We are seeking a highly motivated Machine Learning Engineer with 3–4 years of experience to design, develop, deploy, and maintain scalable machine learning models in production. The ideal candidate has hands-on experience building end-to-end ML pipelines and collaborating with cross-functional teams to solve real-world business problems.
Design, develop, and optimize machine learning models and algorithms
Perform data preprocessing, feature engineering, and exploratory data analysis
Build and maintain scalable ML pipelines and workflows
Deploy models to production using APIs or batch processing systems
Monitor model performance and implement retraining strategies
Collaborate with data engineers and product teams to translate business requirements into ML solutions
Improve model efficiency, scalability, and reliability
Maintain documentation and follow best coding practices
Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or related field
3–4 years of hands-on experience in machine learning or applied AI
Strong programming skills in Python
Experience with ML libraries such as Scikit-learn, TensorFlow, or PyTorch
Solid understanding of supervised and unsupervised learning techniques
Experience with SQL and working with large datasets
Knowledge of model evaluation metrics and validation techniques
Familiarity with Git and version control practices
Experience with MLOps tools (MLflow, Airflow, Kubeflow)
Hands-on experience with cloud platforms (AWS / GCP / Azure)
Experience with Docker and Kubernetes
Exposure to NLP, Computer Vision, or Time Series modeling
Knowledge of CI/CD pipelines