Machine Learning Engineer

📋 Description Design, build, maintain data pipelines for ingestion, transformation, and feature engineering Develop, train, evaluate, and iterate ML models across classification, regression, clustering, NLP Fine-tune and adapt pre-trained LLMs and foundation models for specific use cases Build and manage MLOps infra for versioning, tracking, and deployment Work with structured and unstructured data at scale (text, tabular, time-series) Monitor model performance in production and implement retraining and drift detection 🎯 Requirements Strong Python skills with hands-on experience in core ML libraries (scikit-learn, PyTorch, TensorFlow) Solid data engineering experience — SQL, ETL pipelines, and large-scale datasets Practical experience with model training, evaluation, hyperparameter tuning, and deployment Familiarity with LLMs and transformer-based architectures; fine-tuning or prompt engineering in production contexts Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, DVC, or similar) Must have remote work experience and fluency with remote collaboration tools (Slack, Zoom, Google Workspace, Asana, etc.) 🎁 Benefits Fully remote role with US time zones Global company collaborations Long-term remote career Remote collaboration tooling with Slack, Zoom, and Google Workspace