ChicMic Studios - Artificial Intelligence/Machine Learning Engineer

Key Responsibilities

• Design, develop, and deploy scalable machine learning models for classification, regression, NLP, and generative AI tasks.
• Build and optimize data transformation workflows using Python, Pandas, and related libraries.
• Lead AI/ML pipelines from data ingestion to model deployment, monitoring, and retraining.
• Implement model observability and monitoring for drift detection and continuous evaluation.
• Develop and deploy REST APIs to integrate ML models with production systems using frameworks like FastAPI.
• Ensure high code quality through unit/integration testing and code reviews.
• Collaborate with cross-functional teams including Data Engineers, DevOps, and Product Managers.
• Stay updated with the latest advancements in AI, ML, and GenAI frameworks and tools.
• Apply DevOps/MLOps practices to automate and manage the full ML lifecycle.
  

Required Skills

• Advanced proficiency in Python with expertise in Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch.
• Strong understanding of asynchronous programming, concurrency, and FastAPI (Starlette).
• In-depth knowledge of multithreading, multiprocessing, and Python GIL.
• Ability to write clean, efficient, and testable code.
  

Machine Learning & Deep Learning

• Strong grasp of traditional ML concepts : classification, regression, regularization (L1/L2), overfitting/underfitting, multicollinearity.
• Experience with deep learning architectures : RNNs, attention mechanisms, dropout, early stopping, GANs, diffusion models.
• Knowledge of transfer learning and pre-trained model fine-tuning.
  

MLOps

• Hands-on experience in ML pipeline design including training, deployment, and monitoring.
• Proficiency in data drift and concept drift detection and mitigation.
• Familiarity with model observability tools, unstructured data drift monitoring, and automated drift alerts.
  

Software Engineering & DevOps

• Strong expertise in REST API development, CI/CD pipelines, and integration testing.
• Experience with Docker and containerized deployments.
• Familiarity with cloud-based ML deployment (AWS, Azure) and logging/monitoring frameworks.
  

Data Engineering & Problem Solving

• Strong experience with data wrangling, transformation, joins, ranking, filtering, and preprocessing using Python/Pandas.
• Ability to handle large datasets and build efficient preprocessing workflows.
  

Nice-to-Have

• Experience in Generative AI and working with LLMs.
• Exposure to MLOps tools like MLflow, Kubeflow, or Airflow.
• Knowledge of transformer-based models, embeddings, and NLP pipelines.
• Prior contributions to open-source ML frameworks or GitHub repositories.
  

Core Skills & Proficiency

• Python
• NumPy
• PyTorch
• Machine Learning
• Deep Learning
• REST API Development
• Agile Software Development
• API Development
• Generative AI
• Artificial Intelligence