Role overview
As an LLM Engineer, you will be at the forefront of designing, developing, and refining large language models to meet strategic performance, efficiency, and alignment objectives. Your expertise will enable seamless integration of these models into scalable applications, providing exceptional user experiences and enabling data-driven decision-making.
Responsibilities
- Model Development & Optimization:
- Design, train, fine-tune, and evaluate large language models to enhance performance, efficiency, and alignment with project goals.
- Experiment with novel architectures, prompt-engineering techniques, and retrieval systems to improve model capabilities.
- Systems Integration & Deployment:
- Build scalable inference pipelines to support high-volume, real-time applications.
- Optimize model serving infrastructure through techniques such as quantization, caching, and model distillation.
- Integrate models seamlessly into production environments, including APIs and user-facing applications.
- Research & Cross-Functional Collaboration:
- Lead research initiatives exploring new models, algorithms, and methodologies.
- Collaborate closely with product managers, data scientists, and ML operations teams to translate research innovations into deployable features.
- Proven experience in developing and deploying large language models or similar deep learning models.
- Experience in Language Model Building Blocks (LEGO) is essential
- Strong skills in machine learning frameworks (e.g., TensorFlow, PyTorch).
- Expertise in optimizing inference pipelines and deploying models at scale.
- Familiarity with model compression techniques such as quantization and distillation.
- Ability to work cross-functionally and communicate complex technical concepts effectively.
- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field; Ph.D. preferred.
Benefits
- Opportunity to shape the future of AI with a talented, innovative team.
- Hybrid work environment supporting work-life balance.
- Continuous learning and professional development opportunities.
- Competitive compensation package and comprehensive benefits.
Tags & focus areas
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