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KEY RESPONSIBILITES:
- Train and fine-tune models for target use cases (ASR/STT, TTS, OCR, LLM, classification, recommendation).
- Prepare, clean and label datasets for experimentation and training pipelines.
- Build evaluation frameworks and metrics (for example - accuracy, WER, MOS, F1, OCR precision/recall) and run systematic A/B/benchmark tests.
- Analyze failures, hallucinations, bias and weak cases and propose improvements to models and data.
- Optimize model performance for inference (quantization, LoRA/QLoRA fine-tuning, prompt optimization, decoding strategies).
- Collaborate with platform engineers to package trained models for deployment and monitoring in production.
- Document experiments, datasets, evaluation results and share learnings with the team.
- Work with business teams to understand feedback, define acceptance criteria and measure real-world performance.
KEY REQUIREMENTS:
- 3+ years of experience in Machine Learning or related role working with deep learning models.
- Solid hands-on experience with Python, PyTorch, HuggingFace Transformers.
- Practical experience preparing datasets and running training/finetuning workflows.
- Understanding of model evaluation methodologies and experience with metrics/benchmarking.
- Experience with one or more of: speech recognition, TTS, NLP/LLM, OCR/document understanding.
- Ability to analyze errors and propose iterative improvements based on data and evaluation results.
- Experience working in agile product delivery teams.
- Fluent English - spoken and written.
- Analytical thinking, problem solving, structured approach, attention to detail.
- Proactive, curious, willing to experiment and learn continuously.
COMPENSATIONS & BENEFITS:
- 13th Salary Fixed and KPI Bonus
- Premium Health Care
- 24/7 Accidental Insurance
- 100% Social Insurance
- Meal + Phone Allowance
- Yearly Medical Checkup
- 15/18 Annual Leaves
- Professional and Transparent Working Environment
- Apply Latest Financial Technology in the World
