We are seeking an AI Engineer (Level 2 / 3) with a deep passion for exploring AI technologies, particularly Large Language Models (LLMs) and advanced NLP techniques. The ideal candidate will have a strong foundation in deep learning architectures and experience with state-of-the-art AI frameworks. In this role, you will work on developing and deploying intelligent applications that solve real-world problems for our clients, leveraging tools like LangChain, Hugging Face, and OpenAI APIs.
Responsibilities
- Design and Develop AI Solutions: Build advanced AI and NLP solutions focusing on large language models. Experiment with state-of-the-art Transformer architectures (e. g., BERT, GPT, LLaMA) to address complex language understanding and generation tasks.
- LLM Implementation: Leverage modern AI frameworks and tools (such as LangChain, Hugging Face Transformers, OpenAI APIs, PyTorch, TensorFlow) to develop, fine-tune, and integrate LLMs into applications. Ensure models are optimized and efficient for production use.
- Advanced NLP Techniques: Implement and enhance NLP capabilities like text generation, summarization, and retrieval-augmented generation (RAG) to provide intelligent and contextually aware features in our solutions.
- Prompt Engineering and Fine-Tuning: Craft effective prompts and fine-tune LLMs to improve model performance for specific domains and use cases. Experiment with prompt strategies and training techniques to optimize generative models.
- Production Deployment and MLOps: Deploy and scale models in production environments, ensuring reliability and low-latency performance. Implement MLOps best practices (CI/CD pipelines, model monitoring, version control) to achieve robust, repeatable model deployments.
- Cloud AI Integration: Utilize AI/ML cloud services (AWS, GCP, Azure) for model training, deployment, and infrastructure management. Optimize cloud resources to handle large-scale training and inference efficiently.
- Model Optimization and Scaling: Continuously optimize model performance and implement scaling strategies to handle large datasets and high-volume usage.
- Cross-Functional Collaboration: Work closely with data scientists, software engineers, and product managers to integrate AI capabilities into products and solutions. Collaborate in cross-functional teams to gather requirements, brainstorm ideas, and ensure AI systems meet client needs and quality standards.
- Innovation and Research: Stay up-to-date with the latest AI research, papers, and trends in the industry. Proactively experiment with new algorithms, models, and techniques to keep our solutions at the cutting edge.
Requirements
- Education and Experience: Bachelor's or Master's degree in Computer Science, Engineering, or a related field (or equivalent experience), plus 4+ years of hands-on experience in AI/ML engineering or a similar role.
- Deep Learning and LLM Expertise: Strong foundation in deep learning and NLP, with experience in transformer-based architectures and large language models (e. g., BERT, GPT series, LLaMA).
- Programming and Frameworks: Proficiency in Python programming and experience with major AI/ML frameworks and libraries - e. g., PyTorch, TensorFlow, and data libraries like NumPy, Pandas, scikit-learn. Familiarity with NLP/LLM tools such as Hugging Face Transformers, LangChain, and OpenAI APIs is highly desired.
- NLP and Generation: Proven experience developing NLP solutions, including working on text generation, summarization, conversational AI, or retrieval-augmented generation (RAG) systems.
- Model Tuning: Hands-on skills in prompt engineering and fine-tuning LLMs or other deep learning models to adapt them for specific tasks or domains. Experience with transfer learning and hyperparameter tuning for model optimization.
- Deployment and Cloud: Experience deploying machine learning models into production environments. Familiarity with deploying.
This job was posted by Bilal Khan from Fxis.
