Forward Deployed Engineer

Maxinsights Corporation; Santa Clara (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Maxinsights Corporation seeks a Forward Deployed Engineer to bridge robotics data engines with Embodied AI and World Model R&D teams worldwide. You’ll define precise dataset specifications, plan diverse data scenarios, and orchestrate large-scale data synthesis using advanced simulators and tools.

The role emphasizes software-driven data curation, rigorous QA, and close collaboration with researchers to accelerate generalizable learning for client robots.

Qualifications

• Proficient in Python with strong software engineering practices.
• Experience with large-scale multimodal data processing tools and ML datasets.
• Solid foundation in 3D spatial mathematics and robotics concepts.
• Hands-on project experience with physics simulators or world-model tools is preferred.
• Knowledge of Embodied AI foundation models or autonomous driving perception pipelines is a plus.

Responsibilities

• Interface with Embodied AI/World Model researchers to define dataset specs and data dimensions.
• Plan data distribution including long-tail and OOD scenarios for generalizability.
• Orchestrate data synthesis using Maxinsights' 3D engines or generative tools; script trajectory and perception data generation.
• Oversee data curation, filtering, calibration, and QA across massive data frames and formats.
• Maintain cross-team alignment and data-to-model feedback throughout early client training.

Skills

Python programming

Data engineering

3D spatial math

Simulation/graphics

Autonomous robotics background

Tools

Git

Docker

Shell

Pandas

NumPy

HDF5

Job description

As a Forward Deployed Engineer (FDE - Robotics Data Direction) at Maxinsights, you will serve as the technical bridge connecting our world-leading robotics foundation model data engine with top-tier Embodied AI and World Model R&D teams globally.

While traditional FDE roles typically focus on on-site physical hardware installation and driver debugging, our technology at Maxinsights has achieved a high degree of data streaming and simulation. This role is 100% data- and software-driven, involving absolutely no on-site physical hardware deployment or mechanical debugging.

Your core mission is to deeply understand clients' academic and commercial requirements, acquire and align dataset specifications (Specs), design and produce high-quality multimodal motion and scene simulation data, execute rigorous data governance, and conduct agile, high-frequency iterative validations both within and outside the team. Your work will directly ensure that the delivered data accelerates the generalizability learning of our clients' robots.

Core Responsibilities

1. Client Requirement Interfacing & Specification Definition

   Communicate directly with Embodied AI and World Model researchers to thoroughly analyze their large models' architectural requirements for input data (e.g., perception camera FOV, LiDAR precision, robotic arm dynamic constraints, and specific action trajectory formats).

   Translate ambiguous business and scientific research pain points into high-precision "Dataset Specifications" (Specs), explicitly defining data dimensions, sensor parameters, control command action spaces, and metadata formats.

2. Data Distribution Planning & Scene Design

   Plan and organize the distribution of target datasets, balancing routine scenarios with long-tail scenarios (corner cases) to ensure the datasets possess strong generalizability and cover Out-Of-Distribution (OOD) extreme operating conditions.

   Analyze historical or public datasets provided by clients to identify data gaps in geography, lighting, action types, and obstacle distribution, and perform targeted data completion.

3. Data Production & Synthesis Orchestration

   Utilize and extend Maxinsights' 3D simulation engines (such as Isaac Sim, MuJoCo, etc.) or generative world model tools to orchestrate and run large-scale data synthesis pipelines.

   Write efficient scripts (Python/Bash) to automatically generate customized robot trajectories, multi-angle perception video streams, 3D point clouds, and dynamics states.

4. Data Curation & Quality Governance

   Responsible for data curation, filtering, and calibration, eliminating invalid data such as physical collision errors, transient sensor disconnects, or action drifts.

   Write automated QA scripts to perform static and dynamic quality inspections on tens of millions of data frames across dimensions including dynamics reachability, temporal alignment, and label accuracy.

   Oversee the final format packaging of datasets (e.g., converting trajectory data into MCAP, HDF5, or LeRobot formats) to guarantee seamless, direct ingestion into training pipelines.

5. Closed-Loop Delivery & Continuous Cross-Team Alignment

   Take ownership of data delivery and follow up to evaluate data efficacy during the early stages of client model training, establishing a closed-loop "data-to-model performance" feedback mechanism.

   Maintain daily, high-frequency communication internally with the Algorithm R&D and Platform Development teams, abstracting system-level bugs or shared requirements discovered during frontline deployment to drive the standardized upgrade of Maxinsights' core data engine.

Job Qualifications

Technical Requirements

Programming Foundations: Proficient in Python programming with excellent software engineering literacy (proficient in the use of tools like Git, Docker, Shell, etc.).

Data Engineering Experience: Skilled in using large-scale multimodal data processing tools (e.g., Pandas, NumPy, Arrow, HDF5, and RLDS/TensorFlow Datasets structures).

Spatial & Motion Geometry: Possess a solid foundation in 3D spatial mathematics, understanding 3D rotations (quaternions, rotation matrices), coordinate system transformations, forward/inverse kinematics (FK/IK) of robotic arms, and sensor intrinsic/extrinsic parameters.

Simulation & Graphics (Preferred Bonus): Hands-on project experience using physics simulators like Isaac Sim, MuJoCo, PyBullet, Unity/Unreal Engine, or NeRF/3DGS/generative world models is highly preferred.

Autonomous Driving/Robotics Background (Preferred Bonus): Understanding autonomous driving perception/planning and control pipelines, or the training and evaluation logic of Embodied AI foundation models (e.g., VLA, RT-2, etc.), is highly preferred.

Comprehensive Soft Skills

Cross-Team Coordination & Communication: Possess exceptional technical communication skills, capable of seamlessly aligning complex technical boundaries and delivery Specs with both top AI researchers and non-technical business personnel.

Stress Tolerance & Ownership: Self-driven; able to maintain a results-oriented mindset and proactively drive projects forward amidst the rapid iterations and ambiguous requirement definitions typical of a startup environment.

Explicitly Excluded Scopes

The following functions have been stripped from previous versions of this role and no longer form part of this position's requirements:

No requirement to participate in any on-site assembly, mechanical structure maintenance, or electrical wiring of robot hardware.

No requirement to perform physical calibration of hardware chassis and sensors (the focus is purely on software-level calibration data calculation and alignment).

No requirement to write or debug low-level hardware drivers, MCU firmware, or physical hardware interfaces.

No requirement to handle client-side infrastructure setup (such as network cabling, physical server racking, etc.).