Machine Learning Engineer

Role & responsibilities

A Machine Learning Engineer designs, builds, and deploys machine learning models and systems to solve real-world problems, bridging data science and software engineering . They focus on creating scalable, production-ready AI applications that automate predictions and insights from data .

Key Responsibilities

• Design and develop ML systems, including selecting algorithms, preprocessing data, and building data pipelines for model training .
• Run experiments, perform statistical analysis, fine-tune models, and monitor performance to ensure accuracy and reliability in production .
• Collaborate with teams to define objectives, deploy models via APIs or services, and stay updated on ML advancements .

Preferred candidate profile

• Proficiency in Python/R, ML frameworks like TensorFlow/PyTorch, and tools for data handling (e.g., Pandas, SQL) .
• Strong knowledge of statistics, algorithms, data structures, and software engineering principles along good understanding on Machine learning concepts
• Experience with cloud platforms, DevOps (Docker, Kubernetes), and problem-solving for large datasets; typically, a bachelors in CS/Math with 3+ years relevant experience