Machine Learning Engineer
2 days ago
Key Responsibilities:
- Design, develop, and deploy machine learning models for various business use cases.
- Build and optimize data pipelines for training and inference of ML models.
- Work with structured and unstructured data to preprocess and feature engineer datasets.
- Optimize model performance and scalability for production deployment.
- Implement A/B testing and model monitoring strategies to ensure continuous improvement.
- Collaborate with data scientists to refine models and algorithms.
- Deploy ML models using cloud platforms (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes).
- Research and stay up-to-date with the latest advancements in AI and ML.
- Ensure compliance with data privacy and ethical AI guidelines.
Required Qualifications & Skills:
- BSc in Computer Science, AI, Data Science, or a related field.
- Proven experience in machine learning, deep learning, and statistical modelling.
- Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Experience with data preprocessing, feature engineering, and model evaluation.
- Knowledge of big data technologies (Spark, Hadoop) and databases (SQL, NoSQL).
- Hands-on experience with cloud services (AWS, GCP, or Azure) and MLOps tools.
- Familiarity with version control (Git), CI/CD pipelines, and containerization.
- Strong problem-solving skills and ability to work in a fast-paced environment.
- Excellent communication and teamwork skills.
Preferred Qualifications:
- Experience in natural language processing (NLP), computer vision, or reinforcement learning.
- Knowledge of model explainability, fairness, and AI ethics.
- Experience with edge AI and on-device machine learning.
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