Caylent is looking for a Senior Machine Learning Engineer to help their customers design and document machine learning solutions on the AWS cloud, connecting business goals with technical details of feature design, model training, and inference.
Requirements
- Strong experience in building ML models for real world applications
- Strong experience in at least one of these: AWS ML Services/SageMaker, ML libraries like Keras, Tensorflow, PyTorch, Scikit-learn, MLOps tools such as MLflow, Kubeflow, Airflow, Advanced analytics using time series forecasting and/or inferential statistics
- Strong experience in one or more of these data processing solutions: Big data processing platforms like Spark, Hadoop, or streaming platforms, Data processing and cleansing using Python/Pandas, PySpark, Scala, SQL
- Strong understanding of feature definition, model meta-data, hyperparameter tuning, stochastic gradient descent, deep learning layer types and activation functions
- Experience in visualization using SageMaker, ggplot, matplotlib, or seaborn
- Experience with an IaC tool such as CloudFormation, Amazon CDK or Terraform
Responsibilities
- Work with a team to deliver machine learning solutions on AWS for customers
- Develop and implement ML models, MLOps, and analytics
- Big data processing and preparation of training data for models
- Design and document machine learning solutions on the AWS cloud
- Connect customer business goals with the details of feature design, model training and inference
- Develop solutions designed by an architect
Other
- Participate in daily standup meetings with your team
- Participate in bi-weekly agile ceremonies with the customer
- Excellent written and verbal communication skills
- We are unable to provide sponsorship for this position.
- NOTE: We’re unable to provide visa sponsorship now or at any time in the future.
