Machine Learning Research Engineer
Tasks
- Advance agentic AI
- Advance context engineering
- Build data pipelines
- Collaborate with domain experts
- Communicate research findings
- Deploy LLM based systems
- Deploy machine learning models
- Design ML powered applications
- Develop LLM-based systems
- Enable learning from human feedback
- Integrate ML into real world applications
- Label training data
- Measure application outcomes
- Train and evaluate LLM systems
- Translate insights into computational frameworks
Perks/Benefits
Skills/Tech-stack
Agentic AI | Context engineering | Data Pipelines | Data labeling | Deep learning | Fine Tuning | Human Feedback | LLM Evaluation | Langgraph | Language Models | Language Processing | Large Language Models | Learning from Human Feedback | Machine Learning | Natural Language | Natural Language Processing | Preprocessing | PyTorch | Python | Reinforcement Learning | Reinforcement Learning from Human Feedback | Supervised Fine Tuning | VLLM
Education
Bachelor of Engineering | Master of Engineering | Master of Science | PhD
Regions
Countries
States
Cities
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