Machine Learning Software Engineer

Benefits

Parental leave

Not verified

Non-birth-parent leave

Not verified

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

Not verified

Verification

Not verified

Salary

Not verified

401(k) match

Not verified

Was this benefit information wrong? Tell us.

Schedule

Shift type

Not verified

Weekend work

Not verified

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Machine Learning Software Engineer Remote, United States About Us: Swan delivers the future of defense and industry through scalable autonomous products. Swan is backed by leading defense VCs including a16z's American Dynamism fund. Role Overview: We are seeking an expert Machine Learning Engineer with deep experience in computer vision, model optimization, and deployment on low-cost embedded systems. The ideal candidate will have a strong background in designing, training, and optimizing deep learning models for real-time applications. This role requires expertise in efficient neural network architectures, quantization, model compression, and hardware acceleration techniques to run ML models on resource-constrained devices. Key Responsibilities: - Design, develop, and optimize computer vision models for real-time applications on embedded systems. - Implement model compression techniques such as quantization, pruning, and knowledge distillation to improve performance on low-power hardware. - Deploy machine learning models on embedded platforms, including ARM, NVIDIA Jetson, Qualcomm, or custom ASICs. - Write clean, efficient, and well-documented code in Python and C++, leveraging ML frameworks like TensorFlow, PyTorch, and ONNX. - Develop and fine-tune SLAM, object detection, tracking, and feature extraction models for high efficiency. - Collaborate with cross-functional teams to integrate ML models into production systems, optimizing for latency, accuracy, and power consumption. - Benchmark and profile ML models to identify and implement optimizations for inference on embedded hardware. - Research and apply cutting-edge ML techniques to improve real-time performance in resource-constrained environments. Qualifications and Skills: - Master's or Ph.D. in Computer Science, Electrical Engineering, Machine Learning, or a related field.

Read the full description at jobs.ashbyhq.com. FewerJobs shows a source-linked preview and links to the original posting.