We are seeking a Machine Learning Engineer to design, build, and deploy scalable machine learning models that power data-driven products and decisions. You will work closely with data scientists, software engineers, and product teams to translate business problems into production-ready ML solutions.
Design, develop, and deploy machine learning models for real-world applications
Build end-to-end ML pipelines (data ingestion, training, evaluation, deployment, monitoring)
Optimize models for performance, scalability, and reliability
Collaborate with data scientists to productionize research models
Work with large datasets and perform feature engineering
Monitor model performance and retrain models as needed
Write clean, maintainable, and well-documented code
Stay up to date with the latest ML techniques and tools
Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field (or equivalent experience)
Strong programming skills in Python
Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
Solid understanding of machine learning algorithms and concepts
Experience with data processing tools (NumPy, Pandas, SQL)
Familiarity with software engineering best practices (Git, testing, CI/CD)
Experience deploying ML models to production
Knowledge of cloud platforms (AWS, GCP, or Azure)
Experience with MLOps tools (MLflow, Kubeflow, Airflow, etc.)
Understanding of distributed systems and big data tools (Spark, Kafka)
Experience with deep learning, NLP, or computer vision