Job description
About Burq
Burq started with an ambitious mission: how can we turn the complex process of offering delivery into a simple turnkey solution.
It’s a big mission and now we want you to join us to make it even bigger! 🚀
We’re already backed by some of the Valley’s leading venture capitalists, including Village Global, the fund whose investors include Bill Gates, Jeff Bezos, Mark Zuckerberg, Reid Hoffman, and Sara Blakely. We have assembled a world-class team all over the globe.
We operate at scale, but we’re still a small team relative to the opportunity. We have a staggering amount of work ahead. That means you have an unprecedented opportunity to grow while doing the most important work of your career.
Here’s a quick overview of what you will be doing:
AI/ML Engineer
We’re growing fast and are looking for a AI/ML Engineer to help scale our platform, and help drive innovation in logistics and AI/ML-powered automation.
Design, train, and deploy machine learning models using AWS-native tools (SageMaker, Lambda, Step Functions, S3).
Collaborate with data engineers to build and maintain robust data pipelines for feature ingestion, ETL, and model training.
Fine-tune and optimize models for scalability, accuracy, and production readiness.
Implement MLOps best practices including CI/CD pipelines, model versioning, monitoring, and automated retraining workflows.
Monitor model performance, detect drift, and implement automated alerts and corrective actions.
Work with cross-functional teams (product, software, infrastructure) to integrate AI capabilities into user-facing features.
Share knowledge with the team through code reviews, documentation, and architecture discussions.
Who You Are
3–6 years of professional experience in ML engineering, data science, or related roles.
Hands-on experience with AWS services including SageMaker, Lambda, Step Functions, S3, and DynamoDB.
Proficient in Python and ML frameworks such as TensorFlow.
Proficient in Typescript and React to help bring AI/ML features into the product.
Solid understanding of data engineering concepts: ETL, batch/streaming pipelines, and data validation.
Familiar with containerization (Docker), CI/CD pipelines, and MLOps workflows.
Self-starter who thrives with autonomy and can deliver results with minimal oversight.
Strong collaboration and communication skills; comfortable explaining ML concepts to technical and non-technical stakeholders.
Bonus: AWS ML certification or equivalent hands-on experience.
Bonus: Experience with generative AI, LLMs, or advanced ML applications.
Investing in you 🙏
- Competitive Salary, Stock Options, and Performance-based Bonuses
- Fully Remote
- Comprehensive Medical, Vision and Dental Insurance
At Burq, we value diversity. We are an equal opportunity employer: we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
