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 & modernization, cloud native application development, DevOps, data engineering, security & compliance and everything in between. At Caylent, our people always come first.
We are a fully remote global company 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!
The Mission
At Caylent, a 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 also have a weekly 1:1 with your manager 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
- At least 3 years of hands on experience in at least a few of these ML tools/techniques:
- Build ML models in SageMaker
- Build ML models in frameworks like Tensorflow & PyTorch and deploy in SageMaker
- Train and deploy AWS pre-trained AI Services and Foundational Models
- Build and optimize models using feature definition, activation functions, hyperparameter tuning and other techniques
- Integrate ML models into real-time applications and batch workflows, recommend better infrastructure design and optimization
- Monitor, evaluate and continuously improve model performance, as well as automate these tasks using one or more tools for MLOps
- Hands on experience in these data engineering tools/techniques:
- Data integration, cleansing, transformation, and visualization using Python packages, SQL etc.
- AWS services such as Glue, EMR, Athena, DynamoDB, StepFunctions, EKS etc.
- Experience with an IaC tool such as CloudFormation, CDK or Terraform
- Excellent written and verbal communication skills
Benefits
- 100% remote work
- Equitable Life - Hybrid Plan
- 100% Premium Coverage for the employee and dependents
- Competitive phantom equity
- Long-Term Disability
- 4% Pension match (employer contribution)
- Unlimited Vacations
- Sick Leave
- Paid Holidays
- Parental Leave
- Paid for exams and certifications
- Peer bonus awards
- State of the art laptop and tools
- Equipment & Office Stipend
- Individual professional development plan
- Annual stipend for Learning and Development
- Work with an amazing worldwide team and in an incredible corporate culture
Base Salary Range: The expected base salary range for this position is CAD $114,000 - $131,000per year, commensurate with experience and qualifications.
Additional Compensation Components: In addition to the base salary, the compensation package may include bonuses, commissions, equity, and other incentives. The specific components will vary depending on the role and individual and/or company performance.
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 [email protected].
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