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 field3+ years of experience as a Machine Learning Engineer or similar roleStrong proficiency in PythonExperience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learnSolid understanding of machine learning algorithms, statistics, and data structuresExperience with SQL and data manipulation toolsFamiliarity with software engineering best practices (version control, testing, CI / CD)Preferred Qualifications
Experience deploying ML models in productionKnowledge of MLOps tools and workflowsExperience with cloud platforms (AWS, GCP, or Azure)Familiarity with Docker, Kubernetes, and REST APIsExperience with big data tools (Spark, Kafka, Airflow)Background in NLP, computer vision, or recommendation systemsTech Stack
Python, SQLPyTorch / TensorFlowAWS / GCP / AzureDocker, KubernetesGit, CI / CD pipelines