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Remote Anomaly Detection Jobs in Florida (NOW HIRING)

Senior Software Engineer (Remote)

Miami, FL ยท Remote

$117K - $154K/yr

This is a remote role anywhere in the USA. Meet the Team Our software engineering team develops ... anomaly detection, or security workflow automation. * Familiarity with LLMs, AI agents, embeddings ...

Senior Software Engineer (Remote)

Tampa, FL ยท Remote

$115K - $152K/yr

This is a remote role anywhere in the USA. Meet the Team Our software engineering team develops ... anomaly detection, or security workflow automation. * Familiarity with LLMs, AI agents, embeddings ...

$234K/yr

The role may be onsite or remote based on business needs and candidate profile. This role owns the ... anomaly detection, stock monitoring, shortage/overstock prediction, demand forecasting, variance ...

Deep understanding of AI security concepts, including machine learning, threat detection, anomaly ... Fully Remote: We are a completely remote global team. Though we're distributed, we are intentional ...

New

... anomaly detection, and natural language processing. Our mission is to lower the barrier for ... OneStream is an Equal Opportunity Employer. #LI-REMOTE #LI-AS1

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Remote Anomaly Detection information

What is remote anomaly detection?

Remote anomaly detection is the process of identifying unusual patterns or behaviors in data collected from remote systems, devices, or networks. This technique is commonly used in industries such as cybersecurity, manufacturing, and IoT to monitor operations and quickly detect issues or potential threats. By using algorithms and machine learning, remote anomaly detection can automatically flag data points that deviate from normal patterns, helping organizations respond proactively to prevent problems. This approach is especially valuable in environments where manual monitoring is difficult or impractical due to distance or scale.

What are the key skills and qualifications needed to thrive as a remote anomaly detection specialist, and why are they important?

To thrive in Remote Anomaly Detection, you need a strong background in statistics, data analysis, and machine learning, usually supported by a degree in computer science, engineering, or a related field. Familiarity with analytical tools like Python, R, SQL, and specialized anomaly detection frameworks is essential, along with experience in cloud platforms. Strong problem-solving skills, attention to detail, and effective remote communication set top performers apart. These competencies enable accurate identification of unusual patterns, quick response to potential risks, and seamless collaboration in distributed work environments.

What are some common challenges faced by professionals working in remote anomaly detection roles?

Professionals in remote anomaly detection often face challenges related to data quality and access, as much of the work depends on analyzing large, diverse datasets from various sources. Ensuring secure, real-time data transmission and maintaining robust communication with cross-functional teams can also be demanding, especially when working remotely. Additionally, adapting to evolving algorithms and staying current with the latest detection technologies requires ongoing learning and collaboration. Successfully navigating these challenges typically involves proactive communication, diligent documentation, and leveraging collaborative tools to stay connected with colleagues.

What is the difference between Remote Anomaly Detection vs Data Analyst?

AspectRemote Anomaly DetectionData Analyst
Required CredentialsBackground in cybersecurity, data science, or related fields; certifications like CompTIA Security+ or Certified Data ProfessionalBachelor's degree in statistics, mathematics, or related field; certifications like Microsoft Data Analyst Associate
Work EnvironmentRemote, often in tech or cybersecurity firms, focusing on monitoring systems and identifying irregularitiesRemote or on-site, working with data sets, creating reports, and providing insights for business decisions
Employer & Industry UsageTech companies, cybersecurity firms, financial institutionsBusiness, finance, marketing, healthcare sectors

While both roles involve working with data, Remote Anomaly Detection specialists focus on identifying irregularities in systems or networks, often requiring cybersecurity knowledge. Data Analysts interpret data to inform business strategies. The roles share skills in data analysis but differ in focus and industry applications.

What are the most commonly searched types of Anomaly Detection jobs in Florida?

The most popular types of Anomaly Detection jobs in Florida are:

What job categories do people searching Remote Anomaly Detection jobs in Florida look for?

The top searched job categories for Remote Anomaly Detection jobs in Florida are:

What cities in Florida are hiring for Remote Anomaly Detection jobs?

Cities in Florida with the most Remote Anomaly Detection job openings:

Infographic showing various Remote Anomaly Detection job openings in Florida as of September 2026, with employment types broken down into 75% Full Time, and 25% Contract. Highlights an 100% Remote job distribution.

Senior Computer Vision Engineer ID72408

Fort Lauderdale, FL โ€ข On-site, Remote

AgileEngine
Software Developmentย โ€ขย 201 - 500 employees

$99K - $137K/yr

Full-time

Posted 21 days ago


Job description

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

WHY JOIN US
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

ABOUT THE ROLE
We are looking for a Senior Computer Vision Engineer to own applied model development across computer vision, machine learning, and data science use cases — building and deploying solutions for object detection, image segmentation, classification, and video analysis. You will evaluate and fine-tune model architectures using PyTorch and TensorFlow, build broader ML models for forecasting and anomaly detection, and apply practical knowledge of computer vision hardware including cameras, sensors, and edge devices.

WHAT YOU WILL DO
- Own the applied model development process across computer vision, AI/ML, and broader data science use cases;
- Translate complex business problems into viable, practical, and scalable AI/ML solutions;
- Evaluate various model options, train and fine-tune selected architectures, and rigorously analyze model performance;
- Develop and deploy solutions for object detection, image segmentation, image classification, and video analysis;
- Build and maintain models for time-series forecasting, anomaly detection, regression, clustering, and general data analysis;
- Apply practical knowledge of real-world constraints—such as lighting, sensor limitations, and edge device compute power—to ensure optimal data quality and robust model performance in production.

MUST HAVES
- You must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time;
- 3 to 5 years of professional experience in Computer Vision, Machine Learning, Data Science, or a related field;
- Degree in Computer Science, Engineering, Data Science, Mathematics, or a related discipline (or equivalent practical experience);
- Engineers located in the US must reside in Dallas, TX, and be open to working from the office (onsite);
- Strong, production-level proficiency in Python;
- Deep hands-on experience with PyTorch and/or TensorFlow;
- Proven track record of building and deploying models for detection, segmentation, classification, and image/video analysis;
- Solid understanding of broader ML and data science techniques (time-series modeling, forecasting, anomaly detection, regression, and clustering);
- Practical experience working with computer vision hardware, including cameras, sensors, and lighting setups;
- Familiarity with deploying models on edge devices;
- Strong understanding of how physical and real-world constraints impact data quality, model training, and inference;
- Upper-intermediate English level.

PERKS AND BENEFITS
- Professional growth: Mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation: USD-based pay with education, fitness, and team activity budgets.
- Exciting projects: Modern solutions with Fortune 500 and top product companies.
- Flextime: Flexible schedule with remote and office options.