Real-Time Hand Tracking ML Intern — Edge AI (20ms)

Wayne State University; Austin (TX); On-site; USD 20,000 - 30,000; Full time

Benefits offered by this job

Paid internship

Job summary

A leading research institution is offering a project-based internship in Austin, TX, focusing on building innovative neural mapping for hand intent translation. The role encompasses developing deep models and optimizing inference engines while ensuring low-latency performance. Candidates should demonstrate proficiency in PyTorch, ONNX optimization, and have a passion for biological signals and their applications in robotics. This paid position runs through mid-May 2026 on-site in Austin.

Qualifications

• Advanced proficiency in PyTorch with hands‑on experience in time‑series or biological signal modeling.
• Expertise in ONNX optimization and edge‑device model deployment.
• Familiarity with biomechanical constraints and skeletal rigging logic.
• Fluent in English, written and spoken.

Responsibilities

• Build the sEMG-to-Kinematic labeling pipeline using MediaPipe.
• Develop and train deep temporal models for hand skeletal regression.
• Deploy and optimize inference engines to meet latency requirements.

Skills

PyTorch

ONNX optimization

sEMG signal modeling

TensorRT

QAT

biomechanical constraints

skeletal rigging logic

English fluency

Job description

A leading research institution is offering a project-based internship in Austin, TX, focusing on building innovative neural mapping for hand intent translation. The role encompasses developing deep models and optimizing inference engines while ensuring low-latency performance. Candidates should demonstrate proficiency in PyTorch, ONNX optimization, and have a passion for biological signals and their applications in robotics. This paid position runs through mid-May 2026 on-site in Austin.