Machine Learning Engineer
RefuelAbout the Role
As a Machine Learning Engineer at Refuel, you will be at the forefront of developing the core machine learning algorithms that power our platform. This role involves working in domains such as representation learning, clustering, and outlier detection in high-dimensional spaces. You will also focus on improving label quality in real-world datasets and active learning.
Key Responsibilities
- Develop and implement machine learning algorithms for our platform.
- Stay updated with the latest research in machine learning for content understanding.
- Apply state-of-the-art deep learning models to solve customer problems.
- Collaborate with engineering and design teams to enhance product features and scalability.
- Contribute to defining and evolving our engineering stack as we scale.
- Participate in hiring and mentoring new team members.
Ideal Candidate
You will be a great fit if you have:
- Experience building ML applications for unstructured data (image, video, text, audio streams), including data collection, model development, and deployment.
- Familiarity with Python and hands-on experience with deep learning frameworks like PyTorch and TensorFlow.
- Strong communication skills and enjoy working in a collaborative environment.
- Curiosity about the early startup and company-building journey.
- Bonus: Experience with AWS machine learning stack or published research in machine learning.
Our Tech Stack
- Infrastructure: AWS, Serverless, Kubernetes
- Backend: Python, FastAPI, Postgres, DynamoDB
- Frontend: React, Typescript
What We Offer
- Competitive salary and meaningful equity in the company.
- Opportunity to make a significant impact as a member of our early team.
- A collaborative environment where the best ideas win.
Join us at Refuel and be part of a team that is accelerating the time to production for ML applications built on unstructured data, enabling them to continually improve in the real world.
Benefits Extracted with AI
- Competitive salary
- Meaningful equity
- Opportunity to create a massive impact
- Collaborative environment
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