Senior Machine Learning Engineer

Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related field. 5+ years of experience in building, deploying, and scaling machine learning models in production. Experience deploying Generative AI models, RAG, AI Agents, and prompt engineering. Proven experience with the full product lifecycle from R&D to deployment. Experience in a product-based company, preferably a startup. Strong expertise in Python and SQL. Experience with cloud platforms (AWS, GCP, or Azure). Experience with containerization (Docker, Kubernetes). Experience with real-time data processing, anomaly detection, and time-series forecasting. Experience with large datasets and big data technologies like Spark and Kafka. First-principles thinking and excellent problem-solving skills. Self-starter mentality with the ability to take ownership and work autonomously. Excellent communication skills.

Develop and deploy machine learning models from research to production. Own the end-to-end ML pipeline. Design and implement machine learning algorithms for visibility, prediction, demand forecasting, and freight audit. Ensure reliable and scalable ML infrastructure using MLOps best practices. Perform feature engineering, model tuning, and validation. Build, test, and deploy real-time prediction models.