Machine Learning Model Trainer & Fine-Tuning Specialist

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Job Overview

We are seeking a highly skilled Machine Learning Engineer specialized in model training and fine-tuning to join our cutting-edge AI research and development team. The ideal candidate will play a critical role in developing, optimizing, and enhancing machine learning models across various domains.

Key Responsibilities

- Design and implement advanced machine learning model training pipelines
- Develop and execute comprehensive fine-tuning strategies for pre-trained models
- Conduct in-depth performance analysis and optimization of machine learning models
- Collaborate with cross-functional teams to understand specific model requirements and performance goals
- Implement data preprocessing and augmentation techniques to improve model performance
- Monitor and track model training metrics using advanced logging and visualization tools
- Research and integrate state-of-the-art machine learning techniques and architectures
- Develop robust evaluation frameworks to assess model accuracy, efficiency, and generalizability
- Create documentation for model training processes, methodologies, and findings

Required Qualifications

Technical Skills

- Master's or PhD in Computer Science, Machine Learning, Statistics, or related field
- 1+ years of professional experience in machine learning model training and fine-tuning
- Expert-level programming skills in Python
- Advanced knowledge of deep learning frameworks:
- PyTorch
- TensorFlow
- Keras
- Proficiency in machine learning libraries:
- scikit-learn
- Hugging Face Transformers
- NumPy
- Pandas
- Experience with distributed training frameworks
- Strong understanding of GPU/TPU optimization techniques

Technical Competencies

- Advanced knowledge of neural network architectures
- Experience with transformer models and large language models
- Expertise in transfer learning and model fine-tuning techniques
- Comprehensive understanding of machine learning evaluation metrics
- Proficiency in handling large-scale datasets
- Experience with cloud computing platforms (AWS, GCP, Azure)
- Version control using Git
- Familiarity with MLOps practices and tools

Preferred Qualifications

- Research publications in machine learning conferences (NeurIPS, ICML, ICLR)
- Experience with reinforcement learning
- Expertise in domain-specific model adaptation
- Knowledge of model compression and pruning techniques
- Experience with multi-modal model training

Soft Skills

- Strong analytical and problem-solving abilities
- Excellent communication skills
- Ability to collaborate in a fast-paced, innovative environment
- Creative approach to solving complex machine learning challenges
- Detail-oriented with a systematic approach to experimentation

Equal Opportunity

We are an equal opportunity employer committed to creating an inclusive environment for all employees. We celebrate diversity and are dedicated to creating an equitable workplace.