ZipRecruiter

Log In

1

Machine Learning Object Detection Jobs in West Virginia

Coalition, Inc.

WV · On-site

$200K/yr

About the role Coalition's machine learning models are only as good as the data they're trained on ... detection * Comfortable working in Python and SQL; bonus if you've built tooling around labeling ...

Mitre

Biometrics Engineer

Bridgeport, WV

... knowledge of object-oriented design concepts, design patterns and data structures. Required ... machine learning and statistical analysis. Experience in C/C++, C#, Java/J2EE development.

AmeriSave Mortgage Corp.

$130K - $150K/yr

Rigorously analyze operational and financial metrics to detect process deficiencies, performance ... machine learning workflows. Leverage Python for data preparation, model training, and result ...

Surescripts

Principal AI Engineer

Charleston, WV · Hybrid

... drift detection, to issue and incident response, to data-driven continuous improvement of AI ... machine learning / AI engineering experience * Proven experience architecting and delivering ...

next page

Showing results 1-20

All JobsMachine Learning Object Detection JobsMachine Learning Object Detection Jobs in West Virginia

Machine Learning Object Detection information

What are the key skills and qualifications needed to thrive as a machine learning object detection engineer, and why are they important?

To excel as a Machine Learning Object Detection Engineer, you need a solid background in computer science, mathematics, and deep learning principles, often backed by a relevant degree and experience in computer vision. Familiarity with frameworks like TensorFlow, PyTorch, and OpenCV, as well as experience with annotation tools and GPU computing, is typically required. Strong problem-solving abilities, attention to detail, and effective communication are vital soft skills for collaborating with cross-functional teams and addressing complex challenges. These competencies ensure accurate model development, efficient deployment, and continual improvement of object detection systems in real-world applications.

What are some common challenges faced when working on machine learning object detection projects?

One of the main challenges in machine learning object detection roles is dealing with the quality and quantity of annotated data, as accurate labeling is essential for model performance. Another common challenge is managing variations in object scale, lighting, and occlusion within real-world images, which can affect detection accuracy. Additionally, balancing model accuracy with computational efficiency—especially for real-time applications—often requires careful model selection and optimization. Collaboration with data engineers and domain experts is also typical to ensure data relevance and model applicability.

What is machine learning object detection?

Machine learning object detection is a field within artificial intelligence that focuses on identifying and locating objects within images or videos. It uses algorithms and deep learning models, such as convolutional neural networks (CNNs), to analyze visual data and predict the presence and position of various objects. Object detection is widely used in applications like autonomous vehicles, security surveillance, and image search. The process typically involves training models on labeled datasets so they can accurately detect and classify multiple objects in complex scenes.

What are popular job titles related to Machine Learning Object Detection jobs in West Virginia?

For Machine Learning Object Detection jobs in West Virginia, the most frequently searched job titles are:

What job categories do people searching Machine Learning Object Detection jobs in West Virginia look for?

The top searched job categories for Machine Learning Object Detection jobs in West Virginia are:

What cities in West Virginia are hiring for Machine Learning Object Detection jobs?

Cities in West Virginia with the most Machine Learning Object Detection job openings:

Machine Learning Object Detection jobs near you

Senior Manager, Machine Learning (Data Operations)

Coalition, Inc.

WV • On-site

$200K/yr

Full-time

Medical, Dental, Vision, PTO

Posted 27 days ago

Job description

About the role
Coalition's machine learning models are only as good as the data they're trained on. This role exists to make sure that data is right.

You'll own labeling quality and methodology across Coalition - designing annotation tasks, defining quality frameworks, and ensuring every labeled dataset meets the standard required to ship production ML models. You'll manage our labeling platform (Label Studio), work directly with ML and product teams to structure labeling programs, and oversee outsourced labeling vendors to hit quality and throughput targets.
 

This role reports to the Chief Product Officer and sits at the intersection of product, ML, and operations. You won't manage internal labelers - all annotation work is outsourced - but you will be the single point of accountability for whether Coalition's labeled data is accurate, consistent, and fit for purpose.
Responsibilities
  • Labeling quality & methodology: Define annotation guidelines, taxonomies, and edge-case protocols for each labeling program. Establish gold standard datasets, inter-annotator agreement (IAA) targets, and audit sampling processes. Identify and remediate mislabeled data in existing datasets.
  • Platform & tooling: Serve as the primary user and requirements driver for Label Studio - defining project configuration needs, workflow designs, pre-labeling pipeline requirements, and integration points with ML infrastructure. Partner with the data engineering team that builds and maintains the platform.
  • Cross-functional partnership: Work with ML engineers, data scientists, and product managers to translate model requirements into well-structured labeling tasks. Challenge teams on task design when labeling instructions are ambiguous or likely to produce unreliable labels.
  • Vendor management: Source, onboard, and manage external labeling vendors and BPOs in coordination with Coalition's operations team. Set quality SLAs, run calibration sessions, and manage feedback loops to labelers. Hold vendors accountable to accuracy, not just throughput.
  • Measurement & improvement: Define and track operational metrics - label accuracy, IAA scores, cost per label, turnaround time - and use them to drive continuous improvement. Identify opportunities for active learning, model-assisted labeling, and pre-annotation to reduce cost without sacrificing quality.
Skills and Qualifications
  • 5+ years in ML data operations, data labeling, or a related field (ML engineering, data science, or data engineering with heavy labeling exposure)
  • Deep understanding of annotation quality frameworks: IAA, consensus labeling, gold standard evaluation, error taxonomy, and calibration workflows
  • Direct experience managing labeling platforms (Label Studio strongly preferred; Scale AI, Labelbox, Prodigy, or similar acceptable)
  • Track record managing outsourced labeling vendors or BPOs for ML data production
  • Familiarity with common ML labeling tasks: text classification, NER, document extraction, intent detection
  • Comfortable working in Python and SQL; bonus if you've built tooling around labeling workflows or quality measurement
  • Strong opinions on what makes labeled data good or bad, and the willingness to push back when it's bad
  • Experience in insurance, cybersecurity, or fintech is a plus but not required
Compensation

Our compensation reflects the cost of labor across several US geographic markets. The US base salary for this position ranges from $134,400/year in our lowest geographic market up to $200,000/year in our highest geographic market. Consistent with applicable laws, an employee's pay within this range is based on a number of factors, which include but are not limited to relevant education, skills, job-related knowledge, qualifications, work experience, credentials, and/or geographic location. Your recruiter can share more on target salary for your location during the interview process. Coalition, Inc. reserves the right to modify this range as needed.

Perks
  • 100% medical, dental and vision coverage
  • Flexible PTO policy
  • Annual home office stipend and WeWork access
  • Mental & physical health wellness programs (One Medical, Headspace, Wellhub, and more)!
  • Competitive compensation and opportunity for advancement

Apply