| POSITION | Machine Learning Engineer - Mid-level |
| REQUIRED SKILLS | Algorithm Development & Optimization - Rapid prototyping of algorithms for high-performance data-intensive applications.
- Optimization for speed efficiency and scalability in production environments.
2. Programming & Integration - Python advanced expertise for data processing ML model development and automation.
- C desirable proficiency for integration with vehicle firmware and full product lifecycle delivery.
3. Mathematical & Statistical Foundations - Strong background in:
- Linear Algebra and Geometry essential for ML graphics and computer vision.
- Probability Theory for modeling uncertainty and decision-making.
- Numerical Optimization for training and refining models.
- Statistics for model evaluation and performance analysis.
4. Deep Learning Frameworks - Hands-on experience with PyTorch and TensorFlow for model development and deployment.
5. Model Optimization & Deployment - Skilled in performance-enhancing techniques:
- Quantization
- Pruning
- TensorRT conversion
- Deploying and maintaining production machine learning use cases.
6. Domain Expertise - Proficiency in at least one specialized area:
- Computer Vision
- Large Language Models (LLMs)
- Recommender Systems
- Operations Research
7. Software Engineering Best Practices - Writing clean sustainable and modular code.
- Translating research prototypes into robust production-ready systems.
|
POSITION Machine Learning Engineer - Mid-level REQUIRED SKILLS Algorithm Development & Optimization Rapid prototyping of algorithms for high-performance data-intensive applications. Optimization for speed efficiency and scalability in production environments. 2. Programming & Inte...
| POSITION | Machine Learning Engineer - Mid-level |
| REQUIRED SKILLS | Algorithm Development & Optimization - Rapid prototyping of algorithms for high-performance data-intensive applications.
- Optimization for speed efficiency and scalability in production environments.
2. Programming & Integration - Python advanced expertise for data processing ML model development and automation.
- C desirable proficiency for integration with vehicle firmware and full product lifecycle delivery.
3. Mathematical & Statistical Foundations - Strong background in:
- Linear Algebra and Geometry essential for ML graphics and computer vision.
- Probability Theory for modeling uncertainty and decision-making.
- Numerical Optimization for training and refining models.
- Statistics for model evaluation and performance analysis.
4. Deep Learning Frameworks - Hands-on experience with PyTorch and TensorFlow for model development and deployment.
5. Model Optimization & Deployment - Skilled in performance-enhancing techniques:
- Quantization
- Pruning
- TensorRT conversion
- Deploying and maintaining production machine learning use cases.
6. Domain Expertise - Proficiency in at least one specialized area:
- Computer Vision
- Large Language Models (LLMs)
- Recommender Systems
- Operations Research
7. Software Engineering Best Practices - Writing clean sustainable and modular code.
- Translating research prototypes into robust production-ready systems.
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Job Location:
Monthly Salary:
Posted on:
30+ days ago
Vacancies:
1 Vacancy
