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Home Based Annotation Jobs in California (NOW HIRING)

... and reduce the annotation burden for time-sensitive mapping tasks. * Academic & Technical ... Home Office Reimbursement * Monthly Phone and Internet Reimbursement * Tuition Reimbursement and ...

Embedded Software Engineer

Menlo Park, CA · On-site

$120K - $150K/yr

In addition to our core business, Workstream is home to a small, fast-moving Robotics team focused ... Our Robotics team develops scalable data collection and annotation pipelines that enable the ...

In addition to our core business, Workstream is home to a small, fast-moving Robotics team focused ... Our Robotics team develops scalable data collection and annotation pipelines that enable the ...

In addition to our core business, Workstream is home to a small, fast-moving Robotics team focused ... Our Robotics team develops scalable data collection and annotation pipelines that enable the ...

You've gone beyond basic data annotation and have hands-on experience with data analytics, using ... home. * You have some relevant experience. Ideally, you have at least 1-2 years of relevant ...

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Home Based Annotation information

What is the difference between Home Based Annotation vs Data Labeler?

AspectHome Based AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, home-basedRemote, home-based or office
Industry UsageAI training, machine learningAI training, machine learning
Job TasksAnnotating data for AI modelsLabeling data for AI and ML

Both Home Based Annotation and Data Labeler roles involve annotating or labeling data for AI training. The main difference lies in terminology; 'Home Based Annotation' emphasizes the remote, home-based aspect, while 'Data Labeler' is a more general term used across industries. Both roles require similar skills and are often used interchangeably in job searches.

What are the most commonly searched types of Annotation jobs in California? The most popular types of Annotation jobs in California are:
What job categories do people searching Home Based Annotation jobs in California look for? The top searched job categories for Home Based Annotation jobs in California are:
What cities in California are hiring for Home Based Annotation jobs? Cities in California with the most Home Based Annotation job openings:
Senior/Staff Computer Vision Engineer - Deep Learning Focus

Senior/Staff Computer Vision Engineer - Deep Learning Focus

Phantom AI

Mountain View, CA • Hybrid

$180K - $240K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 13 days ago


Job description

About Us

At Phantom AI, we've built a team of incredibly talented and ambitious people challenging the norm in the automotive industry. We are building cost-effective L2/L3 solutions to reduce the burden of everyday driving and make the roads safe for everyone. For instance, we believe democratizing technologies such as Automatic Emergency Braking and Emergency Lane Support is the first priority before tackling a fully self-driving vehicle. Our main customers are Tier 1 automotive manufacturers who are focused on delivering L2/L3 solutions and in the future will deliver full autonomy.

We differentiate ourselves from other autonomous driving startups through a combination of state-of-the-art technological know-how and real automotive experiences of shipping ADAS systems at a volume production scale. If you feel that you have the passion, commitment, and drive to challenge the status quo within the automotive industry, we would love to hear from you.

We are seeking a highly skilled Senior Deep Learning Engineer to drive the development and deployment of advanced perception models for Advanced Driver Assistance Systems (ADAS). The successful candidate will play a key role in designing cutting-edge neural network architectures, optimizing model performance, and ensuring reliable deployment on embedded platforms. This position requires a balance of deep technical expertise, strong analytical thinking, and cross-functional collaboration.


Responsibilities

  • Design and implement advanced deep learning architectures to enhance perception capabilities within ADAS systems.
  • Maintain and continuously improve existing models by optimizing performance, addressing issues, and refining architecture and algorithms.
  • Perform detailed root cause analysis of production issues and develop sustainable, high-quality solutions.
  • Optimize model performance with a focus on latency, efficiency, and resource utilization for real-time embedded deployment.
  • Integrate and validate deep learning algorithms on automotive-grade hardware and embedded SoCs.
  • Collaborate closely with data engineering, data annotation, and platform engineering teams to ensure smooth data flow and seamless model integration.
  • Provide regular updates and technical reports on model development, maintenance progress, and performance metrics to management.


Required Qualifications

  • 3-5+ years of professional experience developing, training, validating, and deploying deep learning-based perception models for ADAS or related computer vision applications.
  • In-depth understanding of training and inference pipelines, including data loading, augmentation, and loss function design.
  • Advanced degree (M.S. or Ph.D.) in Computer Vision, Robotics, Machine Learning, or a closely related discipline, or equivalent industry experience.
  • Strong proficiency in Python and a deep understanding of software design principles and development best practices.
  • Expertise in PyTorch (preferred) or TensorFlow for large-scale model development and experimentation.
  • Practical experience with data pipelines, distributed training, and machine learning experiment management tools.
  • Proven ability to work effectively in a collaborative, cross-functional team environment.


Preferred Qualifications

  • Comprehensive understanding of machine learning algorithms, including classification, regression, and clustering methods.
  • Experience deploying and optimizing models for embedded or automotive SoCs (e.g., NVIDIA Drive, TI TDA4, Qualcomm Snapdragon).
  • Proficiency in model optimization techniques such as quantization, pruning, and knowledge distillation.
  • Doctorate (Ph.D.) in Computer Science, Artificial Intelligence, or related field is a plus.
  • Strong programming experience in Python and/or C++ within Linux development environments.
  • Familiarity with automotive perception workflows, datasets, and evaluation frameworks (e.g., KITTI, Waymo, Euro NCAP)


Benefits

We offer our employees a comprehensive benefits package including:

  • Salary $180,000-$240,000
  • Medical, dental and vision coverage
  • Office snacks & reimbursable meals*
  • Paid Time Off
  • FSA
  • 401K


Work Type

Hybrid - Phantom AI follows this type of working experience to allow employees the flexibility to work weekly at the office 4x and from home 1x.


Equal Opportunity for Diversity & Inclusion

Phantom AI provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.