Machine Learning Engineer - IT
Tasks
- Apply prompt learning and continuous iteration
- Build RAG pipelines
- Build eval pipelines to measure model and prompt changes
- Configure and analyze LLM metrics with eval frameworks
- Create agentic workflows and orchestration
- Create massive data pipelines for training datasets
- Define system components and contracts with spec driven development
- Deploy computer vision and NLP models to production
- Design low-latency inference solutions
- Develop data pipelines for training and evaluation
- Fine-tune foundation models
- Implement LLM and VLM lifecycle from exploration to context engineering
- Mitigate regressions and hallucinations
- Optimize model throughput and resource usage
Perks/Benefits
Skills/Tech-stack
BigQuery | CI/CD | Clean architecture | Computer Vision | Context engineering | Fine Tuning | Huggingface | Langchain | Langgraph | Language Models | Language Processing | Large Language Models | Llama.cpp | Machine Learning | Natural Language | Natural Language Processing | ONNX | Prompt Learning | Prompt engineering | PyTorch | Python | QLoRA | RAG | SQL | Testing | VLLM
Education
N/A
Regions
Countries
States
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