Software Engineer, Machine Learning Deployment and GPU Development

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Overview

Scythe Robotics is seeking a talented Software Engineer specializing in Machine Learning Deployment and GPU Development to join our dynamic team. The successful candidate will be integral in developing and optimizing algorithms for real-time processing and execution on GPU platforms, aiming to enhance our robotics capabilities. You will collaborate with data scientists, software engineers, and hardware developers to ensure the seamless integration of machine learning models into robotic systems, with a focus on performance, scalability, and reliability.

Job Responsibilities

• Design, develop, and optimize machine learning algorithms for deployment on GPU architectures.
• Collaborate with cross-functional teams to integrate machine learning models into robotics applications.
• Write clean, maintainable, and efficient code following best practices in software development.
• Conduct performance analysis and model evaluation to ensure robustness and scalability.
• Develop and maintain documentation for systems and processes to facilitate knowledge sharing.
• Stay updated with the latest advancements in machine learning and GPU technologies to incorporate innovative solutions.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
• Proficient in programming languages such as Python, C++, or Java.
• Strong experience with machine learning frameworks such as TensorFlow, PyTorch, or Keras.
• Expertise in parallel computing, specifically with NVIDIA CUDA or OpenCL.
• Solid understanding of algorithms and data structures.
• Experience with version control systems, preferably Git.
• Excellent problem-solving skills and the ability to work in a fast-paced environment.

Technologies & Tools

The Software Engineer will utilize a variety of technologies and tools including, but not limited to, NVIDIA GPUs, TensorFlow, PyTorch, CUDA, CMake, Docker, and cloud computing platforms such as AWS or Google Cloud. Familiarity with robotics simulation tools and data pipelines will also be beneficial for optimizing workflows and model deployment.

Ideal Candidates

The ideal candidate for this position is innovative, detail-oriented, and possesses a strong passion for robotics and machine learning. They should be an effective communicator capable of collaborating in a team-oriented environment while also having the drive to work independently. A keen analytical mindset and the ability to adapt to new challenges and technologies quickly is essential. Strong organizational skills and a commitment to delivering high-quality work are also characteristics that will make a candidate successful in this role.