Data scientist jobs in Pacifica, CA and nearby

Data scientist jobs within 25 miles of Pacifica, CA. Nearby towns and cities are included. Distances are straight-line, not driving distances.

Counted Nov 1, 2026

Hiring at a glance

View jobs

Open jobs: 620
Employers: 292

Advertised starting pay

Average starting payUSD / year: $196,019Across 204 listings
Average starting payUSD / hour: $67.14Across 14 listings

Employer-advertised starting pay, not employee salaries. Currencies and pay periods stay separate.

Where work happens

Remote: 0%0 listings
Hybrid: 24%150 listings
On-site: 15%94 listings

Not specified: 61% (376 listings)

Employers hiring include Waymo (30), OpenAI (16), Uber (16).

Sources & calculation notes

These figures describe the listings on this role page at the date shown, not the whole job market. Listings can change.

Employer-listed minimums from at least 10 listings per currency and pay period. These are advertised starting amounts, not employee salaries. Jobs without a minimum and unusual amounts are excluded.

Hybrid and on-site classifications may be inferred from descriptions. Check the original ad. How we count

Data scientist jobs in Pacifica, CA and nearby

Within 25 miles

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Added 10 days ago
Lead Machine Learning Engineer-MLOps Vice President
JPMC page
Palo Alto, CA
We are looking for a Senior MLOps engineer to work closely with Data Scientists to build and deploy ML models on a modern MLOps stack.
Added 10 days ago
Senior Machine Learning Engineer, Simulation
Waymo
San Francisco, CA
Added 10 days ago
V
Product Data Scientist
Vinci
Palo Alto, CA
- $240,000 to $260,000 USD / year
Added 10 days ago
Staff Data Scientist, Marketing Analytics
Chime Financial, Inc
San Francisco, CA
Added 10 days ago
Senior Machine Learning Engineer, Scenes, Traffic Controls
Waymo
San Francisco, CA
Added 10 days ago
Machine Learning Engineer III, Shield
Box
Redwood City, CA
Added 10 days ago
M
Data Scientist, Product Analytics, XBOX Growth
Microsoft
San Francisco, CA
- $102,100 to $219,200 USD / year
XBOX Growth Intelligence is seeking a Data Scientist, Product Analytics to partner with Product, Engineering, and cross-functional business owners to improve XBOX experiences through…
Added 10 days ago
M
Senior Data Scientist - Product Analytics - XBOX Growth
Microsoft
San Francisco, CA
- $119,800 to $261,000 USD / year
XBOX Growth Intelligence is seeking a Senior Data Scientist, Product Analytics to partner directly with Product, Engineering, and cross-functional leaders to shape the future of XBOX…
Added 10 days ago
Principal Machine Learning Engineer
Cisco Systems, Inc.
San Francisco, CA
Added 10 days ago
Senior Manufacturing Data Science & Machine Learning Engineer
ŌURA
San Francisco, CA
Added 10 days ago
Data Scientist, Consultant
BSC
Oakland, CA
…scale." Reporting to the Director, AI & Machine Learning, the Data Scientist, Consultant will develop and deploy novel applications that leverage machine learning models, statistical…
Added 10 days ago
Data Scientist, Principal - AI Product Engineering
BSC
Oakland, CA
…scale.” Reporting to the Director, AI & Machine Learning, the Data Scientist, Principal will lead the development and deployment of novel applications that leverage generative AI models.…
Added 10 days ago
Executive Director Machine Learning Engineer-MLOps
JPMC page
Palo Alto, CA
We are looking for a Senior MLOps engineer to work closely with Data Scientists to build and deploy ML models on a modern MLOps stack.
Added 10 days ago
L
Data Scientist, Algorithms - Pricing - Rider Engagement
Lyft
San Francisco, CA
- $128,000 to $160,000 USD / year
Data Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in a dynamic environment, and partner closely with cross-functional teammates to tackle…
Added 10 days ago
Sr. Data Scientist
Navan
San Francisco, CA
Navan is looking for a hands-on Senior Data Scientist to apply statistical modeling and AI to business optimization and better decision-making. You’ll partner with teams across Navan to…
Added 10 days ago
SI
Director, Machine Learning Engineer, Content
Snap Inc.
Palo Alto, CA · San Francisco, CA
- $284,000 to $500,000 USD / year
Added 10 days ago
Business Data Scientist, YouTube Ads, Finance Revenue Analytics and Forecasting
YouTube
San Bruno, CA
Added 11 days ago
Senior Data Scientist, Product
Robinhood
Menlo Park, CA
Added 11 days ago
Z
Data Scientist, Fleet Orchestration Algorithms
Zoox
Foster City, CA
- $177,000 to $217,000 USD / year
The Core Data Science team builds the products and data assets that let teams across Zoox measure and improve the autonomy and operational performance of our fleet. In this role, you'll…
Added 11 days ago
M
Senior Data Scientist, Product
Mudflap
Palo Alto, CA
- $185,000 to $225,000 USD / year
We’re building a data-driven decision engine that powers every aspect of our business - from product development and customer experience to growth and operational excellence. We’re looking…
Added 11 days ago
KL
Data Scientist - Product & Visualization
Kepler Labs
San Francisco, CA
- $150,000 to $180,000 USD / year
The global economy runs on physical assets: fabs, plants, mines, warehouses, data centers, pipelines. A drought, a port closure or a failed supplier moves through those assets into company…
Added 11 days ago
M
Senior Data Scientist - Ecosystem Economics & Growth, XBOX
Microsoft
San Francisco, CA
- $119,800 to $261,000 USD / year
Are you passionate about using data, economics, and advanced analytics to influence strategy at scale? The XBOX Growth Intelligence team is seeking a Senior Data Scientist to drive…
Added 11 days ago
Machine Learning Engineer
Chooch
San Mateo, CA
Added 12 days ago
SI
Data Scientist, Level 4
Snap Inc.
San Francisco, CA · Palo Alto, CA
- $133,000 to $235,000 USD / year
Added 12 days ago
Data Scientist, Product to Market (P2M) Optimization
Gap Inc.
San Francisco, CA
Gap Inc. is seeking a Data Scientist to join our Product-to-Market (P2M) Data Science team. P2M encompasses the decisions that shape how products move from planning to the customer,…

Chooch

Machine Learning Engineer

San Mateo, CA, United States

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Job details

Posting language: English
Posted: Oct 20, 2026

Original job description

Company Description Chooch helps build and run the best Computer Vision AI applications that make cameras intelligent, enhancing productivity & revenues, while reducing operational costs. Chooch has been named a leading computer vision platform by IDC. Role Description We are looking for a Machine Learning Engineer (US-based) to join our team. This is a full-time, hybrid role with frequent hands-on experience with customer projects in the Bay Area. The Machine Learning Engineer will be responsible for the successful design, accuracy, and backbone behind our Computer Vision AI applications. This includes data preparation, training, configuring neural networks, deploying networks in real customer locations, and refining computer vision algorithms for healthcare, manufacturing, and retail customers. This role requires frequent interaction with technical and non-technical customers while working closely within our solutions engineering teams. The Machine Learning Engineering role has opportunity to grow, lead technical projects, and improve current processes while providing meaningful feedback to our product and solutions teams. Product Description Chooch AI is a computer vision platform that helps hospitals automate supply room monitoring and inventory management. Using fixed cameras and AI, the platform continuously tracks supplies in storage areas and updates on-hand counts in real time. When inventory levels fall below defined thresholds, replenishment orders are automatically generated and sent to ERP systems, eliminating manual counts and barcode scanning. Hospitals using Chooch AI significantly reduce critical stockouts, optimize inventory levels, and improve supply chain staff productivity. By turning supply rooms into self-managing systems, Chooch AI enables clinical and supply chain teams to focus more time on patient care.

Responsibilities/What you'll do at Chooch:

Design, train and fine-tune models for object detection, classification, segmentation, tracking and anomaly detection on real customer video and images.
Adapt pretrained and foundation models (YOLO-family detectors, ViTs, CLIP-style and vision-language models) to new customer use cases with limited labeled data.
Own data pipelines end to end: curation, labeling guidelines, augmentation, synthetic data, and dataset versioning.
Optimize models for production and edge hardware using quantization, pruning, distillation, ONNX export and TensorRT, hitting agreed latency and accuracy targets.
Build evaluation suites with clear metrics (mAP, precision/recall, false-alarm rates per camera-hour) and catch regressions before release.
Deploy and monitor models in production, diagnose drift and failure cases, and close the loop with retraining.
Work with product, solutions engineers and customers to turn vague requirements into measurable model specs.
Write clean, tested, reviewed code and contribute to shared ML tooling.

Nice to have

Experience with vision-language models (CLIP, LLaVA-style models) or open-vocabulary detection.
Multi-object tracking and video analytics (re-identification, action recognition, temporal models).
Few-shot learning, active learning, or synthetic data generation for low-data domains.
MLOps tooling: MLflow or Weights & Biases, Kubernetes, Triton Inference Server, CI/CD for models.
Domain experience in Healthcare, retail and supply chain, manufacturing inspection, workplace safety or video surveillance.

Key Components

Model Development and Optimization: Design, develop, and optimize machine learning models for computer vision applications.
Data Management: Collaborate with ML engineers to ensure the collection, processing, and maintenance of high-quality datasets necessary for model training and testing.
Algorithm Implementation: Implement state-of-the-art computer vision algorithms to improve system accuracy and performance in real-world scenarios.
Cross-Functional Collaboration: Work closely within the solutions engineering team to integrate machine learning models into the broader product and systems.
On-Site Travel and Field Testing: Many of our projects are live deployments with major fortune 500 customers – testing new, innovative ML technologies. Traveling on site is sometimes needed to see the environment, test in the real-world, and ensure the technology is operating as expected.
Performance Evaluation: Regularly evaluate the performance of computer vision models, using both qualitative and quantitative methods, and iterate to enhance accuracy and efficiency.
Research and Innovation: Understanding of the latest developments in machine learning and computer vision, applying innovative approaches and technologies to solve complex challenges.
Stakeholder Engagement: Collaborate with internal and external stakeholders to understand their needs and translate them into effective technical solutions.
Problem-Solving: Address and troubleshoot complex problems that arise during the development and deployment of computer vision systems.

The ideal candidate should be deeply passionate about machine learning and its real-world applications, particularly in improving and leveraging state-of-the-art neural networks to make an impact.

3–5 years of industry experience building ML systems, with at least 2 years focused on computer vision.
BS or MS in Computer Science, Electrical Engineering, Math or a related field, or equivalent practical experience.
Strong Python and hands-on experience with PyTorch (or TensorFlow) for training and debugging deep learning models.
Shipped at least one computer vision model to production, and can explain the trade-offs made along the way.
Solid grasp of CNN and transformer architectures for detection, segmentation and classification.
Experience with OpenCV and image/video processing: decoding streams, preprocessing, augmentation.
Working knowledge of model optimization for inference (ONNX, TensorRT, quantization or similar).
Comfortable with Docker, Git, Linux and training on GPUs in a cloud environment (AWS/Azure).
Sound ML fundamentals: loss functions, overfitting, class imbalance, evaluation metrics and experiment design.
Clear written and verbal communication, including explaining model behavior to non-ML stakeholders.

Chooch offers extensive benefits including health, dental, vision insurance, 401K with 3% match, extensive PTO, and life insurance policies included.

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