Senior Machine Learning Engineer, Diligent Robotics
Robotics
AI-powered robots for patient care teams
Job no longer available
AI-powered robots for patient care teams
101-200 employees
Job no longer available
101-200 employees
Company mission
To make technical advances towards robots and humans working together side by side, with an emphasis on human-centric design.
Role
Who you are
- Master’s or PhD in Computer Science, Robotics, Machine Learning, or related field
- 5+ years of experience in applied machine learning, computer vision, or robotics perception
- Strong background in deep learning frameworks (PyTorch, TensorFlow, JAX)
- Hands-on experience with real-time perception/navigation tasks (detection, tracking, segmentation,path planning)
- Expertise in one or more sensor modalities: RGB/depth cameras, LIDAR, radar, or multimodal fusion
- Experience deploying ML models on edge/embedded hardware (e.g., Jetson, TPU, ARM-based platforms)
- Familiarity with SLAM, mapping, and navigation pipelines
- Solid software engineering skills in Python and C++ for ML system integration
- Proven ability to take ML models from research prototype to production deployment
- Strong debugging skills for diagnosing ML performance gaps in fielded systems
What the job involves
- As a Sr ML Engineer, Perception / Robotics, you will develop, deploy, and optimize machine learning models that enable robots to understand and navigate complex human environments
- You will lead the design of ML systems, from sensor fusion to real-time inference, ensuring robustness in safety-critical, real-world deployments
- Develop and deploy ML models for perception/navigation tasks such as object detection, semantic segmentation, tracking, scene understanding, localization, and path prediction
- Design and implement sensor fusion and mapping pipelines combining vision, depth, LIDAR, IMU, and other signals for robust perception and navigation in dynamic spaces
- Build real-time ML inference pipelines optimized for robotic hardware and embedded compute
- Setup data collection, labeling strategies, dataset curation, and synthetic data augmentation for training and evaluation
- Establish metrics, benchmarks, and test frameworks to validate ML models in both simulation and real-world environments
- Collaborate with robotics software engineers to integrate perception and navigation intelligence into autonomy stacks
- Work with operations to analyze field data, diagnose performance gaps, and iterate on model improvements
- Contribute to long-term ML and perception and navigation architecture decisions, influencing the roadmap for future robots
- Mentor junior ML engineers and contribute to building strong applied ML best practices within the team
Our take
Healthcare workers do everything they can to provide high-quality care to patients, but the high-pressure work environment can make this difficult. Whilst in-person care is their most important job, different scenarios will require workers to constantly fetch different medical items for patients, increasing job pressure and restricting the time workers have to spend with patients.
Diligent Robotics develops AI-powered robots for patient care teams called Moxi that can fetch, store, and deliver items needed within healthcare facilities. The robots have specialized storage compartments for sensitive medical materials and can safely navigate through elevators, security doors, automatic doors, and other existing infrastructure.
Whilst AI is becoming increasingly prevalent in healthcare, Diligent Robotics has taken a bold step by developing AI-driven robots that reduce the burden of item fetching for healthcare workers. Its Moxi robots now operate in more than 25 hospitals and have completed over 1.5M tasks, showing strong real-world traction. This success was further reinforced by Serve Robotics acquisition of the company, which aims to accelerate Moxi's development and expand the future of AI-powered healthcare support.
Freddie
Company Specialist at Welcome to the Jungle
Insights
70% employee growth in 12 months
Company
Funding (last 2 of 6 rounds)
Sep 2023
$25m
LATE VC
Apr 2022
$30m
SERIES B
Total funding: $70.9m
Company benefits
- Competitive salary and equity based on experience and contribution
- Competitive health plan coverage for individuals and dependents
Company HQ
North Side, Austin, TX
Leadership
Andrea L. Thomaz
(Co-Founder & CEO)Andrea has been an Associate Professor at The University of Texas since 2016. Previously, they were an Assistant then Associate Professor at the Georgia Institute of Technology.
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