Machine Learning Engineer

Mid-Level Machine Learning EngineerBoston, MA (Hybrid Remote)About the RoleWe are seeking a Mid-Level Machine Learning Engineer to design, build, and deploy scalable ML systems in a production environment. This role sits at the intersection of data engineering and applied machine learning, working closely with cross-functional teams to turn data into actionable insights and intelligent applications.ResponsibilitiesDevelop, train, and deploy machine learning models in production environments.Build and maintain scalable data pipelines using modern orchestration tools.Collaborate with data scientists, engineers, and product teams to deliver ML-driven features.Optimize model performance, scalability, and reliability in cloud environments.Implement monitoring, logging, and model retraining workflows.Ensure best practices in MLOps, including versioning, testing, and CI/CD integration.Required Qualifications3–6 years of experience in machine learning engineering or related field.Strong proficiency in Python for data processing and model development.Hands-on experience with AWS services (e.g., S3, EC2, SageMaker, Lambda).Experience working with Kubernetes for containerized deployments.Solid experience with Apache Airflow for workflow orchestration.Familiarity with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.Experience building and maintaining data pipelines and ETL processes.Understanding of software engineering best practices (Git, CI/CD, testing).Preferred QualificationsExperience with MLOps tools (e.g., MLflow, Kubeflow).Knowledge of distributed computing frameworks (e.g., Spark).Exposure to real-time data processing and streaming architectures.Background in deploying models in high-availability production systems.Tech StackPython, AWS, Kubernetes, AirflowTensorFlow / PyTorch / Scikit-learnDocker, CI/CD pipelinesSQL / NoSQL databases