Senior Machine Learning Engineer
WFA Digital Insight
The demand for skilled machine learning engineers has surged in recent years, with a notable 25% increase in job postings in the last year alone. As companies like Caylent continue to drive innovation in cloud native services, the need for experts who can design and implement effective machine learning solutions has become crucial. With the global machine learning market expected to reach $30 billion by 2027, professionals with strong experience in building ML models, MLOps, and analytics are in high demand. Caylent's commitment to fostering a community of technological curiosity and its focus on employees' growth make it an attractive destination for those looking to advance their careers in machine learning.
Job Description
About the Role
The Senior Machine Learning Engineer plays a pivotal role in designing and documenting machine learning solutions on the AWS cloud for Caylent's customers. This position is integral to a cross-functional delivery team, working closely with architects, engineers, and customers to connect business goals with the intricacies of feature design, model training, and inference. The role requires a deep understanding of various model types, tools, and the ability to develop solutions that align with customer needs.As a Senior Machine Learning Engineer at Caylent, you will be part of a global team that operates fully remotely, with a culture that celebrates technological curiosity and community. Your day-to-day responsibilities will include participating in daily standup meetings, contributing to bi-weekly agile ceremonies, and working closely with your manager to guide your career growth and optimize your time at Caylent.
What You Will Do
- Develop and implement machine learning models, MLOps, and analytics on the AWS cloud
- Collaborate with a team to deliver machine learning solutions tailored to customer needs
- Participate in and contribute to daily standup meetings and bi-weekly agile ceremonies
- Work on big data processing and preparation of training data for models
- Develop solutions designed by architects, focusing on efficiency and scalability
- Engage in continuous learning to stay updated with the latest advancements in machine learning and AWS services
- Contribute to the development of best practices and standards for machine learning within the company
- Collaborate with cross-functional teams to integrate machine learning solutions with other services and products
- Participate in code reviews and ensure high-quality code that meets Caylent's standards
What We Are Looking For
- Strong experience in building ML models for real-world applications
- Experience with AWS ML Services, SageMaker, or ML libraries like Keras, TensorFlow, PyTorch, Scikit-learn
- Knowledge of MLOps tools such as MLflow, Kubeflow, Airflow
- Advanced analytics skills using time series forecasting and/or inferential statistics
- Experience with big data processing solutions like Spark, Hadoop, or streaming platforms
- Strong understanding of feature definition, model metadata, hyperparameter tuning, stochastic gradient descent, deep learning layer types, and activation functions
- Experience with visualization tools like SageMaker, ggplot, matplotlib, or seaborn
- Excellent written and verbal communication skills
- Ability to work in a remote, distributed team environment
Nice to Have
- Experience with an IaC tool such as CloudFormation, Amazon CDK, or Terraform
- Knowledge of containerization using Docker
- Experience with agile development methodologies
- Certification in AWS or machine learning
- Experience working with global teams and customers
Benefits and Perks
- Pay in USD
- 100% remote work with flexible working hours
- Generous holidays and flexible PTO
- Competitive phantom equity
- 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
- Opportunity to work with an amazing worldwide team in an incredible corporate culture
How to Stand Out
- Ensure you have a strong portfolio that showcases your machine learning projects and accomplishments.
- Practice explaining technical concepts in simple terms to prepare for interviews where you may need to communicate with non-technical stakeholders.
- Highlight any experience you have with AWS services, as this is a key requirement for the role.
- Be prepared to discuss your experience with MLOps and how you have implemented it in previous roles.
- Research Caylent's culture and values to understand how you can contribute to and thrive in their community.
- Consider reaching out to current or former employees to gain insights into the company culture and what it's like to work as a Senior Machine Learning Engineer at Caylent.
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