Computer Vision, AI Engineer II
- Steneral Consulting
1 Days Ago
NA
C2C
Coppell-TX
3-5 Years
Required Skills: Python, Computer Vision, Detection, Segmentation, Classification, OCR, PyTorch, TensorFlow Machine Learning, Model Development, Optimization Image, Video Analysis
Job Description
What You Will Be Doing:
- Applied Model Development: Own the end-to-end development of computer vision and ML models—covering detection, segmentation, classification, OCR and image/video analysis.
- Model Evaluation & Selection: Evaluate model options, benchmark trade-offs, and recommend the right approach for each business problem.
- Training & Fine-Tuning: Train, fine-tune, and optimize models using PyTorch or TensorFlow, including transfer learning and data-efficient techniques.
- Performance Analysis: Define metrics, analyze model performance, diagnose failure modes, and iterate to meet accuracy and latency targets.
- Hardware-Aware Engineering: Account for the real-world constraints of cameras, sensors, lighting, and edge devices that affect data quality and model performance.
- Data Pipelines: Build and maintain data, labeling, and evaluation pipelines that support reliable experimentation and deployment.
- Collaboration: Work with software, hardware, and MLOps engineers to take models from prototype to production.
Qualifications:
Experience:
- 3–5 years of hands-on experience building computer vision and machine learning models.
- Proven track record taking models from experimentation to production.
Skills:
- Proficiency in both modern AI-based CV models (CNNs, transformers, embeddings) and traditional computer vision
- Strong Python skills for CV/ML development, data processing, and experimentation.
- Experience with PyTorch or TensorFlow.
- Hands-on experience with detection, segmentation, classification, and image/video analysis.
- Practical knowledge of computer vision hardware—cameras, sensors, lighting, and edge devices—and the real-world constraints that affect data quality and model performance.
- Experience with broader ML problems: time-series modeling, anomaly detection, clustering, and data analysis.
Abilities:
- Strong analytical and performance-debugging skills.
- Able to evaluate model options and turn business problems into practical AI solutions.
- Strong problem-solving skills and ability to work in a fast-paced, agile environment.
Education:
- Bachelor’s or Master’s degree in Computer Science, Engineering or a related field.
Preferred Qualifications:
- Experience deploying models to edge devices or optimizing for inference (quantization, pruning, TensorRT, ONNX).
- Familiarity with MLOps practices: experiment tracking, model versioning, and drift/performance monitoring.
- Experience with cloud platforms (Azure, AWS, or GCP) and GPU-based training.
- Experience working with retail, IoT, or real-world imaging datasets.
