Job Description
Develop and deploy machine learning models into production environments
- Train and fine-tune models using large and diverse datasets
- Implement AI techniques such as natural language processing (NLP), computer vision, and deep learning
- Collaborate with data scientists, ML engineers, and software developers to optimize model performance and scalability
- Utilize cloud-based AI services for scalable deployment and model management
Requirements
4+ year in Python and machine learning frameworks like TensorFlow or PyTorch
2+ years experience with data science libraries such as NumPy, Pandas, and Scikit-learn
2+ years experience of supervised, unsupervised, and deep learning techniques
Familiarity with cloud AI services (e.g., AWS SageMaker, Google AI Platform, Azure ML)
Strong problem-solving skills and ability to work in a fast-paced environment
Preferred Qualifications
Experience with model monitoring and performance tuning in production
Exposure to MLOps tools and CI/CD for ML pipelines
Understanding of model explainability and ethical AI practices
No Referrers Available
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