Machine Learning Engineer
3 weeks ago
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.
Mid-Senior level
Employment typeContract
Job functionInformation Technology, Engineering, and Science
IndustriesBanking, Information Services, and Technology, Information and Media
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