Machine Learning Engineer
hace 4 semanas
Caylent is a cloud native services company that helps organizations unlock the full potential of their people and technology using Amazon Web Services (AWS). We provide a comprehensive range of AWS services, including workload migrations & modernization, cloud native application development, DevOps, data engineering, security & compliance, and more. At Caylent, our people are our top priority.
We are a fully remote global company with employees in Canada, the United States, and Latin America. We celebrate the unique culture of each of our team members and foster a community of technological curiosity. If you're passionate about AI and cloud computing, come talk to us to learn more about what it means to be a Caylien.
The MissionAs a Machine Learning Engineer at Caylent, you'll work 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're looking for someone with a strong understanding of various model types and tools, who can help our customers connect their business goals with the details of feature design, model training, and inference. You'll 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
- 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
- Medical Insurance for you and eligible dependents
- 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
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
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LinkedIn Profile
At Caylent, we are dedicated to creating a diverse and inclusive workplace. To support our efforts in fostering a more equitable recruitment process, we invite you to share your gender identity voluntarily. This information is optional and will be kept confidential, used only to help us track and improve our diversity initiatives. If you prefer not to answer, you're welcome to select 'Prefer Not to Respond'. * Select...
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