About the Role
We're looking for a Machine Learning Engineer to help build and deploy AI models that power our products. You'll work on challenging problems in natural language processing, computer vision, and generative AI.
This is an opportunity to work at the forefront of AI technology and see your work directly impact users.
Responsibilities
- Design, train, and deploy machine learning models
- Build scalable ML pipelines and infrastructure
- Optimize models for production performance
- Collaborate with product and engineering teams
- Stay current with the latest ML research and techniques
- Contribute to best practices and documentation
Requirements
- 3+ years of experience in machine learning engineering
- Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow)
- Experience with LLMs and generative AI models
- Understanding of MLOps practices and tools
- Strong mathematical foundation (linear algebra, statistics, optimization)
- Experience deploying models to production
Nice to Have
- PhD or MS in Computer Science, Machine Learning, or related field
- Publications in top ML conferences (NeurIPS, ICML, ICLR)
- Experience with cloud ML platforms (AWS SageMaker, GCP Vertex AI)
- Contributions to open-source ML projects
- Experience with distributed training and inference
Benefits
- Competitive salary and equity package
- Fully remote work environment
- Flexible working hours
- Health, dental, and vision insurance
- $3,000 annual learning and conference budget
- $1,500 home office stipend
- Unlimited PTO policy
- GPU access for personal projects
- Regular team retreats
How to Apply
Send your resume, GitHub profile, and any relevant publications to careers@netora.com. Tell us about a challenging ML problem you've solved.
Netora is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.