ML Engineer
We are looking for a talented Machine Learning Engineer with expertise in Natural Language Processing (NLP) and Generative Modeling for a technology company with more than 30 years of experience in software development in the field of security and automation. Its products are used worldwide for data analysis and verification.
Key Responsibilities
1. Natural Language Processing (NLP):
2. Model Training and Optimization:
3. Evaluation and Metrics:
4. Generative Modeling:
Qualifications:
1. Natural Language Processing (NLP):
- Text preprocessing, tokenization, and embeddings.
- Strong understanding of transformer architectures (e.g., GPT, BERT, T5).
- Fine-tuning pre-trained models for specific tasks.
- Expertise in prompt engineering and optimization.
- In-depth knowledge of attention mechanisms and positional encoding.
2. Model Training and Optimization:
- Experience with distributed training techniques (e.g., data parallelism, model parallelism).
- Expertise in hyperparameter tuning and optimization.
3. Evaluation and Metrics:
- Familiarity with NLP evaluation metrics (e.g., BLEU, ROUGE, perplexity).
- Ability to design and implement custom evaluation pipelines.
4. Generative Modeling:
- Understanding of diffusion processes, noise schedules, and reverse diffusion.
- Experience with generative adversarial networks (GANs) and variational autoencoders (VAEs) as complementary techniques.
- Expertise in training diffusion models from scratch or fine-tuning pre-trained models.
- Knowledge of loss functions specific to diffusion models (e.g., noise prediction loss).
Qualifications:
- Proven experience in machine learning and deep learning.
- Strong background in NLP techniques and architectures.
- Familiarity with generative modeling methods such as GANs, VAEs, and diffusion models.
- Proficiency in programming languages such as Python and frameworks like TensorFlow or PyTorch.
- Excellent problem-solving skills and ability to work in a collaborative environment.
