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7 hours ago
At the heart of our technology lies a sophisticated machine learning architecture, and we're seeking an accomplished Machine Learning Engineer to lead its development. As a key member of our engineering team, you will be responsible for designing, building, and deploying scalable ML models that power our business-critical solutions.
Key Responsibilities:
- Design, develop, and deploy machine learning models using regression, classification, clustering, and deep learning techniques.
- Build and optimize data pipelines, feature engineering, and training workflows to drive innovation and measurable business outcomes.
- Deploy models to production using containerization technologies like Docker and Kubernetes, and cloud platforms such as AWS and Google Cloud.
- Monitor model performance, retrain, and maintain production-ready systems.
- Develop APIs and integrate machine learning solutions with enterprise applications to enhance business operations.
- Stay updated on machine learning and artificial intelligence trends, and contribute innovative solutions to drive business growth.
- Collaborate with cross-functional teams, including data scientists, engineers, and product managers, to align with business goals and objectives.
- Minimum 3 years of experience in machine learning engineering or a related field.
- Strong proficiency in Python programming language; knowledge of Java, Scala, and R is beneficial.
- Expertise in popular machine learning libraries and frameworks: scikit-learn, TensorFlow, PyTorch, and Keras.
- Hands-on experience with data tools: Pandas, NumPy, Apache Spark, and SQL databases.
- Experience with machine learning deployment: SageMaker, Azure Machine Learning, Google Cloud AI Platform, TensorFlow Serving, and TorchServe.
- Familiarity with databases: MongoDB, Cassandra, and version control systems like Git.
- Understanding of DevOps/Machine Learning Operations practices to ensure seamless model deployment and maintenance.
- Excellent problem-solving, communication, and collaboration skills to work effectively in a fast-paced environment.
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