Edge AI Scientist - Real-Time Multimodal ML

Tacit; San Francisco (CA); On-site; USD 180,000 - 270,000; Full time

Benefits offered by this job

Competitive equity package

Medical, dental, and vision insurance

Unlimited PTO

Visa sponsorship

4% 401k matching

Job summary

You will publish or deploy models in real‑world systems, collaborate with hardware engineers and neuroscientists, and thrive in a fast‑moving startup environment with ambitious goals.

Qualifications

• PhD in CS/ML/Neuroscience or equivalent industry experience.
• Expertise in deep learning frameworks (PyTorch/TensorFlow) and fluency in Python.
• Track record of publishing or deploying ML models in real-world systems.
• Independent work ethic, flexibility, and resourcefulness.
• Effective communication and collaboration skills.
• Comfortable in a fast-moving startup environment, eager to build independently.

Responsibilities

• Design and implement state-of-the-art machine learning algorithms for processing multimodal biosignals from custom hardware.
• Build and optimize neural network architectures.
• Develop and evaluate multimodal learning techniques to fuse information from multiple sensors.
• Iterate rapidly on model prototypes for real-time inference on custom hardware.
• Create and maintain a robust evaluation framework for benchmarking performance across datasets.
• Collaborate with hardware engineers, neuroscientists, and product teams to align models with user needs.

Skills

PhD or equivalent

Python

Deep learning

Publications

Startup adaptability

Communication skills

Education

PhD in CS/ML/Neuroscience

Tools

PyTorch

TensorFlow

Python

Job description

You will publish or deploy models in real‑world systems, collaborate with hardware engineers and neuroscientists, and thrive in a fast‑moving startup environment with ambitious goals.