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Machine Learning Engineer

Skills

aiairflowawsazureci cdcloudcomputer visioncontainerizationdata ingestiondata sciencedockergcpgithadoopkubeflowmachine learningmlflowmlopsmodel deploymentnlppythonpytorchsagemakerscikit learn

Description

Category: Technology
Location:

We are looking for a highly skilledMachine Learning Engineerto join our AI and data science team. In this role, you will design, develop, and deploy machine learning models and pipelines that power critical data-driven solutions across our organization. You’ll collaborate with data scientists, software engineers, and product teams to deliver intelligent systems at scale.

Responsibilities

  • Design and implement machine learning models for classification, regression, recommendation, NLP, or time-series forecasting tasks.

  • Develop, test, and maintain scalable ML pipelines for training, validation, and inference.

  • Collaborate with data engineers to build efficient data ingestion and feature extraction systems.

  • Optimize model performance using techniques like hyperparameter tuning, cross-validation, and regularization.

  • Deploy models to production using MLOps practices with tools like MLflow, TFX, or SageMaker.

  • Monitor and maintain the health of deployed models, updating them as needed.

  • Document ML experiments, metrics, and decisions.

  • Work closely with cross-functional teams to identify machine learning opportunities and define technical solutions.

Requirements

  • Bachelor’s or Master’s in Computer Science, Machine Learning, Data Science, or related field (Ph.D. a plus).

  • 3–5+ years of hands-on experience building machine learning models in production.

  • Proficiency in Python and ML frameworks such as scikit-learn, TensorFlow, or PyTorch.

  • Experience with ML pipeline tools (e.g., Airflow, Kubeflow, MLflow).

  • Familiarity with cloud services (AWS, GCP, or Azure) and model deployment.

  • Solid understanding of statistics, data structures, and algorithms.

  • Experience with version control (Git), containerization (Docker), and CI/CD for ML.

Preferred Qualifications

  • Experience with NLP or computer vision projects.

  • Familiarity with big data tools (e.g., Spark, Hadoop).

  • Experience using GPU-accelerated training environments.

Details

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