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Machine Learning Scientist

Tacit
San Francisco, California, United StatesFull timePosted today
Location
San Francisco, California, United States
Type
Full time
Salary
$180,000 - $270,000/year

About Tacit

We are an early-stage, deep tech startup based in San Francisco, developing innovative hardware that rethinks human-computer interaction. We are backed by General Catalyst, Khosla Ventures, and Greylock Partners, with a founding team from Stanford, BrainGate, Oculus, and Tesla. While we can't reveal too much just yet, our team is tackling cutting-edge engineering challenges to bring revolutionary products to life.

About the Role

As a Machine Learning Scientist, you will develop cutting-edge AI models to integrate and decode complex, multimodal data streams from our custom sensing hardware. You'll play a pivotal role in advancing our technology stack by building and optimizing models for real-time applications. This position spans foundational research in deep learning, hands-on model development, and applying algorithms to scale across diverse data sources and users.

Responsibilities

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

Requirements

  • PhD in computer science, machine learning, computational neuroscience, or related fields (or equivalent industry experience).
  • Expertise in deep learning frameworks (e.g., PyTorch, TensorFlow) and fluency in Python.
  • Track record of publishing or deploying machine learning models in real-world systems.
  • Independent work ethic, flexibility, and resourcefulness.
  • Effective communication and collaboration skills.
  • Comfortable in fast moving startup environment, excited to build independently.

Preferred Qualifications

  • Familiarity with human-machine interaction systems such as automatic speech recognition or neural interfaces.
  • Hands-on experience with consumer wearables or custom hardware.
  • Knowledge of low-latency inference techniques and model optimization for edge devices.

Details

  • Position type: Full time, onsite in San Francisco (SOMA)
  • Company size: 30–40 people

Compensation and Benefits

  • Salary range: $180,000–$270,000/year
  • Equity: Competitive equity package
  • Insurance: Comprehensive medical, dental, and vision insurance
  • Time off: Unlimited PTO
  • Visa sponsorship: Available
  • 401k matching: 4%

About Tacit

Tacit is an early-stage deep tech startup developing innovative hardware that rethinks human-computer interaction. The company builds custom sensing hardware paired with machine learning to process multimodal biosignals and enable novel human-computer interfaces.

Industry
Hardware; Deep Tech
Head office
San Francisco, California
Company size
30-40
Hardware developmentMachine learning for biosignalsHuman-computer interactionCustom sensing technology
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