ML Engineer
Position Title
ML Engineer
Description
An ML Engineer designs, develops, and deploys machine learning models and systems, transforming data into intelligent and scalable solutions that power decision-making and automation.
Responsibilities
- Develop and train ML models using structured and unstructured data.
- Collaborate with data scientists, analysts, and product teams to define requirements.
- Implement scalable ML pipelines for model training, validation, and deployment.
- Monitor model performance and retrain as needed to ensure accuracy over time.
- Work with cloud services (AWS, GCP, Azure) and MLOps tools to deploy models.
- Optimize algorithms for performance and scalability.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
- 2 years of hands-on experience in building and deploying machine learning models.
- Strong proficiency in Python and ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.
- Solid understanding of machine learning concepts, algorithms, and statistical techniques.
- Practical experience in data preprocessing, feature engineering, model selection, and evaluation.
- Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization tools like Docker or Kubernetes.
- Experience using version control tools (Git) and working knowledge of CI/CD pipelines is a plus.
Job Benefits
- Work with cutting-edge AI and ML technologies.
- Competitive salary and flexible work arrangements.
- Continuous learning and certification support.
- Opportunity to make a real-world impact using AI.