Machine Learning Engineer

We are looking for a skilled Machine Learning Engineer to design, build, and deploy production-ready machine learning solutions that solve real business problems. In this role, you will work at the intersection of data, engineering, and product, turning data into scalable, reliable, and measurable ML-driven features.

This position is ideal for an engineer with strong fundamentals in machine learning and software engineering who enjoys taking models from experimentation to production and continuously improving them over time.

Key Responsibilities

• Design, develop, and deploy machine learning models to solve business problems
• Build and maintain automated ML pipelines for data processing, training, and evaluation
• Work with cross-functional teams to define ML requirements and validate model outputs
• Perform feature engineering, model tuning, and experimental analysis
• Deploy models into production environments and monitor performance over time
• Collaborate with data engineers to improve dataset quality and consistency
• Document model architecture, performance metrics, and system workflows
• Research new algorithms, tools, and frameworks to improve predictive accuracy and efficiency

Requirements

• 3–5+ years of experience building and deploying machine learning models in production environments
• Strong proficiency in Python and hands-on experience with ML frameworks such as TensorFlow, PyTorch, and scikit-learn
• Solid understanding of machine learning algorithms, statistical concepts, and model evaluation techniques
• Practical experience with ML pipelines, MLOps practices, and production deployment of ML models
• Experience with data preprocessing, feature engineering, and working with large-scale datasets
• Ability to translate business and product requirements into effective ML solutions
• Strong communication skills and the ability to collaborate effectively with cross-functional teams