Machine Learning Engineer (Robotics) (The Intelligent Automation Specialist)
Company: Unreal Gigs
Location: San Francisco
Posted on: November 15, 2024
Job Description:
Are you passionate about applying machine learning to robotics
to enable intelligent, autonomous behavior? Do you excel at
building and optimizing algorithms that empower robots to learn,
adapt, and perform complex tasks? If you're ready to create the
brains behind robotic systems, our client has the ideal role for
you. We're looking for a Machine Learning Engineer (Robotics) (aka
The Intelligent Automation Specialist) to develop and implement
machine learning models that advance the capabilities of robotic
systems.As a Machine Learning Engineer in Robotics at our client,
you'll collaborate with robotics, software, and data teams to
design algorithms that enhance navigation, perception, and
decision-making in real-world environments. Your work will be
central in creating robots that learn from their environments,
react to changing conditions, and continuously improve.Key
Responsibilities:
- Develop Machine Learning Models for Robotics Applications:
Build and train models for object recognition, obstacle detection,
navigation, and decision-making. You'll develop algorithms that
enable robots to interpret and respond to complex
environments.
- Implement Reinforcement Learning and Computer Vision
Algorithms: Utilize reinforcement learning and computer vision
techniques to enable autonomous robotic behavior and perception.
You'll create adaptive systems that improve performance over
time.
- Integrate ML Models into Robotic Systems: Work with software
and hardware teams to deploy ML models onto embedded platforms and
robotic hardware. You'll ensure models are optimized for real-time
performance and reliability.
- Optimize Algorithms for Real-Time Performance: Enhance model
efficiency to run effectively on limited computational resources.
You'll refine and compress algorithms to achieve high performance
within embedded or edge environments.
- Collect and Process Training Data: Gather and preprocess data
from robotic sensors (e.g., cameras, LIDAR, IMUs) for training and
testing. You'll ensure that data is clean, labeled, and prepared
for robust model training.
- Conduct Simulation and Testing of ML-Driven Behaviors: Use
simulation environments and real-world tests to validate ML model
performance. You'll monitor, troubleshoot, and optimize models to
handle edge cases and variability in real-time applications.
- Stay Updated on AI and Robotics Trends: Keep current with
advancements in machine learning, computer vision, and AI as
applied to robotics. You'll integrate cutting-edge techniques to
maintain a competitive edge in robotic intelligence.Required
Skills:
- Proficiency in Machine Learning and Deep Learning: Extensive
experience with ML/DL frameworks like TensorFlow, PyTorch, or
Keras, specifically applied to robotics or autonomous systems.
- Expertise in Computer Vision and Reinforcement Learning: Strong
knowledge of computer vision techniques (e.g., object detection,
segmentation) and reinforcement learning for enabling adaptive
behaviors in robots.
- Programming Skills in Python and C++: Proficiency in Python for
model development and C++ for integration into robotic systems and
real-time applications.
- Data Processing and Model Optimization: Experience with data
cleaning, preprocessing, and model optimization techniques to
maximize performance on embedded hardware.
- Analytical and Problem-Solving Skills: Strong troubleshooting
skills for debugging ML models, analyzing performance data, and
implementing improvements in complex systems. Educational
Requirements:
- Bachelor's or Master's degree in Computer Science, Robotics,
Machine Learning, or a related field. Equivalent experience in ML
and robotics may be considered.
- Relevant certifications or coursework in machine learning, AI,
or computer vision are advantageous. Experience Requirements:
- 3+ years of experience in machine learning engineering, with a
focus on robotics or autonomous systems.
- Experience with robotic operating systems like ROS (Robot
Operating System) and familiarity with simulation environments
(e.g., Gazebo) is beneficial.
- Familiarity with embedded ML deployment (e.g., TensorFlow Lite,
NVIDIA Jetson) is a plus.
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Keywords: Unreal Gigs, Fremont , Machine Learning Engineer (Robotics) (The Intelligent Automation Specialist), Engineering , San Francisco, California
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