Machine Learning Engineer
Core
Design, develop, and deploy machine learning systems and models to upgrade stakeholder decision-making by analyzing data distributions and solving real-time problems.
Role type
Machine Learning Engineer
Builds
Machine Learning systems, models, and applications deployed in production
Domain
Data Science / Machine Learning / Deep Learning
Deliverable
production ML models
Required skills
Python, TensorFlow, Scikit-learn, PySpark, Pandas, NumPy, Seaborn, Plotly, Matplotlib, Linear Algebra, Statistics, Probability, Gradient Boosting, Stacking, Classification, Deep Learning, Hadoop, Apache Spark, Cloud Infrastructure (AWS SageMaker, DataBricks, EC2)
Preferred skills
Kubernetes, Task Queues
Responsibilities
Explore and visualize data to understand distributions affecting model performance; verify and clean data; design and develop ML systems; perform statistical analysis and fine-tune models; train and retrain ML systems; deploy ML models in production and maintain cloud infrastructure costs; develop ML apps per client and data scientist requirements; analyze problem-solving capabilities and use-cases of ML algorithms.
Seniority
Mid-level, hands-on IC