AI/ML Engineer
2 weeks ago
AI/ML Engineer Requirements
- 6+ years' experience in data domain (data analysis, database development).
- Minimum 4 years' as an AI/ML Engineer, specializing in data wrangling, cleaning, and feature engineering.
- Minimum 3 years' strong knowledge of Azure AI for deploying ML models and services like OCR, Object Recognition, Text to Speech, Document Search, etc.
- Minimum 3 years' experience with machine learning libraries and frameworks (TensorFlow, PyTorch, etc.).
- Minimum 2 years' on Apache Spark or Azure Databricks. Proficient in Python, R, PySpark, and SparkSQL.
- Expertise in Apache Spark and Databricks (ML Flow and Auto ML) for large-scale data processing and model training.
- Strong knowledge of Generative AI, Prompt Engineering, Embedding, and Vector DBs, Workflows, Agents, and frameworks like LangChain and HuggingFace.
- Familiarity with deep learning architectures (CNNs, RNNs).
- Experience with NLP libraries (NLTK, spaCy) is beneficial.
- Working Knowledge of Power BI or other data visualization tools is advantageous.
- Good understanding of MLOps tools and processes.
Role & Responsibilities
- Evaluate and define functional requirements for BI and DW solutions.
- Design and develop machine learning models for complex business problems using supervised and unsupervised learning.
- Design and develop Generative AI use cases leveraging LLMs and frameworks.
- Lead data identification and analysis efforts for data sources collaborating directly with data owner teams.
- Collaborate with data scientists and software engineers to integrate ML models into production systems leveraging Databricks.
- Train, evaluate, and optimize machine learning models on Databricks.
- Monitor model performance and identify areas for enhancement.
- Visualize outputs using BI Tools.
- Stay updated on the latest AI, machine learning, and Generative AI advancements.
- Work with DevOps team to implement CI/CD pipelines.
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