Who we are
At Sway AI, we believe there’s a better way to do AI. No more expensive investments in AI tools and skillsets. No more months-long projects with uncertain results. We put compelling AI solutions in your hands using our “no code” platform. We save you time and money so that you can focus on actual decision-making.
Our team is an experienced and talented group of entrepreneurs, scientists, and engineers who share a single-minded focus to re-architect how AI/ML applications are built and deployed. A venture-backed startup, we were founded and are led by proven entrepreneurs who have built several successful companies.
Are you an ML engineer that knows the ins and outs of designing and deploying real-world cloud-based AI solutions? Do you have the skills and experience to make deploying AI models fast, secure and scalable? Do you want to work on exciting projects that help change the way people use AI? If so, we want you to join our awesome team of engineers and data scientists to help us build a new generation of no-code AI applications.
What you’ll do
- Design, develop and deploy robust, reliable and scalable ML solutions using cloud platforms such as AWS, Azure, GCP or other cloud providers
- Implement and automate ML best practices
- Collaborate with other ML engineers, data scientists, front end engineers, and product managers to ensure the quality and delivery of machine learning products
- Research and evaluate new ML technologies and trends
- Mentor and coach other ML engineers
- Design, develop and deploy machine learning models using frameworks such as TensorFlow, PyTorch, Scikit-Learn, etc.
- Implement and maintain model deployment tools such as Kubernetes, Kubeflow, MLflow, Seldon Core, etc.
- Conduct model testing and validation using tools such as Jest, Enzyme, Cypress, etc.
- Monitor and improve model performance and accuracy using tools such as TensorBoard, MLflow Tracking, etc.
What you’ll need
- PhD or MS, or equivalent, in mathematics or CS with a focus on machine learning
- 8+ years of professional experience as an ML engineer or similar role
- Experience with machine learning frameworks such as TensorFlow, PyTorch, Scikit-Learn, etc.
- Experience with model deployment tools such as Kubernetes, Kubeflow, MLflow, Seldon Core, etc.
- Experience with model testing and validation tools such as Jest, Enzyme, Cypress, etc.
- Experience with cloud platforms such as AWS, Azure, GCP or other cloud providers
- Experience with model performance and accuracy tools such as TensorBoard, MLflow Tracking
- Experience writing code in Python and writing documentation in easily understandable language
- Strong communication, collaboration and problem-solving skills
What you’ll get
- A chance to help define the company, our culture, and the industry
- A competitive compensation package
- A chance to work on exciting projects that make a positive impact
- An opportunity to learn and grow with some of the best engineers and data scientists in the industry
If you’re as excited about this opportunity as we are, don’t hesitate to apply. We can’t wait to hear from you!