eTeam
Role name: ML Engineer
Work Location: Bellevue, US (onsite)
Role and responsibilities:
5+ years of experience in AI/ML development • Strong programming skills in Python (preferred), R, or Java. • Experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or XGBoost. • Solid understanding of machine learning algorithms and statistical modeling. • Experience with data manipulation tools (e.g., Pandas, NumPy) and SQL. • Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices. • Excellent problem-solving and communication skills. Design, implement, and optimize machine learning models (supervised, unsupervised, reinforcement learning). • Work on NLP, computer vision, recommendation systems, and predictive analytics projects. • Perform feature engineering, data preprocessing, and model selection. • Collaborate with Data Engineers to acquire and preprocess large datasets. • Build data pipelines to support training, testing, and deployment of models. • Ensure data quality, consistency, and reliability. • Deploy ML models into production environments using CI/CD and MLOps practices. • Monitor model performance, retrain models, and handle model versioning. • Optimize inference performance and resource utilization. • Stay current with the latest ML/AI technologies, frameworks, and research. • Evaluate new algorithms, tools, and libraries to improve model performance. • Experiment with novel approaches to solve complex business problems. • Work with software engineers, data scientists, and product managers to integrate ML solutions into applications. • Mentor junior engineers and share best practices in ML development and deployment.
Role and responsibilities:
5+ years of experience in AI/ML development • Strong programming skills in Python (preferred), R, or Java. • Experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or XGBoost. • Solid understanding of machine learning algorithms and statistical modeling. • Experience with data manipulation tools (e.g., Pandas, NumPy) and SQL. • Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices. • Excellent problem-solving and communication skills. Design, implement, and optimize machine learning models (supervised, unsupervised, reinforcement learning). • Work on NLP, computer vision, recommendation systems, and predictive analytics projects. • Perform feature engineering, data preprocessing, and model selection. • Collaborate with Data Engineers to acquire and preprocess large datasets. • Build data pipelines to support training, testing, and deployment of models. • Ensure data quality, consistency, and reliability. • Deploy ML models into production environments using CI/CD and MLOps practices. • Monitor model performance, retrain models, and handle model versioning. • Optimize inference performance and resource utilization. • Stay current with the latest ML/AI technologies, frameworks, and research. • Evaluate new algorithms, tools, and libraries to improve model performance. • Experiment with novel approaches to solve complex business problems. • Work with software engineers, data scientists, and product managers to integrate ML solutions into applications. • Mentor junior engineers and share best practices in ML development and deployment.