The company is looking to advance its machine learning systems and improve the performance of its large language models.
Requirements
- Proven experience in developing, optimizing, and deploying ML systems in production environments
- Strong background in building and managing end-to-end training pipelines for ML models
- Extensive knowledge and hands-on experience in fine-tuning large language models
- Skilled in ML frameworks such as TensorFlow, PyTorch, or similar tools
- Proficient in Python with a focus on writing efficient, clean, and maintainable code for ML applications
- Experience with model training and pipeline development
- Knowledge of ML best practices and research
Responsibilities
- Architect, build, and optimize ML systems
- Develop and deploy robust ML models that deliver high-impact results for real-world applications
- Design and implement efficient, scalable pipelines to train and retrain ML models
- Fine-tune large language models to align with specific enterprise requirements
- Implement and refine feedback loops to iteratively improve the effectiveness of ML models
- Stay current with ML advancements and apply insights to the ML infrastructure
- Mentor and guide junior team members
Other
- Cross-functional collaboration with product and business teams
- Clear and effective communication of ML methodologies, results, and insights to non-technical stakeholders
- Bachelor’s or Master’s degree in Machine Learning, Computer Science, Data Engineering, or a related field
- Active Secret or Top Secret Clearance
- Ability to distill complex ML concepts for both technical and non-technical audiences
