Job Description

Responsibilities:

• Develops and refines machine learning models to solve specific business problems (Model Training)
• Conducts feature engineering to enhance model performance and represent data optimally
• Performs hyperparameter tuning to optimize model performance
• Designs and implements ML pipelines that sequence different steps for optimal results (e.g., model training, evaluation, data transformation)
• Selects appropriate algorithms based on problem requirements, data characteristics, and performance criteria
• Analyzes data to uncover trends, patterns, and insights 
• Considers and accounts for data drift over time to ensure models remain effective in production
• Conducts prompt engineering to improve performance of models requiring natural language inputs
• Ensures quality through model evaluation and rigorous testing of results
• Estimates costs for ML-related tasks, including project offers and change requests
• Collaborates with business stakeholders to deeply understand the business case behind the ML model and its expected outcomes 

Job Requirements

Requirements:

• Strong knowledge of machine learning algorithms, hyperparameter tuning, and model evaluation
• Experience with prompt engineering and natural language processing (NLP) tasks
• Proficiency in Python
• Familiarity with ML libraries such as TensorFlow, Scikit-learn, and PyTorch
• Knowledge of data analysis techniques, feature engineering, and data preparation
• Understanding of ML pipelines and workflow automation
• Ability to detect and address data drift in production environments
• Strong problem-solving and analytical thinking skills
• Experience working with stakeholders to understand and refine business cases
• Familiarity with cost estimation and budget management for ML projects
• Excellent communication skills to convey technical insights in business terms
• Continuous learning mindset, staying updated with the latest in AI/ML technologies
• Strong problem-solving and analytical thinking skills.
• Experience working with stakeholders to understand and refine business cases.
• Continuous learning mindset, staying updated with the latest in AI/ML technologies.
• Primary Skills:
• Core Libraries: Python 3.11+, pandas, NumPy, scikit-learn
• Deep Learning: TensorFlow, Keras, PyTorch
• Natural Language Processing: (Azure) OpenAI, Prompt Engineering, transformers, Langchain
• Development & Deployment: Git, Docker
• Data Visualization & Application: Streamlit, Matplotlib
• Azure: Azure Cognitive Services, Azure Databricks
• Secondary Skills:
• Azure Databases & Data Services: Azure Cosmos DB, Azure Data Factory

Skills