AI/ML Engineer
2 days ago
Key Responsibilities:
- Develop, test, and deploy machine learning models and algorithms in production environments.
- Work with large datasets to perform data preprocessing, feature engineering, and model training.
- Build scalable pipelines for model training, validation, deployment, and monitoring.
- Collaborate with software development teams to integrate ML models into applications.
- Optimize model performance through hyperparameter tuning, ensembling, and algorithm selection.
- Stay updated with latest ML research and technologies, recommending adoption where appropriate.
- Mentor junior engineers and participate in code reviews.
- Develop tools for automating model testing and deployment workflows.
Required Skills & Qualifications:
- Bachelor's or Master's degree in Computer Science, Machine Learning, Statistics, or related fields.
- 4 to 6 years of professional experience in machine learning or data science roles.
- Proficiency in Python and ML libraries like TensorFlow, PyTorch, Scikit-learn.
- Strong understanding of supervised, unsupervised, and reinforcement learning techniques.
- Experience with deep learning architectures such as CNNs, RNNs, Transformers.
- Hands-on experience with data pipelines, feature engineering, and model deployment.
- Familiarity with cloud platforms like AWS, Azure, or GCP.
- Experience with containerization tools like Docker and orchestration with Kubernetes is a plus.
Strong problem-solving skills and ability to work in a collaborative environment.
Preferred Qualifications:
- Knowledge of NLP, computer vision, or time-series analysis.
- Experience with ML lifecycle management tools (MLflow, Kubeflow).
- Familiarity with big data frameworks (Spark, Hadoop).
- Experience with DevOps/CI-CD pipelines for ML.
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