Role Description - Develop LM/VLM-powered agents that autonomously interface with code, GUI, web tools, and design software to drive generative simulation. - Build agentic systems that synthesize high-quality, diverse physical data by orchestrating simulation, generative models, and interactive tools. - Build data pipelines to curate, generate, and preprocess datasets used for training and evaluating language- and vision-language-based agents. - Collaborate with simulation and infrastructure teams to co-develop APIs, GUIs, and services that enable seamless interaction with physics engines and simulation environments. - Drive innovation by staying at the forefront of LLM agents, autonomous tool use, and generative simulation — and translating cutting-edge research into robust, production-ready systems. - Contribute to the creation of a generative simulation stack that empowers downstream applications in robotics, embodied AI, and physical reasoning. Qualifications - A bold and imaginative vision for a next-generation paradigm of physical data synthesis— combining simulation, generative models, and autonomous agents. - Deep curiosity and strong technical ownership, with a track record of driving complex, open-ended projects from concept to implementation. - Experience with (multimodal) large language models, generative AI tools, agentic software design, GUI automation, program synthesis. - Passion for inventing creative solutions at the edge of AI, simulation, and physical reasoning, with an eagerness to build systems that generate high-fidelity, useful data for embodied intelligence. Requirements - Familiarity with interactive design tools (e.g., CAD software, game engines) or simulation environments (e.g., physics engines, robotics simulators).

Role Description - Design, build, and maintain large-scale data pipelines (batch and streaming) for robotics foundation model training and evaluation at petabyte scale - Own core data infrastructure: data model, storage systems, ingestion pipelines, transformation frameworks, and orchestration layers - Standardize data models and unify processing pipelines across real-world teleoperation and synthetic simulation datasets - Collaborate with a team of driven individuals committed to building general-purpose Physical AI Qualifications - Excellent software engineering skills (Python, Go, or similar) - Extensive experience designing, building, and maintaining large-scale data pipelines (8+ years) - Deep understanding of distributed systems (Spark, Kafka, or similar) - Extensive experience with data storage technologies (data lakes, warehouses, object stores like S3) - Experience running and maintaining production-grade infrastructure (Kubernetes, Terraform) Requirements - Bonus: Experience supporting AI systems, in particular embodied AI like self-driving

Role Description - Develop LM/VLM-powered agents that autonomously interface with code, GUI, web tools, and design software to drive generative simulation. - Build agentic systems that synthesize high-quality, diverse physical data by orchestrating simulation, generative models, and interactive tools. - Build data pipelines to curate, generate, and preprocess datasets used for training and evaluating language- and vision-language-based agents. - Collaborate with simulation and infrastructure teams to co-develop APIs, GUIs, and services that enable seamless interaction with physics engines and simulation environments. - Drive innovation by staying at the forefront of LLM agents, autonomous tool use, and generative simulation — and translating cutting-edge research into robust, production-ready systems. - Contribute to the creation of a generative simulation stack that empowers downstream applications in robotics, embodied AI, and physical reasoning. Qualifications - A bold and imaginative vision for a next-generation paradigm of physical data synthesis— combining simulation, generative models, and autonomous agents. - Deep curiosity and strong technical ownership, with a track record of driving complex, open-ended projects from concept to implementation. - Experience with (multimodal) large language models, generative AI tools, agentic software design, GUI automation, program synthesis. - Passion for inventing creative solutions at the edge of AI, simulation, and physical reasoning, with an eagerness to build systems that generate high-fidelity, useful data for embodied intelligence. Requirements - Familiarity with interactive design tools (e.g., CAD software, game engines) or simulation environments (e.g., physics engines, robotics simulators).

Role Description We are seeking a seasoned Data Engineer to join our team. You will be responsible for architecting and building robust data frameworks that empower Operational Data Store / Enterprise Data Lake Platforms. This role requires a blend of high-level technical expertise in modern data stacks and the ability to collaborate independently with stakeholders to translate business needs into scalable data solutions. What You’ll Do - Lead the full lifecycle of data engineering projects, from initial requirement gathering with stakeholders to production deployment and monitoring. - Design, develop and maintain complex data transformations, ensuring high data quality and performance using scripting languages like Python, Airflow, DBT and databases such as Snowflake or similar Data Lakes. - Build, scale, and maintain automated workflows using Apache Airflow to manage sophisticated data dependencies. - Maintain high engineering standards through CI/CD implementation and rigorous version control using GitHub. - Implement automated processes for data validation, ensuring high standards of data quality, accuracy, and integrity across all pipelines. - Act as a technical partner to the Analytics, Sales, and Marketing teams, building curated datasets that drive strategic decision-making. Qualifications - 3+ years' experience in design & developing complex automation frameworks, queries, data modeling in SQL, Python, DBT, Apache Airflow. - Deep experience in scripting languages such as Python and Cloud database experience such as Snowflake, Redshift, etc. to facilitate rapid ingestion and dissemination of key data. - Marketing Data Domain Expertise: Hands-on experience working with Marketing datasets including campaign performance data, lead, funnel stages and opportunity pipelines, and revenue attribution models. - Expertise in architecting scalable DBT projects using advanced modeling techniques, custom macros, complex Jinja-templated logic, and modular project structures to enforce DRY (Don't Repeat Yourself) principles across the enterprise. - Advanced proficiency in the DBT lifecycle including CI/CD processes such as Jenkins, Gitlab CI/CD etc., and source control tools such as GitHub, etc. - Experience identifying and solving issues concerning data management to improve data quality, and clean, prepare and optimize data for ingestion and consumption. - Proven experience integrating and managing business data from enterprise applications into Semantic Layers to decouple complex logic from the BI layer to drive analytics and insights. - Bachelor's Degree in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience. Bonus Points - Marketing Automation Tools Knowledge: Experience with platforms such as Salesforce, Marketo, People.ai, Outreach and CRM systems for data integration and processing. - Understanding of machine learning concepts: Ability to collaborate with data science teams and support machine learning initiatives through data preparation, transformation and Feature store support. Benefits - Market leader in compensation and equity awards - Comprehensive physical and mental wellness programs - Competitive vacation and holidays for recharge - Paid parental and adoption leaves - Professional development opportunities for all employees regardless of level or role - Employee Networks, geographic neighborhood groups, and volunteer opportunities to build connections - Vibrant office culture with world class amenities - Great Place to Work Certified™ across the globe