onsite
Machine Learning Engineer
Machine Learning Engineer
This role is for a Machine Learning Engineer responsible for scaling ML models, building and maintaining production pipelines for training and prediction, and developing reusable deployment and monitoring tools. The role also involves mentoring junior colleagues and participating in industry events.
About the role
Responsibilities
- Work with data scientists to refine the ML model and scale it up
- Create and maintain ML model training/prediction pipelines in production
- Create re-usable tools and frameworks for ML model deployment and monitoring
- Mentor junior colleagues, conduct internal workshops and external meetups, participate in external conferences and give talks.
Requirements
- Solid understanding of machine learning models and related mathematics
- Solid understanding of engineering processes and principles.
- Strong understanding of both object-oriented and functional programming concepts and languages.
- Experience building production data pipelines for model training/prediction
- Experience working with large data sets, coming from varied sources
- Experience working with open-source ML libraries such as Tensorflow, PyTorch and XGBoost
- Experience working with cloud-based ML model deployment and automation tools (such as Airflow, Docker)
- Experience working with engineering tools for infrastructure and deployment (such as Docker, Kubernetes)
- Familiarity with data engineering technologies (Kafka/Flink/Spark etc)
- Typical background: Bachelors or Masters in computer science with 4+ years of experience working as a Software Engineer or Machine Learning Engineer in a product company
- Familiarity with infrastructure automation tools like Terraform
- In-depth understanding of data engineering technologies (Kafka/Flink/Spark etc)
Skills
Machine LearningTensorFlowPyTorchXgboostAirflowDockerKuberneteskafkaFlinkSparkTerraformobject oriented programmingfunctional programming