Research Engineer - JetBrains AI

About the Role

The role requires a deep understanding of NLP and transformer-based approaches, as well as experience with modern deep learning frameworks such as PyTorch. You will be working with a talented team of engineers who are passionate about AI and are committed to delivering high-quality products. The company values independence, creativity, and a willingness to learn and adapt, making it an exciting and dynamic work environment.

JetBrains AI is part of a larger organization that has been at the forefront of developing innovative software development tools for over two decades. The company has a strong culture of innovation and collaboration, and is committed to creating a workspace that is inclusive and supportive of all employees.

What You Will Do

• Work with stakeholders to convert business requirements into technical specifications
• Design, deploy, and support Large Language Models in production environments
• Train LLMs from scratch on a large GPU cluster
• Collect and process pre-training and fine-tuning datasets
• Support and improve existing subsystems
• Collaborate with the engineering team to identify and prioritize tasks
• Develop and implement automated testing and validation procedures
• Stay up-to-date with the latest developments in the LLM field and apply this knowledge to improve the models
• Work with the product team to ensure that the models meet the needs of the end-users
• Participate in code reviews and contribute to the improvement of the overall code quality

What We Are Looking For

• Experience in design, deployment, and support of production ML systems
• A strong theoretical background in NLP and transformer-based approaches
• Proficiency with modern deep learning frameworks such as PyTorch
• Experience with distributed training of multi-billion parameter models
• Attention to detail and great communication skills
• Ability to work independently and collaboratively as part of a team
• Strong problem-solving skills and ability to think creatively
• Experience with LLM inference frameworks such as vLLM, DeepSpeed, TensorRT
• Knowledge of MLOps tools and practices, including CI/CD for ML
• Familiarity with K8s and Kubeflow

Nice to Have

• Experience with LLM alignment techniques such as RLHF/RLAIF
• Scientific publications in the NLP field
• Experience with other deep learning frameworks such as TensorFlow
• Knowledge of software development methodologies such as Agile

Benefits and Perks

• Opportunity to work on a cutting-edge AI project with a talented team of engineers
• Competitive salary and benefits package
• Flexible working hours and remote work options
• Access to a large GPU cluster for training and deploying models
• Professional development opportunities, including training and conference attendance
• Collaborative and dynamic work environment
• Recognition and reward for outstanding performance
• Comprehensive health insurance and wellness programs
• Generous paid time off and vacation days

• Make sure you have a strong understanding of transformer-based approaches and experience with modern deep learning frameworks such as PyTorch.
• Highlight your experience with distributed training of multi-billion parameter models and your ability to work with large datasets.
• Showcase your problem-solving skills and ability to think creatively, and provide examples of how you have applied these skills in previous roles.
• Be prepared to discuss your experience with LLM inference frameworks and MLOps tools and practices.
• If you have experience with LLM alignment techniques or scientific publications in the NLP field, be sure to highlight these in your application.
• Research the company culture and values, and be prepared to discuss how you align with these and how you can contribute to the team.
• Practice your communication skills, as the ability to communicate complex technical ideas is essential for this role.