Noww - Machine Learning Engineer - Large language Models

Role : Machine Learning Engineer - Large Language Models.

Roles And Responsibilities :

- Design, develop, and deploy large-scale language models for a range of NLP tasks such as text generation, summarization, question answering, and sentiment analysis.

- Fine-tune pre-trained models (e.g., GPT, BERT, T5) on domain-specific data to optimize performance and accuracy.

- Collaborate with data engineering teams to collect, preprocess, and curate large datasets for training and evaluation.

- Experiment with model architectures, hyperparameters, and training techniques to improve model efficiency and performance.

- Develop and maintain pipelines for model training, evaluation, and deployment in a scalable and reproducible manner.

- Implement and optimize inference solutions to ensure models are performant in production environments.

- Monitor and evaluate model performance in production, making improvements as needed.

- Document methodologies, experiments, and findings to share with stakeholders and other team members.

- Stay current with advancements in LLMs, NLP, and machine learning, and apply new techniques to existing projects.

- Collaborate with product managers to understand project requirements and translate them into technical solutions.

- 3+ years of experience in machine learning and natural language processing.

- Proven experience working with LLMs (such as GPT, BERT, T5, etc.) in production environments.

- Demonstrated experience fine-tuning and deploying large-scale language models.

Technical Skills :

- Proficiency in Python and experience with ML libraries and frameworks such as PyTorch ,TensorFlow, Hugging Face Transformers, etc.

- Strong understanding of deep learning architectures (RNNs, CNNs, Transformers) and hands-on experience with Transformer-based architectures.

- Familiarity with cloud platforms (AWS, GCP, Azure) and experience with containerization tools like Docker and orchestration with Kubernetes.

- Experience with data preprocessing, feature engineering, and data pipeline development.

- Knowledge of distributed training techniques and optimization methods for handling large datasets.

Soft Skills :

- Excellent communication and collaboration skills, with an ability to work effectively across interdisciplinary teams.

- Strong analytical and problem-solving skills, with attention to detail and a passion for continuous learning.

- Ability to work independently and manage multiple projects in a fast-paced, dynamic environment.

Preferred Qualifications :

- Experience with prompt engineering and techniques to maximize the effectiveness of LLMs in various applications.

- Knowledge of ethical considerations and bias mitigation techniques in language models.

- Familiarity with reinforcement learning, especially RLHF (Reinforcement Learning from Human Feedback).

- Experience with model compression and deployment techniques for resource-constrained environments.

- Contributions to open-source projects or publications in reputable machine learning journals.

- Professional development opportunities, including access to conferences, workshops, and training programs.

- A collaborative, inclusive work culture that values innovation and teamwork.

Qualifications :

- Bachelors or Masters degree in Computer Science, Machine Learning, Data Science, or a related field.

Primary skills (Must have) :

- Python.

- PyTorch, TensorFlow, Hugging Face Transformers.

- Familiarity in cloud platforms-AWS, GCP, Azure.

- docker, kubernetes.

Interview Details :

- Video screening with HR.

- L1 - Technical Interview.

- L2 - Technical and HR Round.

Note : Candidate must have own laptop.

Must follow Kuwait calendar.

Working Hours : 11 : 30 AM to 7 : 30 PM.

Working days : Sunday to Thursday.