Machine Learning Engineer

As a Machine Learning Engineer, you will be responsible for designing and implementing scalable machine learning models throughout the entire lifecycle - from data preprocessing to deployment. Your role will involve leading feature engineering and model optimization efforts to enhance performance and accuracy. Additionally, you will build and manage end-to-end ML pipelines using MLOps practices, ensuring seamless deployment, monitoring, and maintenance of models in production environments. - Lead feature engineering and model optimization efforts - Build and manage end-to-end ML pipelines using MLOps practices - Collaborate with data scientists and product teams to understand business requirements and translate them into effective ML solutions - Conduct advanced data analysis and create visualization dashboards for insights - Maintain detailed documentation of models, experiments, and workflows In terms of required skills: - Must have at least 3 years of experience in machine learning development - Proficiency in Python using Pandas, NumPy, and Scikit-learn for advanced data handling and feature engineering - Strong hands-on expertise in TensorFlow or PyTorch for deep learning model development Desirable skills include: - Experience with MLOps tools like MLflow or Kubeflow for model management and deployment - Familiarity with big data frameworks such as Spark or Dask - Exposure to cloud ML services like AWS SageMaker or GCP AI Platform - Working knowledge of Weights & Biases and DVC for experiment tracking and versioning - Experience with Ray or BentoML for distributed training and model serving Join our team and contribute to cutting-edge machine learning projects while continuously improving your skills and expertise in a collaborative and innovative environment.,