Machine Learning Engineer
4 weeks ago
We are seeking a highly skilled Machine Learning Engineer to join our team at MNR Solutions. As a Machine Learning Engineer, you will be responsible for designing, developing, and implementing machine learning models and algorithms to solve complex problems.
Key Responsibilities:- Design and develop machine learning models and algorithms to solve complex problems.
- Experiment with various machine learning techniques and select the most appropriate ones for specific tasks.
- Analyze and preprocess large datasets to prepare them for machine learning models.
- Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies.
- Develop and select features for machine learning models to improve accuracy and performance.
- Evaluate model performance using metrics such as accuracy, precision, recall, F1 score, and ROC-AUC.
- Tune hyperparameters and optimize models to enhance performance.
- Deploy machine learning models into production environments and integrate them with existing systems.
- Monitor and maintain deployed models to ensure they perform well in real-world scenarios.
- Work closely with data scientists, software engineers, and product managers to align machine learning solutions with business goals.
- Participate in code reviews and contribute to best practices in machine learning development.
- Stay up-to-date with the latest advancements in machine learning and data science.
- Research and implement new algorithms and techniques to improve existing models.
- Document machine learning processes, models, and experiments.
- Prepare reports and presentations to communicate findings and insights to stakeholders.
- Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field from a reputable institution.
- Minimum of 2 years of experience in machine learning engineering or data science roles.
- Proficiency in programming languages such as Python, R, or Java.
- Experience with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Strong understanding of machine learning algorithms and techniques (e.g., supervised, unsupervised learning, neural networks).
- Experience with data preprocessing, feature engineering, and model evaluation.
- Familiarity with version control systems (e.g., Git) and cloud platforms (e.g., AWS, Azure, Google Cloud).
- Experience with deep learning techniques and frameworks.
- Knowledge of big data technologies (e.g., Hadoop, Spark).
- Experience with containerization and orchestration tools (e.g., Docker, Kubernetes).
This position is fully remote. Candidates must have a reliable internet connection and a suitable home office setup.
The role involves collaborating with a distributed team and requires effective communication and self-management skills.
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