Role OverviewThe ML Engineer will design, build, and deploy production-grade ML systems with end-to-end ownership of the model lifecycle. The role involves architecting and delivering AI-powered solutions, developing and optimizing ML models, and collaborating with cross-functional teams.
What You Will Do
The ML Engineer will handle the entire AI lifecycle, including data acquisition, preprocessing, model training, deployment, inference, and monitoring in production environments. They will also participate in continuous improvement of the ML infrastructure and processes for scalability and performance.
Why It Might Be a Fit
The ideal candidate will have strong programming skills in Python, hands-on experience with ML frameworks, and familiarity with cloud environments and infrastructure. They will also have excellent communication skills and the ability to engage directly with customers and stakeholders.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field
- 1-6 years of professional experience in ML engineering
- Strong programming skills in Python (TypeScript experience is a plus)
- Hands-on experience with ML frameworks such as PyTorch or TensorFlow
- Familiarity with cloud environments and infrastructure (preferably AWS)
- Strong understanding of data pipeline design, real-time inference, and model monitoring
- Excellent communication skills with the ability to engage directly with customers and stakeholders
Benefits
- Above market base
- Bonus
- Equity
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