Senior Data Engineer, ML Ops

Build the Path Forward

At Path Robotics, we’re building the future of embodied intelligence. Our AI-driven systems enable robots to adapt, learn, and perform in the real world closing the skilled labor gap and transforming industries. We go beyond traditional methods, combining perception, reasoning, and control to deliver field-ready AI that is risk-aware, reliable, and continuously improving through real-world use.

Big, hard problems are our everyday work, and our team of intelligent, humble, and driven people make the impossible possible together.

You will play a mission-critical role in architecting our data platform, enabling our machine learning and robotics teams to move faster, experiment more effectively, and deploy AI solutions into production.

This is a founding-level opportunity to lay the groundwork for our entire data infrastructure and build the data team. Reporting to the Director of AI, you’ll collaborate with a talented team of machine learning engineers and software engineers to deliver clean, reliable, and scalable data pipelines that fuel experimentation, production models, and cutting-edge AI development.

• Architect and build our end-to-end data platform, including ingestion, transformation, orchestration, quality monitoring, and data access layers.
• Lead initiatives that break down data silos and enable seamless collaboration between business domains
• Design and develop optimized database architecture and data schemas with strategic partitioning for large scale multi-modal data.
• Implement scalable ETL/ELT pipelines that serve experimentation, training, validation, and real-time deployment needs across robotics and AI systems.
• Collaborate with ML and robotics engineers to define and deliver the data infrastructure required for cutting-edge model development and real-world deployment.
• Establish data governance, reproducibility, and lineage standards to ensure data integrity and traceability at scale.
• Develop data contracts and API specifications to ensure reliable data exchange between robotics systems, ML models, and downstream applications.
• Write production-grade, maintainable, and well-documented Python and SQL code for critical data workflows.
• Help shape our MLOps, observability, and CI/CD practices for continuous learning systems in physical environments.

• 5+ years of experience in data engineering, with a strong track record of building scalable data systems and infrastructure from the ground up.
• Previous experience supporting AI/ML teams with data platforms in fast-paced or startup environments.
• Deep proficiency in SQL, Python, and distributed data systems.
• Hands-on experience with tools like AWS, Snowflake, Dagster, dbt, or equivalent modern data stack.
• Experience with streaming technologies such as Kafka, Flink, or similar platforms for real-time data processing.
• Passionate about building clean, reliable data pipelines that power real-time ML and robotics workflows.
• Experience with data quality, observability, and production monitoring of data systems.
• Comfortable operating in ambiguity and taking ownership. You’re excited to build and own the foundation of a data-first company.
• Bonus: experience working with sensor data, robotics logs, time series, or other high-volume real-world datasets.

Why You’ll Love Working Here

• Daily free lunch to keep you fueled and connected with the team
• Flexible PTO so you can take the time you need, when you need it
• Comprehensive medical, dental, and vision coverage
• 6 weeks fully paid parental leave, plus an additional 6–8 weeks for birthing parents (12–14 weeks total)
• 401(k) retirement plan through Empower
• Generous employee referral bonuses—help us grow our team!

Who We Are

Regulatory and Compliance Requirements
This position may support work performed under U.S. Government contracts and requires compliance with applicable federal regulations, including FAR and DFARS where applicable.
The role may involve access to export-controlled information subject to ITAR and/or EAR. Candidates must be able to comply with U.S. export control regulations, which may include meeting the definition of a “U.S. Person” where required.
This position may also involve handling Controlled Unclassified Information (CUI) and requires adherence to company and federal data protection and confidentiality standards. Employment may be contingent upon successful completion of a background check consistent with applicable requirements.