We are looking for a highly skilled Middle/Senior ML Engineer to join our team.

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As a Machine Learning (ML) Engineer, you will be responsible for designing, developing, and implementing machine learning models and algorithms to solve complex problems and enhance the performance of existing systems. Your expertise in machine learning techniques and programming skills will be instrumental in developing innovative solutions and driving data-driven decision making within the organization.

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Responsibilities:

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• Stay up to date with the latest advancements in machine learning and related fields.
• Conduct research and experiments to identify suitable machine learning models, algorithms, and approaches to solve specific business problems.
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• Design, develop, and deploy machine learning models, including but not limited to supervised learning, unsupervised learning, and deep learning models.
• Evaluate model performance and optimize for accuracy, efficiency, and scalability.
• Clean, preprocess, and transform raw data to make it suitable for machine learning algorithms. Handle data quality issues, missing values, outliers, and feature engineering to improve model performance.
• Identify relevant features and engineer new features from available data sources to enhance model performance. Utilize domain knowledge and statistical techniques to extract meaningful information from data.
• Implement training pipelines for machine learning models, using various techniques such as cross-validation and hyperparameter optimization. Evaluate model performance using appropriate metrics and techniques.
• Deploy machine learning models into production systems and integrate them with existing infrastructure. Collaborate with software engineers and DevOps teams to ensure seamless deployment, monitoring, and maintenance of the models.
• Optimize machine learning models for performance, scalability, and efficiency. Fine-tune algorithms, parallelize computations, and explore distributed computing frameworks to handle large datasets and real-time applications.
• Collaborate with cross-functional teams, including data scientists, software engineers, product managers, and stakeholders, to understand requirements, translate business problems into technical solutions, and communicate the results effectively.
• Document methodologies, techniques, and results of machine learning projects. Prepare clear and concise reports and presentations to communicate findings, insights, and recommendations to technical and non-technical audiences.
• Stay updated with the latest trends and advancements in machine learning, artificial intelligence, and related fields. Participate in conferences, workshops, and online communities to expand knowledge and share insights within the organization.

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Requirements:

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• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field.
• Strong programming skills in languages such as Python or Java.
• Proficiency in machine learning libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, or Keras.
• Experience with data manipulation, preprocessing, and feature engineering techniques.
• Solid understanding of various machine learning algorithms and statistical concepts.
• Knowledge of deep learning architectures, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs).
• Familiarity with cloud platforms, such as AWS, Azure, or GCP, and experience with deploying models in a cloud environment.
• Strong problem-solving and analytical thinking abilities.
• Excellent communication and collaboration skills.
• Ability to work independently and manage multiple projects simultaneously.

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Preferred Skills:

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• Experience with big data technologies and distributed computing frameworks (e.g., Hadoop, Spark).
• Knowledge of natural language processing (NLP) techniques and frameworks.
• Understanding of computer vision algorithms and image processing techniques.
• Familiarity with containerization technologies like Docker and orchestration tools like Kubernetes.

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If you have the required skills and experience, please submit your application for consideration.

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