Machine Learning Engineer

Roles & Responsibilities:

• Design and implement machine learning models, algorithms, and deep learning applications and systems.
• Optimize and scale ML models for production.
• Collaborate with data scientists, administrators, data analysts, data engineers, and data architects on production systems and applications.
• Monitor model performance and identify differences in data distribution that could potentially affect model performance in real-world applications.
• Ensure algorithms generate accurate user recommendations.
• Prepare and clean data for model training, including data wrangling, feature engineering, and handling missing values.
• Integrate machine learning models into production systems (web applications, APIs) using software engineering best practices.
• Document the machine learning development process and model performance for future reference and collaboration.
• Stay up to date with developments in the machine learning industry.

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (preferred).
• At least 5 years of hands-on experience as machine learning engineer or similar role.
• Familiarity with Python, Java, C++, and R.

• Machine Learning Algorithms and Techniques (supervised, unsupervised, reinforcement learning).
• Software Engineering Principles (version control, testing, Dev Ops).
• Cloud Computing Platforms (AWS, Azure, GCP) (often a plus).
• Extensive math and computer skills, with a deep understanding of probability, statistics, and algorithms.
• In-depth knowledge of machine learning frameworks, like Keras or PyTorch.
• Familiarity with data structures, data modeling, and software architecture.
• Excellent time management and organizational skills.