Description

You will apply machine learning and deep learning techniques to extract insights from large datasets and solve complex business problems.

Responsibilities

• Prep large datasets for consumption and assess the accuracy of various data sources.
• Collaborate with business users to define use case feasibility and identify how data can be applied to specific problems.
• Evaluate machine learning algorithm results, focusing on model explainability and performance monitoring.
• Execute prompt engineering tasks for specific use cases.
• Determine the practical advantages and drawbacks of various machine learning techniques in real-world applications.

Required Skills

• 5 years of experience in data science or a related field.
• Proficiency in Python for data manipulation and statistical analysis.
• Experience with machine learning techniques including clustering, decision tree learning, and artificial neural networks.
• Hands-on experience with deep learning architectures such as RNN, CNN, and LSTM.
• Proficiency with deep learning frameworks including TensorFlow and Keras.
• Experience in natural language processing and working with LLM frameworks like LangChain or Llama-Index.
• Knowledge of evaluation techniques and agentic principles.
• Experience with database technologies including SQL, Oracle, SQL Server, or NoSQL.
• Experience using AWS services including Athena, Glue, SageMaker, and QuickSight.
• Familiarity with modern software development, DevOps strategies, and GitOps.

Preferred Skills

• Experience using machine learning models within the automotive industry.

Key Skills

Education

Not specified