AI Research Engineer — Adaptive Sensing & Imaging

Elio; San Mateo (CA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Medical, dental & vision

401(k) program

Cutting-edge research projects

Impact in sensing

Job summary

Elio, based in San Mateo, CA, is seeking an experienced AI Research Engineer to join the AI & Data Science team and advance imaging and sensing technologies. This role sits at the intersection of computer vision, representation learning, and reinforcement learning in a full-time, on-site capacity.

You will work on learning real-time acquisition policies, building transferable representations across modalities, and collaborating with scientific and engineering teams to deploy scalable,

Qualifications

• PhD in CS/EE or related field required.
• 8+ years of AI/ML research, engineering, or data science experience.
• Strong publication record in computational methods or ML.
• Expert Python and PyTorch skills; familiarity with pandas and scikit-learn.
• Experience with cloud infrastructure (AWS) is a plus.
• Excellent communication and collaboration in a fast-paced startup.

Responsibilities

• Research, develop, and ship novel AI algorithms for Elio's adaptive sensing platform.
• Design, build, and validate pipelines for imaging and sensing applications.
• Own technical problems end to end from hypothesis to results communication.
• Collaborate across teams to translate research into production-grade capabilities.
• Track emerging AI research and contribute ideas to strengthen technical edge.

Skills

Python

PyTorch

Pandas

Scikit-learn

Education

Ph.D. in Computer Science, Electrical Engineering, or related field

Tools

AWS

Docker

Job description

Elio, based in San Mateo, CA, is seeking an experienced AI Research Engineer to join the AI & Data Science team and advance imaging and sensing technologies. This role sits at the intersection of computer vision, representation learning, and reinforcement learning in a full-time, on-site capacity.

You will work on learning real-time acquisition policies, building transferable representations across modalities, and collaborating with scientific and engineering teams to deploy scalable,