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Machine Learning Scientist - AI for Code(m/w/x)
Prototyping ML models for code bug/vulnerability detection and LLM solutions for contextual code analysis. Hands-on experience with modern large language model architectures and NLP/PLP focus required. Flexible work policy.
Requirements
- Advanced academic background (Master’s or PhD) in Computer Science, Machine Learning, or a related quantitative field
- Strong industry experience in machine learning and modern software engineering practices
- Solid programming skills in Python and hands-on experience with core ML/DL frameworks (e.g., PyTorch, TensorFlow, Hugging Face)
- Proven experience in applied Machine Learning with a focus on Natural Language Processing (NLP) or Programming Language Processing (PLP)
- Hands-on experience with modern LLM architectures and techniques, such as Fine-tuning strategies, advanced prompt engineering, and working with vector databases
- Experience with large-scale data processing frameworks and cloud infrastructure (e.g. AWS)
- Experience driving research projects from ideation to prototype with high autonomy
- Excellent communication skills in English and ability to explain complex scientific topics clearly
Tasks
- Stay updated on ML, Deep Learning, and LLM advancements
- Identify opportunities to enhance products within the SDLC
- Design and prototype advanced ML models for bug and vulnerability detection
- Validate models that address complex code issues
- Develop LLM-based solutions for contextual code analysis
- Implement Retrieval-Augmented Generation (RAG) techniques
- Fine-tune models on proprietary codebases
- Explore agentic systems for automated code remediation
- Build and manage data pipelines for large code-centric datasets
- Gather and process data for training specialized models
- Collaborate with engineering and product teams to integrate ML prototypes
- Ensure products meet the needs of a global user base
- Articulate complex technical concepts to diverse stakeholders
- Document research findings for technical and non-technical audiences
Work Experience
- approx. 4 - 6 years
Education
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- PyTorch
- TensorFlow
- Hugging Face
- AWS
Benefits
Flexible Working
- Flexible work policy
Informal Culture
- Dynamic work culture
Learning & Development
- Continuous education support
Social Impact
- Diversity, Equity, and Inclusion commitment
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Machine Learning Scientist - AI for Code(m/w/x)
Prototyping ML models for code bug/vulnerability detection and LLM solutions for contextual code analysis. Hands-on experience with modern large language model architectures and NLP/PLP focus required. Flexible work policy.
Requirements
- Advanced academic background (Master’s or PhD) in Computer Science, Machine Learning, or a related quantitative field
- Strong industry experience in machine learning and modern software engineering practices
- Solid programming skills in Python and hands-on experience with core ML/DL frameworks (e.g., PyTorch, TensorFlow, Hugging Face)
- Proven experience in applied Machine Learning with a focus on Natural Language Processing (NLP) or Programming Language Processing (PLP)
- Hands-on experience with modern LLM architectures and techniques, such as Fine-tuning strategies, advanced prompt engineering, and working with vector databases
- Experience with large-scale data processing frameworks and cloud infrastructure (e.g. AWS)
- Experience driving research projects from ideation to prototype with high autonomy
- Excellent communication skills in English and ability to explain complex scientific topics clearly
Tasks
- Stay updated on ML, Deep Learning, and LLM advancements
- Identify opportunities to enhance products within the SDLC
- Design and prototype advanced ML models for bug and vulnerability detection
- Validate models that address complex code issues
- Develop LLM-based solutions for contextual code analysis
- Implement Retrieval-Augmented Generation (RAG) techniques
- Fine-tune models on proprietary codebases
- Explore agentic systems for automated code remediation
- Build and manage data pipelines for large code-centric datasets
- Gather and process data for training specialized models
- Collaborate with engineering and product teams to integrate ML prototypes
- Ensure products meet the needs of a global user base
- Articulate complex technical concepts to diverse stakeholders
- Document research findings for technical and non-technical audiences
Work Experience
- approx. 4 - 6 years
Education
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- PyTorch
- TensorFlow
- Hugging Face
- AWS
Benefits
Flexible Working
- Flexible work policy
Informal Culture
- Dynamic work culture
Learning & Development
- Continuous education support
Social Impact
- Diversity, Equity, and Inclusion commitment
About the Company
Sonar
Industry
IT
Description
Sonar helps prevent code quality and security issues, enhancing developer productivity with AI-driven tools.
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