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Position Overview:
We are seeking a highly skilled and motivated Machine Learning Engineer to join our dynamic team. As a Machine Learning Engineer, you will be responsible for developing, implementing, and deploying machine learning models and algorithms to solve complex business problems. You will collaborate with cross-functional teams to understand business requirements, design scalable solutions, and drive innovation through the application of cutting-edge machine learning techniques. The ideal candidate will have a strong background in machine learning, data analysis, and software engineering, with a passion for leveraging data-driven insights to drive business impact.
Key Responsibilities:
- Develop and implement machine learning algorithms and models to solve business problems across various domains, such as natural language processing, computer vision, recommendation systems, and predictive analytics.
- Design and build scalable, efficient, and reliable machine learning pipelines and systems for data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment.
- Collaborate with data scientists, data engineers, and software developers to integrate machine learning solutions into production systems and applications.
- Conduct exploratory data analysis, feature engineering, and model evaluation to understand data characteristics and model performance.
- Stay up-to-date with the latest advancements in machine learning research and techniques, and proactively identify opportunities to apply them to improve our products and services.
- Work closely with stakeholders to understand business requirements, define success metrics, and deliver actionable insights through data-driven analysis and visualization.
- Communicate technical concepts and findings to non-technical stakeholders in a clear and concise manner.
Qualifications:
- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field. PhD is a plus.
- Solid understanding of machine learning concepts, algorithms, and techniques, with hands-on experience in developing and deploying machine learning models at scale.
- Proficiency in programming languages such as Python, R, or Java, and experience with machine learning libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, or Spark MLlib.
- Strong analytical and problem-solving skills, with the ability to analyze large, complex datasets and derive actionable insights.
- Experience with data preprocessing, feature engineering, model selection, and hyperparameter tuning.
- Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes) is a plus.
- Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team environment.
Method of Application
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