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Camera Ai Jobs (NOW HIRING)

Skild AI

Camera Systems Software Engineer

San Mateo, CA · On-site

$146K - $153K/yr

Position Overview We are seeking an experienced Camera Systems Software Engineer to own camera integration and enablement for real-time robotic systems built on NVIDIA Tegra platforms. This person ...

Qualcomm

AI/ML Camera Lead Engineer

San Diego, CA · On-site

$108K - $143K/yr

Prior ASIC implementation of camera or image processing IP * Experience defining or maintaining benchmarking and evaluation frameworks for ML/LLM systems * Familiarity with agentic AI frameworks or ...

Qualcomm

AI/ML Camera Lead Engineer

San Diego, CA · On-site

$200 - $250/hr

Prior ASIC implementation of camera or image processing IP * Experience defining or maintaining benchmarking and evaluation frameworks for ML/LLM systems * Familiarity with agentic AI frameworks or ...

NRG

Sr Software Engineer, Video Intelligence

WA · Remote

$150K - $185K/yr

Experience improving precision/recall, reducing false alerts, or evaluating customer-facing camera AI * Experience with smart home, security camera, IoT, edge/cloud, or real-time inference ...

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How much do camera ai jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for camera ai in the United States is $28.16, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $30.53 per hour, depending on experience, location, and employer.

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Infographic showing various Camera Ai job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 76% Full Time, 19% Part Time, and 4% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $58,583 per year, or $28.2 per hour.

Sr Software Engineer, Video Intelligence

Seattle, WA • On-site

Nrg Bluewater Wind
See more jobs at Nrg Bluewater Windexternal

$150 - $200/hr

Other

Medical, Dental, Vision, Retirement

Posted 21 days ago

Key responsibilities

  • Build and evaluate systems that generate natural-language descriptions, insights, and summaries from video.

  • Own video-language understanding, temporal video reasoning, event understanding, and multimodal embeddings strategies.

  • Partner with cross-functional teams to move models from research to production and develop evaluation methods for system performance.

Job description

About This Role

We are seeking a Sr Video Intelligence Engineer to advance video understanding. This role will build video-language, summarization, context, and event‑reasoning capabilities that improve camera intelligence and customer trust.

Responsibilities
  • Own VLM strategy, video-language understanding, temporal video reasoning, event understanding, and multimodal embeddings.
  • Improve AI Video Search, video summarization, alert relevance, recognition support, and false‑alert reduction.
  • Build and evaluate systems that generate useful natural‑language descriptions, insights, and summaries from video.
  • Partner with AI, platform, product, and app teams to move models from research to production.
  • Develop production evaluation methods for precision, recall, grounding, latency, safety, and customer usefulness.
  • Guide architecture decisions across cloud, edge, and hybrid inference paths for video intelligence.
Required Qualifications
  • Bachelor’s degree in Computer Science, Software Engineering, AI/ML, or a related technical field, and 5+ years of professional experience in software development, applied science, or ML engineering;
  • Master’s degree in Computer Science, Software Engineering, AI/ML, or a related technical field, and 2+ years of professional experience in software development, applied science, or ML engineering.
  • Experience with LLMs, vision-language models, multimodal AI, or generative AI systems.
  • Strong Python software engineering skills.
  • Experience processing, analyzing, or serving video content at scale.
  • Familiarity with event detection, summarization, semantic understanding, embeddings, or model evaluation.
  • Experience deploying AI services into production with Git and CI/CD workflows.
Preferred Qualifications
  • Experience generating natural-language descriptions, summaries, or searchable representations from video.
  • Experience with multimodal foundation models, temporal video understanding, re-identification, or vector retrieval.
  • Experience improving precision/recall, reducing false alerts, or evaluating customer-facing camera AI.
  • Experience with smart home, security camera, IoT, edge/cloud, or real-time inference architectures.
  • Experience with Docker, Kubernetes, GCP/AWS, or production model monitoring.
Compensation & Benefits

The base salary range for this position is: $150K to $180K. The base salary range above represents the low and high end of the salary range for this position. Actual salaries will vary based on several factors including but not limited to location, experience, and performance. The range listed is just one component of the total compensation package for employees. Other rewards may include annual bonus, short- and long-term incentives, and program-specific awards. In addition the position may be eligible to participate in the benefits program which include, but are not limited to, medical, vision, dental, 401K, and flexible spending accounts.

Position requires in-office presence in Seattle, WA on a hybrid schedule for Monday, Tuesday, Wednesday, and Thursday with a work from home day on Friday. The position will start remote and then will move into the hybrid schedule.

EEO Statement

NRG Energy is committed to a drug and alcohol-free workplace. To the extent permitted by law and any applicable collective bargaining agreement, employees are subject to periodic random drug testing, and post-accident and reasonable suspicion drug and alcohol testing. EOE AA M/F/Protected Veteran Status/Disability. Level, Title and/or Salary may be adjusted based on the applicant's experience or skills.

EEO is the Law Poster (The poster can be found at http://www.eeoc.gov/employers/upload/poster_screen_reader_optimized.pdf)

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