Job description

Joby Advanced Development designs, develops, and flight-tests novel aircraft using a software-first autonomy approach. We build and deploy autonomy, perception, planning, and radar systems across conventional, electric, and hydrogen-electric aircraft in both CTOL and VTOL configurations. Joby Advanced Development is seeking a Autonomy Senior Data Scientist, to build the AI data and evaluation platform for our Superpilot™ autonomy stack. This position offers a unique opportunity to design and build the AI data science solutions that power Joby’s varied fleet of autonomous aircraft. In this role, you will develop data-centric AI solutions to autonomy problems, involving data engineering and machine learning. The role requires broad industry experience and deep technical knowledge of data science and data engineering. You will build robust software for flight telemetry, sensor, and imagery data, turning raw logs, collected data, and synthetic data into reliable AI datasets, metrics, and workflows that support development, validation, and deployment. Further, you will also build AI solutions using this data to solve autonomy problems in perception and other applications. Your work will help teams develop algorithms, detect regressions, investigate edge cases, and validate safety-critical behavior long before it reaches flight operations. We are a small, high-impact team that values curiosity, technical initiative, and the ability to operate independently. You will collaborate deeply with perception, controls, and flight software engineers to build a foundation that accelerates our path to safe, autonomous flight. The right candidate is a strong AI data scientist who cares deeply about system design, reliability, developer experience, and enabling fast, safe iteration across multiple aircraft programs. • AI Data Annotation and Curation • Design, implement, and maintain a scalable auto-labeling pipeline for a heterogeneous fleet of aircraft and simulators and their associated imagery and data • Design, implement, and maintain a scalable data quality pipeline for curating, filtering, and analyzing data for autonomy data • Develop data-centric algorithms and software to catalog the data (metadata, anomaly detection, missing data) • AI Data Evaluation and Analysis • Build the AI data software that transforms raw flight and simulation data into trustworthy metrics, curated datasets, and actionable engineering insight • Develop scalable pipelines for AI algorithm evaluation, analysis, and visualization • AI Solutions Development • Design and develop data-centric AI solutions for autonomy problems in perception and decision-making • Proactively explore the data, develop new metrics, interpret trends, and investigate anomalies in data from both real world and simulation • Collaborate closely with the rest of the Superpilot™ team to ideate, plan and execute on high-quality, well-integrated solutions and feature • Monitor system health and performance, proactively addressing issues and providing user support • Degree in computer science, aerospace engineering, or related field • 8+ years of experience in data science • Expertise in machine learning model development, evaluation, and deployment • Expertise in data analytics, dashboards, and visualization • Experience in building dataset management solutions, platforms, and infrastructure • Strong proficiency in Python and Git within a Linux-based environment • Experience with cloud data and compute (AWS, GCP, Azure) • Proven ability to document complex technical designs, architectural trade-offs, and implementation roadmaps • Champion of software best practices, including rigorous code reviews and mentorship • Excellent communication skills for collaborating with cross-functional teams This position must meet US export control compliance requirements, therefore a candidate must qualify as a “US Person” as defined by 22 C.F.R. § 120.15. “US Person” includes US Citizens, lawful permanent residents, refugees, or asylees. • Expert-level software engineering: deep expertise in architecting and writing clean, scalable, and maintainable code • Experience data engineering infrastructure, platforms, tools • Experience processing high-bandwidth sensor data from robotics such as cameras, lidar, radar • Experience in processing aircraft data such as GPS, inertial, air data, radio data • Experience with MLOps and DevOps to deploy ML models in a production environment using tools such as MLflow, Dagster, Docker, Kubernetes Compensation at Joby is a combination of base pay and Restricted Stock Units (RSUs). The target base pay for this position is $149,900 - $202,600/yr . The compensation package will be determined by job-related knowledge, skills, and experience. Joby also offers a comprehensive benefits package, including paid time off, healthcare benefits, a 401(k) plan with a company match, an employee stock purchase plan (ESPP), short-term and long-term disability coverage, life insurance, and more. Joby Aviation is an equal opportunity employer.

Requirements

Must-haves

AI Data Annotation and Curation • Design, implement, and maintain a scalable auto-labeling pipeline for a heterogeneous fleet of aircraft and simulators and their associated imagery and data
Design, implement, and maintain a scalable data quality pipeline for curating, filtering, and analyzing data for autonomy data
Develop data-centric algorithms and software to catalog the data (metadata, anomaly detection, missing data)
AI Data Evaluation and Analysis • Build the AI data software that transforms raw flight and simulation data into trustworthy metrics, curated datasets, and actionable engineering insight
Develop scalable pipelines for AI algorithm evaluation, analysis, and visualization
AI Solutions Development • Design and develop data-centric AI solutions for autonomy problems in perception and decision-making
Proactively explore the data, develop new metrics, interpret trends, and investigate anomalies in data from both real world and simulation
Collaborate closely with the rest of the Superpilot™ team to ideate, plan and execute on high-quality, well-integrated solutions and feature
Monitor system health and performance, proactively addressing issues and providing user support
Degree in computer science, aerospace engineering, or related field
8+ years of experience in data science
Expertise in machine learning model development, evaluation, and deployment
Expertise in data analytics, dashboards, and visualization
Experience in building dataset management solutions, platforms, and infrastructure
Strong proficiency in Python and Git within a Linux-based environment
Experience with cloud data and compute (AWS, GCP, Azure)
Proven ability to document complex technical designs, architectural trade-offs, and implementation roadmaps
Champion of software best practices, including rigorous code reviews and mentorship
Excellent communication skills for collaborating with cross-functional teams
Expert-level software engineering: deep expertise in architecting and writing clean, scalable, and maintainable code
Experience data engineering infrastructure, platforms, tools
Experience processing high-bandwidth sensor data from robotics such as cameras, lidar, radar
Experience in processing aircraft data such as GPS, inertial, air data, radio data
Experience with MLOps and DevOps to deploy ML models in a production environment using tools such as MLflow, Dagster, Docker, Kubernetes

Nice-to-haves

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Application prep

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Keywords to mirror

aimachine learningrestpythonawsgcpazuremldockerkubernetes

Platform: icims
Effort: medium

Benefits

Benefits detected in the listing.

401(K)

Paid Time Off