ML Engineer Intern - Perception Autolabeling

SupportFinity™; United States; On-site; USD 41,328 - 75,768; Full time

Job summary

SupportFinity™ is offering an internship for a Machine Learning Engineer focusing on perception autolabeling. Interns will work alongside seasoned ML Engineers to enhance autolabeling capabilities through integration of advanced ML architectures.

This role is ideal for passionate individuals pursuing a Masters or PhD in relevant fields. The position is set to begin in May or June 2026, offering a competitive hourly pay between $30 and $55.

The internship promises hands-on experience in a professional setting, honing skills essential for future careers in autonomous driving technology.

Qualifications

• Currently pursuing a Masters or a PhD degree in Computer Science, Computer Engineering, or a similar discipline.
• Proven ability to develop ML models for 3D data processing.
• Strong programming skills in Python.
• Good communication skills.

Responsibilities

• Conduct research to integrate ML components into the auto-labeling pipeline.
• Prepare datasets for model development and validation.
• Collaborate with a ML Engineer.
• Gain hands-on experience with production-level data.
• Summarize findings in a comprehensive final report.

Skills

Proven ability to develop ML models

Strong programming skills in Python

Good written and verbal communication skills

Passion for self-driving car technology

Education

Masters or PhD in Computer Science or similar

Tools

PyTorch

Job description

SupportFinity™ is offering an internship for a Machine Learning Engineer focusing on perception autolabeling. Interns will work alongside seasoned ML Engineers to enhance autolabeling capabilities through integration of advanced ML architectures.

This role is ideal for passionate individuals pursuing a Masters or PhD in relevant fields. The position is set to begin in May or June 2026, offering a competitive hourly pay between $30 and $55.

The internship promises hands-on experience in a professional setting, honing skills essential for future careers in autonomous driving technology.