---
title: 'Machine Learning Scientist at Tacit'
canonical: 'https://feeny.ai/job/machine-learning-scientist-tacit-san-francisco-pt1w314e43ge'
type: 'job'
last_seen: '2026-09-09'
---

# Machine Learning Scientist at Tacit

- **Company:** Tacit
- **Location:** San Francisco, CA
- **Compensation:** $180k–$270k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-07-23
- **Last confirmed live:** 2026-09-09
- **Apply:** https://jobs.ashbyhq.com/tacit/0134f596-4493-4658-ba09-6a5b201959c3

## Job description

## 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:

- This position is full time, onsite in San Francisco (SOMA)
- Company size: 30-40 people

## Compensation Range

$180,000 - $270,000/year

## BENEFITS

- Competitive equity package
- Comprehensive medical, dental, and vision insurance
- Unlimited PTO
- Visa sponsorship
- 4% 401k matching

## About Tacit

## Company Overview
- **One-liner**: An early-stage, stealth deep tech startup based in San Francisco, developing innovative hardware that rethinks human-computer interaction, with a focus on neurotechnology and Edge AI.
- **Entity Type**: Private (Early Stage, Stealth)
- **Headquarters**: San Francisco, California, United States
- **Founded**: Not publicly available
- **Founders**: Not publicly available (founding team includes alumni from Stanford, BrainGate, Oculus, and Tesla)

## Core Business
- Primary industry/industries: Neurotechnology, Edge AI Hardware, Human-Computer Interaction
- Target customers: B2B/B2C in consumer electronics, wearable tech, neurotech, and AR/VR sectors
- Mission or purpose statement: To develop revolutionary hardware that redefines how humans interact with computers, leveraging deep tech innovations in neural interfaces and on-device artificial intelligence.

## Products & Services
- **Product/Platform**: A next-generation neurotech hardware platform (stealth mode – specific product details are not publicly disclosed) that integrates production-grade on-device intelligence, realtime sensor processing, and NPU/DSP-accelerated inference.

## Market Standing
- **Valuation/Market Cap**: Not disclosed (stealth startup)
- **Key Metric**: Total Funding – Backed by top-tier venture firms (General Catalyst, Khosla Ventures, Greylock Partners) but specific funding amounts are not publicly available.
- **Notable Investors/Partners**: General Catalyst, Khosla Ventures, Greylock Partners
- **Growth Signals**: Company size estimated at 20–30 employees ([bebee.com](https://bebee.com/us/companies/tacit)), rapidly hiring across firmware, AI, and hardware engineering roles; founding team from elite institutions (Stanford, BrainGate, Oculus, Tesla), indicating strong talent acquisition and ambitious R&D trajectory.

## Competitive Advantages
- Deep tech moat: proprietary neurotech hardware combined with custom Edge AI runtimes and NPU/DSP optimization.
- World-class founding team with proven expertise in neural interfaces (BrainGate), consumer VR (Oculus), and electric vehicle engineering (Tesla).
- Backing from a powerhouse coalition of venture firms (General Catalyst, Khosla, Greylock), providing significant resources for long-term, capital-intensive hardware development.
- Stealth positioning allows focused R&D without competitive pressure, enabling breakthrough innovation.

## Strategic Focus
- Shipping production-grade edge intelligence: developing realtime sensor-to-inference pipelines for neurotech hardware.
- Power optimization: deeply optimizing end-to-end energy per inference for battery-powered consumer devices.
- Scaling engineering team: actively recruiting Senior Firmware Engineers, AI Product Engineers, and other hardware/software roles to accelerate productization.
- Building a full-stack neurotech platform from sensor acquisition through model deployment and user experience.

## Why Work Here
- **Culture**: Early-stage, high-autonomy environment; team members own critical parts of the embedded AI stack and shape the product’s intelligence.
- **Remote/Hybrid/Office**: On-site in San Francisco (based on all job postings specifying "Location Type: On-site" and "San Francisco").
- **Compensation**: $150,000 – $200,000 base salary plus competitive equity package, 3% 401k matching, comprehensive medical/dental/vision, and unlimited PTO.
- **Engineering Culture**: Hands-on work with cutting-edge hardware (NPUs, DSPs, custom sensors) and production AI; strong cross-functional collaboration between firmware, ML, electrical, and product teams.
- **Visa Sponsorship**: Offered for qualified candidates.
- **Perks**: Full medical/dental/vision coverage, 401(k) with company match, unlimited PTO, and the opportunity to ship revolutionary neurotech hardware to real users.

## Sources
1. [Tacit Careers Page (Ashby)](https://jobs.ashbyhq.com/tacit/62712a3e-e5b8-4884-9450-aae4d2dfa45c)
2. [BeBee - Tacit Company Profile](https://bebee.com/us/companies/tacit)
3. [Jobright.ai - Tacit AI Product Engineer Posting](https://jobright.ai/jobs/info/6971dbb2b707bf728a4b654d)
4. [Indeed.com - Tacit Careers and Employment](https://www.indeed.com/cmp/Tacit)
5. [Tacit AI Official Website (Tacit AI)](https://tacitx.ai/about/) – *(Note: this domain appears distinct from tacit.ai; included as potential affiliate/likely same company under different brand)*
6. [Tacit Official Website](https://tacit.ai/)

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