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.
Relevant Experience:
- 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.
Skills Expected:
- Machine Learning Algorithms and Techniques (supervised, unsupervised, reinforcement learning).
- Software Engineering Principles (version control, testing, DevOps).
- 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.