MachineLearningEngineer

Join Hire Hangar and work with fast-growing global companies while building a long-term, remote career. MACHINE LEARNING ENGINEER (DATA & AI) Remote US Time Zones (EST–PST) Role Overview We are looking for a skilled Machine Learning Engineer with a strong data engineering foundation to build, train, and deploy ML models and data pipelines across a range of complex environments. This role sits at the intersection of data and AI — you will be responsible for everything from sourcing, cleaning, and structuring data to training models, evaluating performance, and getting solutions into production. The ideal candidate thinks rigorously about data quality, understands the full ML lifecycle, and is equally comfortable working with large datasets as they are fine-tuning models or building scalable inference pipelines. Key Responsibilities - Design, build, and maintain robust data pipelines for ingestion, transformation, and feature engineering - Develop, train, evaluate, and iterate on machine learning models across classification, regression, clustering, and NLP tasks - Fine-tune and adapt pre-trained LLMs and foundation models for specific use cases and datasets - Build and manage MLOps infrastructure including model versioning, experiment tracking, and deployment pipelines - Work with structured and unstructured data at scale — including text, tabular, and time-series data - Monitor model performance in production and implement retraining and drift-detection strategies - Collaborate with engineering and product teams to translate data insights into actionable AI features - Document data schemas, model architectures, and pipeline logic clearly and thoroughly Required Qualifications - Strong Python skills with hands-on experience in core ML libraries (scikit-learn, PyTorch, TensorFlow, or similar) - Solid data engineering experience — SQL, ETL pipelines, and working with large-scale datasets - Practical experience with model training, evaluation, hyperparameter tuning, and