AI Engineer Role

New

Skills

AWS Classification Computer Vision IoT LLMs Machine Learning MLOps Model Evaluation Segmentation Video Processing

We are looking for an experienced AI Engineer specializing in Computer Vision to build an end-to-end ML training pipeline. This role involves data ingestion, labeling, training, retraining, and evaluating various ML models. The ideal candidate will own MLOps processes and ensure the models are validated and optimized for edge deployment.

Key Responsibilities
  • Build and manage an end-to-end ML training pipeline.
  • Train and evaluate segmentation, classification, and mass-estimation models.
  • Create cloud-side evaluation harness for assessing real-world model performance.
  • Track experiments, versions, and automated evaluation as part of MLOps.
  • Analyze failure cases to drive improvements across different food items and environments.
Required Skills & Qualifications
  • Strong understanding of computer vision fundamentals: segmentation, detection, classification, and tracking.
  • Fluency with Vision Language Models (VLMs), Large Language Models (LLMs), and foundation models.
  • Experience in building ML pipelines and annotation systems.
  • Proficiency in evaluating ML models and making metric-driven decisions.
  • Familiarity with cloud ML infrastructure (AWS or equivalent) and production pipelines.
  • Experience in cloud-to-edge model deployment.
  • Knowledge of video understanding techniques such as temporal tracking and video segmentation.
  • Familiarity with MLOps tooling like Weights & Biases, MLflow, and SageMaker.
  • Experience in shipping LLM/agent-powered features in products.
  • Background in hardware/IoT CV experience for embedded cameras.

No forms. Your profile is generated instantly.

Job Type: Remote

Salary: Not Disclosed

Experience: Entry

Duration: Months

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