Senior Machine Learning Engineer

Senior Machine Learning Engineer - Not an Active Opening, Building Talent Pipeline ARGENTINA Caylent is a cloud native services company that helps organizations bring the best out of their people and technology using Amazon Web Services (AWS). We provide a full-range of AWS services including workload migrations and modernization, cloud native application development, DevOps, data engineering, security and compliance, and everything in between. At Caylent, our people always come first. We are a global company and operate fully remote with employees in Canada, the United States, and Latin America. We celebrate the culture of each of our team members and foster a community of technological curiosity. Come talk to us to learn more about what it means to be a Caylien Note: This isn’t an active role right now, but we’re building a community of great talent for future opportunities at Caylent. If your background aligns with what we’re looking for, our team may reach out to learn more about you and explore potential future fits. The Mission At Caylent, a Senior Machine Learning Engineer works as an integral part of a cross-functional delivery team to design and document machine learning solutions on the AWS cloud for our customers. We are looking for someone that has a strong understanding of the various model types and tools, and can help our customers connect their business goals with the details of feature design, model training and inference. You will develop solutions designed by an architect. You will participate in daily standup meetings with your team and bi-weekly agile ceremonies with the customer. Your manager will have a weekly 1:1 with you to help guide you in your career and make the most of your time at Caylent. Your Assignments Work with a team to deliver machine learning solutions on AWS for customers Participate in and contribute to daily standup meetings Develop and implement ML models, MLOps, and analytics Big data processing and preparation of training data for models Your Qualifications Strong experience in building ML models for real world applications Strong experience in at least one of these: AWS ML Services/SageMaker 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 Excellent written and verbal communication skills Pay in USD Generous holidays and flexible PTO Paid for exams and certifications Peer bonus awards State of the art laptop and tools Equipment & Office Stipend Annual stipend for Learning and Development Work with an amazing worldwide team and in an incredible corporate culture This role may require up to 25% travel, depending on business needs. Caylent is a place where everyone belongs. We celebrate diversity and are committed to creating an inclusive environment for all employees. Our approach helps us to build a winning team that represents a variety of backgrounds, perspectives, and abilities. So, regardless of how your diversity expresses itself, you can find a home here at Caylent. We are proud to be an equal opportunity employer. We prohibit discrimination and harassment of any kind based on race, color, religion, national origin, sex (including pregnancy), sexual orientation, gender identity, gender expression, age, veteran status, genetic information, disability, or other applicable legally protected characteristics. If you would like to request an accommodation due to a disability, please contact us at NOTE: We’re unable to provide visa sponsorship now or at any time in the future. #J-18808-Ljbffr