remote
AI/ML Engineer - UST
ML Engineer
Design, develop, and deploy machine learning models and pipelines using Python, deep‑learning frameworks, and cloud services to deliver data‑driven solutions for enterprise clients.
About the role
Key Responsibilities
- Develop, train, and fine‑tune machine learning and deep learning models using Python, TensorFlow, PyTorch, and Scikit‑learn.
- Build end‑to‑end ML pipelines, including data preprocessing, feature engineering, model validation, and deployment.
- Collaborate with data engineers and product teams to integrate models into scalable cloud environments (AWS) and containerized services (Docker).
- Monitor model performance in production, implement retraining strategies, and ensure robustness and compliance.
- Research and apply state‑of‑the‑art algorithms to solve business problems and improve existing solutions.
Requirements
- Bachelor’s or higher in Computer Science, Engineering, or a related field with 1–3 years of hands‑on ML experience.
- Proficiency in Python and experience with deep‑learning frameworks such as TensorFlow or PyTorch.
- Solid understanding of statistical modeling, feature engineering, and model evaluation techniques.
- Experience deploying models on AWS services (SageMaker, EC2, Lambda) and containerizing applications with Docker.
- Strong problem‑solving skills, ability to work in cross‑functional teams, and effective communication of technical concepts.
Skills
pythontensorflowpytorchawsdocker