Machine Learning Engineer (Object Detection)

Machine Learning Engineer (Object Detection)

Posted 5 days ago by KlutchShots Ai on Linkedin

Negotiable
Undetermined
Undetermined
United Kingdom

Summary: The Machine Learning Engineer (Object Detection) role involves designing, developing, and optimizing object detection models for an AI-focused company. The position requires collaboration with cross-functional teams to integrate AI features into the core product, leveraging expertise in Python and deep learning frameworks. Candidates should have a strong background in computer vision and experience with model deployment on edge devices. This role offers opportunities for professional growth in a dynamic work environment.

Key Responsibilities:

  • Design and implement object detection algorithms using modern deep learning frameworks.
  • Build, train, and evaluate custom models for various detection tasks.
  • Develop data pipelines and prepare datasets for training and validation.
  • Optimize model performance for accuracy, speed, and memory efficiency.
  • Convert and integrate models into mobile/edge platforms using tools like CoreML, ONNX, or TensorFlow Lite.
  • Collaborate with cross-functional teams to understand product requirements and deploy models to production.
  • Continuously monitor and improve model performance based on real-world data and feedback.

Key Skills:

  • 3+ years of experience in machine learning with a focus on computer vision and object detection.
  • Proficiency in Python, along with solid understanding of data structures and algorithms.
  • Experience with deep learning frameworks such as PyTorch or TensorFlow.
  • Strong understanding of CNNs, bounding box regression, and evaluation metrics (mAP, IoU, etc.).
  • Familiarity with model optimization techniques like pruning, quantization, and distillation.
  • Experience training and deploying custom models on real-world datasets.
  • Excellent problem-solving and debugging skills.
  • Experience with CoreML and running models on iOS or edge devices is a plus.
  • Knowledge of ONNX, TensorFlow Lite, or other model conversion tools.
  • Familiarity with real-time video processing and hardware acceleration (e.g. GPU, NPU).
  • Experience with MLOps tools for model versioning and deployment.
  • Prior work on AI features in consumer-facing applications.

Salary (Rate): undetermined

City: undetermined

Country: United Kingdom

Working Arrangements: undetermined

IR35 Status: undetermined

Seniority Level: undetermined

Industry: IT