Machine Learning Engineer

About the Role We are seeking a Machine Learning Engineer to design, build, and deploy scalable ML models that power data-driven products and decisions. You will work closely with data scientists, software engineers, and product teams to take models from research to production in a fully remote environment.

Key Responsibilities Design, develop, and deploy machine learning models for production use Build and maintain scalable ML pipelines (data ingestion, training, evaluation, deployment) Collaborate with product and engineering teams to translate business requirements into ML solutions Optimize model performance, reliability, and scalability Monitor models in production and retrain as needed Conduct experiments and evaluate models using appropriate metrics Write clean, maintainable, and well-documented code

Required Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field 3+ years of experience as a Machine Learning Engineer or similar role Strong proficiency in

Python Experience with ML frameworks such as

TensorFlow, PyTorch, or Scikit-learn Solid understanding of machine learning algorithms, statistics, and data structures Experience with SQL and data manipulation tools Familiarity with software engineering best practices (version control, testing, CI/CD)

Preferred Qualifications Experience deploying ML models in production Knowledge of

MLOps

tools and workflows Experience with cloud platforms (AWS, GCP, or Azure) Familiarity with Docker, Kubernetes, and REST APIs Experience with big data tools (Spark, Kafka, Airflow) Background in NLP, computer vision, or recommendation systems Tech Stack Python, SQL PyTorch / TensorFlow AWS / GCP / Azure Docker, Kubernetes Git, CI/CD pipelines