Machine Learning Engineer
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Job Description
We are looking for a skilled and innovative Machine Learning Engineer to join our team. The ideal candidate will be responsible for designing developing and deploying machine learning models and data-driven solutions that improve business outcomes. You will work closely with data scientists software engineers and product teams to turn data into actionable intelligence.
Key Responsibilities:
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Design and implement machine learning algorithms and models for various applications.
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Preprocess clean and analyze large datasets from diverse sources.
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Collaborate with cross-functional teams to define project requirements and success metrics.
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Train test and evaluate model performance using industry-standard metrics.
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Optimize models for scalability and real-time deployment.
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Deploy models into production using tools like Docker Kubernetes or cloud services (AWS Azure GCP).
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Monitor and maintain deployed models for accuracy and performance.
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Document code models and processes for future reference.
Requirements:
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Bachelors or Masters degree in Computer Science Engineering Mathematics or related field.
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Proven experience with Python and libraries such as TensorFlow PyTorch Scikit-learn etc.
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Strong understanding of machine learning algorithms data structures and software engineering principles.
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Experience with SQL and NoSQL databases.
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Familiarity with cloud platforms and MLOps practices.
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Excellent problem-solving and analytical skills.
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Strong communication and teamwork abilities.
Preferred Qualifications:
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Ph.D. in a related field.
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Experience in deep learning NLP computer vision or recommendation systems.
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Experience with tools like MLflow Airflow or Kubeflow.
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Contributions to open-source ML projects or published research papers.
Employment Type
Full Time
