We are seeking a passionate and highly skilled AI Engineer with a strong background in Generative AI and Large Language Models (LLMs). The ideal candidate will have 3-6 years of hands-on experience in developing, fine-tuning, and deploying state-of-the-art models like GPT, BERT, T5, and similar architectures. You will be responsible for building advanced AI solutions that power our next-generation products and services.
Key Responsibilities:
- Model Development & Research: Develop and optimize generative models, especially LLMs (e.g., GPT, BERT, T5) for various NLP tasks such as text generation, summarization, sentiment analysis, and question answering.
- Data Handling & Preprocessing: Work with large-scale datasets to train and fine-tune models, ensuring high-quality data preprocessing and augmentation to improve model accuracy and performance.
- Algorithm Optimization: Collaborate with cross-functional teams to design and implement algorithms that scale and are optimized for production environments.
- Deployment & Scaling: Lead efforts in deploying machine learning models to production and optimizing for performance, efficiency, and scalability on cloud infrastructure (AWS, GCP, Azure).
- Cross-team Collaboration: Work closely with product, engineering, and data science teams to align AI solutions with business goals and requirements.
- Research & Innovation: Stay up to date with the latest advancements in AI, machine learning, and NLP. Contribute to research papers or patents where applicable.
- Mentoring & Knowledge Sharing: Mentor junior engineers and data scientists, sharing your expertise in machine learning, AI tools, and techniques.
- Qualifications:
- Education: Bachelor's or Master's degree from a premier institution in Computer Science,
- Engineering, Mathematics, or a related field.
- Experience:
- 3-6 years of professional experience working in Generative AI, Natural Language Processing (NLP), and deep learning.
- Hands-on experience with training, fine-tuning, and deploying Large Language Models (LLMs) such as GPT, BERT, T5, etc.
- Strong understanding of transformer architectures, attention mechanisms, and neural networks.
- Experience with state-of-the-art NLP techniques (text generation, embeddings, sentiment analysis, etc.).
• Technical Skills:
- Proficiency in Python and popular machine learning libraries (TensorFlow, PyTorch, Hugging Face, etc.).
- Deep understanding of data structures, algorithms, and machine learning methodologies.
- Familiarity with cloud platforms (AWS, GCP, Azure) for model deployment and scaling.
- Experience in optimizing models for production environments (efficiency, latency, etc.).
