to respond to common inquiries from researchers, customers, or members of the general public. Ability to write presentations and articles for publication that conform to prescribed style and format. Ability to effectively present information to colleagues, management, and/or public groups. Psychometric Skills : Ability to apply advanced mathematical concepts such as exponents, logarithms, quadratic equations, and permutations. Ability to design and implement analyses related to test reliability and validity, analysis of variance, correlation techniques, sampling theory, and latent variable modeling. Ability to apply and interpret statistical procedures, including but not limited to Rasch calibration, linking, and equating. Presentation Skills: Ability to clearly and succinctly present analyses results to internal stakeholders (e.g., Sales, Test Development), external partners, and respond to psychometric and measurement questions related to MetaMetrics' core business. Reasoning Ability : Ability to apply principles of logical or scientific thinking to a wide range of intellectual and practical problems. Ability to deal with a variety of abstract and concrete variables. Publishing - A track record of peer-reviewed research publications and conference papers is preferred. PM18 Compensation details: 00 Yearly Salary PIf86e793d56ef-6481