Introduction:
Are you ready to redefine the possibilities of AI and machine learning? Join us at Fastino as we pioneer the next generation of language models. Our team, boasting alumni from Google Research, Stanford, Cambridge, and Berkeley, is on a mission to develop specialized, efficient AI systems. If you're passionate about groundbreaking technology and solving AI's hardest problems, we want you on our team!
Fastino is backed by leading investors including Microsoft, Insight Partners, NEA, CRV, Valor, Github CEO Thomas Dohmke, and others.
Responsibilities:
- Conduct and lead research on the development, training, and deployment of large language models, with a willingness to work on both pre-training and post-training (fine-tuning, alignment, optimization) processes.
- Drive innovation in sequential architectural design and improvements to existing LLM structures to enhance performance, efficiency, and interpretability.
- Collaborate closely with MLOps engineers to build, optimize, and maintain scalable training pipelines for LLMs, ensuring efficient deployment in production environments.
- Design, implement, and evaluate novel model architectures, leveraging techniques from transformer models and beyond to improve language understanding, generation, and inference capabilities.
- Publish research findings in reputable journals and conferences, contributing to the body of knowledge in large language models, sequential architectures, and machine learning operations.
- Develop and maintain documentation and codebases, ensuring reproducibility and best practices in research and development workflows.
- Stay current with advancements in machine learning, NLP, and AI, and assess their relevance to ongoing and future projects.
Qualifications:
- PhD / MS in Computer Science, Machine Learning, Computational Linguistics, or a related field, with a strong focus on natural language processing or machine learning.
- Proven experience in pre-training or post-training large language models, with a track record of success in fine-tuning, alignment, and adaptation techniques.
- Strong background in research and development of novel sequential architectures, with experience in transformers and alternative approaches to sequence modeling.
- Proficiency in MLOps best practices, including model versioning, CI/CD pipelines, containerization, and cloud deployment for large-scale models.
- Demonstrated experience publishing papers in high-impact machine learning and NLP conferences (e.g., NeurIPS, ACL, ICML) or journals.
- Solid programming skills in Python and familiarity with machine learning frameworks like TensorFlow, PyTorch, Hugging Face Transformers, and MLOps tools (e.g., MLflow, Kubeflow).
- Strong analytical and problem-solving skills, with an aptitude for translating complex theoretical research into practical applications.
Why Join Us?
- Supportive Environment: Benefit from the resources of Microsoft and venture funding, collaborating with top-tier talent from renowned universities.
- Top-Tier Compute: Enjoy a dedicated GPU cluster for research.
- Impactful Work: Your contributions will directly shape the future of AI applications, making technology more accessible, eco-friendly and dev friendly!
- Competitive Benefits: Receive competitive salary, stock options, health benefits, and more.