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Caylent is an AI-first cloud services company that helps organizations turn ambitious ideas into meaningful business impact. As an AWS Premier Tier Services Partner and a charter member of Anthropic’s Claude Partner Network, we combine deep expertise in AWS, artificial intelligence, and Anthropic’s Claude platform to help customers modernize their technology, build intelligent products, and move AI from experimentation into production. Our capabilities span generative and agentic AI, cloud migration and modernization, cloud-native application development, data and analytics, DevOps, managed services, security and compliance, and customer experience transformation. 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! 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 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 Excellent written and verbal communication skills Benefits 100% remote work Generous holidays and flexible PTO 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 This role may require up to 25% travel, depending on business needs. NOTE: We’re unable to provide visa sponsorship now or at any time in the future. At Caylent, we are committed to fair, transparent, and inclusive hiring practices. As part of our recruitment process, we may use artificial intelligence (AI) tools or automated systems to assist with the screening and evaluation of applications to help match candidate qualifications with job requirements. These tools are designed to support — not replace — human decision-making. Final hiring decisions are always made by our trained recruitment professionals. If an AI or automated tool is used during your application process, it will only be in accordance with applicable laws and regulations, and your information will be handled in a secure and confidential manner. If you have any questions, please contact talent@caylent.com 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 hr@caylent.com.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.