AI/ML Engineer
1 day ago
Job Title : Python - AI/ML Engineer
Job Type : Payroll
Job Summary :
We are seeking a highly skilled and passionate Python AI/ML Engineer with strong expertise in building AI/ML solutions, deploying models to production, and managing end-to-end ML pipelines. The ideal candidate should have deep knowledge of traditional machine learning and deep learning techniques, hands-on programming experience, and a solid foundation in enterprise-grade software engineering and MLOps practices.
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 :
Programming & Python Ecosystem :
- 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 Skills & Proficiency :
- NumPy
- PyTorch
- Machine Learning
- Deep Learning
- REST API Development
- Agile Software Development
- API Development
- Generative AI
- Artificial Intelligence
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