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Day Image Annotation Jobs (NOW HIRING)

Data Engineer III 70756-1

Menlo Park, CA · On-site +1

$134K - $162K/yr

Our team develops comprehensive data curation and evaluation solutions for image generation models ... Additional Responsibilities LLM-Assisted Annotation: Design and operate pipelines that use LLMs and ...

... annotation, and evaluation pipelines that improve model quality across visual quality, prompt ... Curate and manage large-scale image datasets using SQL and model-derived signals, ensuring data ...

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Day Image Annotation information

What is day image annotation?

Day image annotation is the process of labeling or tagging objects, regions, or attributes in images taken during daylight conditions. This annotated data is often used to train computer vision models, such as those used in autonomous vehicles or surveillance systems, to recognize and interpret visual information. Annotators may identify and mark features such as pedestrians, vehicles, road signs, and other elements visible in daytime imagery. The accuracy and quality of these annotations are crucial for developing reliable AI systems. Day image annotation can be performed manually or with the assistance of annotation tools.

What is the difference between Day Image Annotation vs Day Data Labeling?

AspectDay Image AnnotationDay Data Labeling
Primary FocusAnnotating images for machine learning modelsLabeling data, including images, for training AI systems
Work EnvironmentRemote or on-site, involving detailed image workSimilar, often remote, involving data categorization
Required SkillsAttention to detail, familiarity with annotation toolsAttention to detail, understanding of data structures
Industry UsageAutonomous vehicles, healthcare, retailAutonomous vehicles, healthcare, retail

Both Day Image Annotation and Day Data Labeling involve preparing data for AI models, but image annotation specifically focuses on marking objects within images, while data labeling can include various data types. They share similar skills and work environments, often overlapping in industries like autonomous vehicles and healthcare.

What are some common challenges faced by Day Image Annotation specialists, and how can they overcome them?

Day Image Annotation specialists often encounter challenges such as maintaining high accuracy while labeling large volumes of images and dealing with ambiguous or low-quality visual data. To overcome these challenges, it is important to follow clear annotation guidelines, communicate regularly with team members or project managers for clarifications, and utilize annotation tools efficiently. Many teams also conduct peer reviews to ensure consistency and quality across datasets, which helps specialists learn and improve their skills over time.

What are the key skills and qualifications needed to thrive as a Day Image Annotation Specialist, and why are they important?

To thrive as a Day Image Annotation Specialist, you need strong attention to detail, visual acuity, and a basic understanding of data labeling concepts, often supported by a high school diploma or equivalent. Familiarity with annotation software tools such as Labelbox, CVAT, or Supervisely is typically required. Strong organizational skills, patience, and the ability to work independently make someone stand out in this position. These skills ensure high-quality, accurate annotations that are essential for effective machine learning model training and data integrity.
More about Day Image Annotation jobs
What cities are hiring for Day Image Annotation jobs? Cities with the most Day Image Annotation job openings:
What are the most commonly searched types of Image Annotation jobs? The most popular types of Image Annotation jobs are:
What states have the most Day Image Annotation jobs? States with the most job openings for Day Image Annotation jobs include:
Infographic showing various Day Image Annotation job openings in the United States as of May 2026, with employment types broken down into 13% Locum Tenens, 13% As Needed, 58% Full Time, 4% Part Time, 8% Temporary, and 4% Nights. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution.

Staff Machine Learning Engineer

Intuitive Surgical

Sunnyvale, CA

Full-time

Posted 26 days ago


Intuitive Surgical rating

9.1

Company rating: 9.1 out of 10

Based on 6 frontline employees who took The Breakroom Quiz


Job description

Company Description

It started with a simple idea: what if surgery could be less invasive and recovery less painful? Nearly 30 years later, that question still fuels everything we do at Intuitive. As a global leader in robotic-assisted surgery and minimally invasive care, our technologies—like the da Vinci surgical system and Ion—have transformed how care is delivered for millions of patients worldwide.

We’re a team of engineers, clinicians, and innovators united by one purpose: to make surgery smarter, safer, and more human. Every day, our work helps care teams perform with greater precision and patients recover faster, improving outcomes around the world.

The problems we solve demand creativity, rigor, and collaboration. The work is challenging, but deeply meaningful—because every improvement we make has the potential to change a life.

If you’re ready to contribute to something bigger than yourself and help transform the future of healthcare, you’ll find your purpose here.

Job Description

About This Opportunity:

As a Staff Machine Learning Engineer, you will be responsible for driving the design, development, and deployment of novel machine learning solutions for pathology image analysis.  You will work with alongside research, engineering, regulatory, and clinical teams to develop and test algorithms and translate them into robust, validated, and scalable medical device software.  The ideal candidate will have a proven track record of leading efforts to build and deploy cutting-edge deep learning models on large-scale image data. Ability to work in person in San Carlos, CA office is preferred.

Responsibilities:

  • Independently lead projects to conceive, develop, and implement AI/ML approaches to extract novel insights from large-scale microscopy image data sets
  • Perform analysis of neural networks, propose and execute experiments to improve key performance metrics
  • Update and improve primary machine learning models as more data is generated
  • Support software infrastructure and data engineering required to store, annotate, train, and test on large pathology image sets
  • Implement semi-supervised and self-supervised methods to reduce image annotation burden
  • Collaborate with physicians and product teams to ensure clinical relevance, robustness, and usability of models
  • Stay up to date with the latest pathology CV/ML literature, use this to inform research & product direction
  • Optimize and validate models for integration into production systems, ensuring performance in real-world clinical settings
  • Develop applications to be deployed and scaled
Qualifications

Required Qualifications:

  • PhD or Master’s degree in Computer Science or related field with a focus on ML/CV
  • 7+ years of industry experience developing and deploying ML models or 4+ years of industry experience with a PhD
  • Previously deployed CV/ML projects to users/customers
  • Strong background in deep learning for computer vision
  • Expert knowledge of the latest machine learning approaches for image analysis
  • Able to read, understand and implement the latest algorithms from research papers
  • Able to implement and experiment with own architecture ideas
  • Fluent in Python and experience with ML frameworks and models (Pytorch, Yolo, etc.)
  • Experience with distributed training and cloud-based ML workflows
  • Experience with large-scale image datasets

Preferred Qualifications:

  • Experience with pathology whole-slide images or biomedical image analysis
  • Familiarity with multimodal data integration (imaging + clinical / molecular data)
  • Expertise in industrial-scale ML engineering, including model deployment for real-time inference, GPU/throughput optimization (e.g., TensorRT, ONNX Runtime, mixed precision), and building scalable, production-ready ML pipelines with MLOps best practices
  • Familiarity with containerized deployments (Docker, Kubernetes) and scaling ML systems in production
  • Experience with CI/CD and MLOps pipelines for automated model deployment and monitoring
  • Track record of leading CV/ML projects from conception through deployment
  • Published research in the CV/ML domain
Additional Information

Due to the nature of our business and the role, please note that Intuitive and/or your customer(s) may require that you show current proof of vaccination against certain diseases including COVID-19.  Details can vary by role.

Intuitive is an Equal Opportunity Employer. We provide equal employment opportunities to all qualified applicants and employees, and prohibit discrimination and harassment of any type, without regard to race, sex, pregnancy, sexual orientation, gender identity, national origin, color, age, religion, protected veteran or disability status, genetic information or any other status protected under federal, state, or local applicable laws.

Mandatory Notices

U.S. Export Controls Disclaimer:  In accordance with the U.S. Export Administration Regulations (15 CFR §743.13(b)), some roles at Intuitive Surgical may be subject to U.S. export controls for prospective employees who are nationals from countries currently on embargo or sanctions status.

Certain information you provide as part of the application will be used for purposes of determining whether Intuitive Surgical will need to (i) obtain an export license from the U.S. Government on your behalf (note: the government’s licensing process can take 3 to 6+ months) or (ii) implement a Technology Control Plan (“TCP”) (note: typically adds 2 weeks to the hiring process).  

For any Intuitive role subject to export controls, final offers are contingent upon obtaining an approved export license and/or an executed TCP prior to the prospective employee’s start date, which may or may not be flexible, and within a timeframe that does not unreasonably impede the hiring need. If applicable, candidates will be notified and instructed on any requirements for these purposes. 

We will consider for employment qualified applicants with arrest and conviction records in accordance with fair chance laws.

Preference will be given to qualified candidates who do not reside, or plan to reside, in Alabama, Arkansas, Delaware, Florida, Indiana, Iowa, Louisiana, Maryland, Mississippi, Missouri, Oklahoma, Pennsylvania, South Carolina, or Tennessee.

This position may be filled at a different job level than listed here depending on
business need and/or on the selected candidate’s experience, knowledge and skills.
Compensation will be based primarily on the job level at which the role is filled and the
candidate’s qualifications, consistent with applicable law.

We provide market-competitive compensation packages, inclusive of base pay, incentives, benefits, and equity. It would not be typical for someone to be hired at the top end of range for the role, as actual pay will be determined based on several factors, including experience, skills, and qualifications. The target compensation ranges are listed.

Base Salary Range Region 1:$229,600 - $330,400
Base Salary Range Region 2: $195,200 - $280,800
Shift: Day
Workplace Type: Set Schedule - This job will be onsite weekly, the percentage of onsite work will be defined by the leader.