Role Overview
We are looking for an AI / Machine Learning Engineer to build and scale our intelligent systems. You will take prototype models from data science, optimize them for production, and integrate them into our core software architecture to drive automated decisions.
Key Responsibilities
- Model Development: Design, train, and fine-tune machine learning and deep learning models to solve business problems.
- Data Pipelines: Build and maintain scalable ETL (Extract, Transform, Load) pipelines to process large-scale structured and unstructured data.
- Production Deployment: Deploy ML models into cloud production environments, ensuring high availability and low latency.
- MLOps: Implement CI/CD for machine learning (MLOps) to automate model monitoring, retraining, and version control.
- System Integration: Collaborate with backend engineers to integrate model outputs into user-facing software applications via APIs.
- Research & Evaluation: Keep up with latest AI advancements, evaluate new algorithms, and benchmark model performance against metrics.
Requirements
- Experience: 3+ years of professional software engineering experience with a strong focus on AI/ML applications.
- Programming: Expert proficiency in Python, including libraries like NumPy, Pandas, and Scikit-Learn.
- Frameworks: Deep understanding of deep learning frameworks such as PyTorch or TensorFlow.
- Cloud & Infrastructure: Experience deploying models on cloud platforms (AWS, GCP, or Azure) using Docker, Kubernetes, or serverless tools.
- Big Data: Familiarity with data processing tools like Spark, SQL, and NoSQL databases.
- Education: Master’s or Bachelor’s degree in Computer Science, Data Science, Mathematics, or a related technical field.
