Machine Learning Python Developer

Position Overview:
As a Machine Learning Python Developer, you will play a critical role in designing, developing, and implementing machine learning models and algorithms. You will work closely with cross-functional teams to solve complex problems and deliver data-driven solutions. The ideal candidate is passionate about machine learning, has a strong foundation in Python programming, and is eager to apply their skills to real-world challenges.
Key Responsibilities:
Collaborate with data scientists, engineers, and other stakeholders to understand project requirements and develop machine learning models and algorithms using Python and relevant libraries (e.g., TensorFlow, PyTorch, scikit-learn).
Collect, preprocess, and clean large datasets for training and evaluation.
Perform feature engineering and selection to improve model performance.
Evaluate and benchmark machine learning models, making iterative improvements.
Deploy machine learning models into production environments.
Monitor and maintain machine learning models, ensuring their ongoing accuracy and performance.
Stay up-to-date with the latest developments in machine learning and artificial intelligence.
Qualifications:
Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field (or equivalent work experience).
Proven experience in developing machine learning models and algorithms using Python.
Strong programming skills in Python and experience with relevant libraries and frameworks.
Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch) is a plus.
Knowledge of data preprocessing, feature engineering, and model evaluation techniques.
Experience with data visualization tools (e.g., Matplotlib, Seaborn) is a plus.
Excellent problem-solving and critical-thinking skills.
Strong communication and teamwork skills.
Experience with cloud platforms (e.g., AWS, Azure) is a plus.
Familiarity with big data technologies (e.g., Hadoop, Spark) is a plus.
Benefits:
Competitive salary and performance-based bonuses.
Flexible work arrangements, including remote options.
Professional development and training opportunities.
Opportunities to work on cutting-edge machine learning projects.