Исследователь/ Researcher [LLM, VLM, and Omni-Model Training]
Москва, Россия
3 – 6 лет
Полная занятость
Гибкий, Офис, Удаленная занятость
Research Scientist
Вакансия открыта в Дочерней компании экосистемы МТС - ООО «МВС ИИ». MWS AI – это часть экосистемы МТС Web Services, где создаются AI-решения будущего. Голосовые ассистенты и чат-боты могут ответить на любой вопрос клиента, а компьютерное зрение - распознавать лица и эмоции. Мы объединили сильных разработчиков, самый мощный суперкомпьютер, и прорывные идеи, чтобы делать жизнь людей комфортнее и безопаснее и помогать бизнесу.
We are seeking a Researcher to drive the development and training of Large Language Models (LLMs), Vision-Language Models (VLMs), and omni-modal models. The successful candidate will work at the intersection of research and practical systems, contributing to model design, experimentation, and scalable training pipelines under the guidance of more senior researchers and engineers. This role is ideal for candidates who already have some hands-on experience with deep learning and are motivated to grow into large-scale LLM/VLM research and engineering.
- Contribute to the design, training, and evaluation of LLMs, VLMs, and omni-modal models
- Run experiments, analyze results, and help iterate on model architectures and training recipes
- Assist in developing and optimizing training and inference pipelines for latency, throughput, and cost efficiency
- Help implement and maintain distributed training workflows on multi-GPU and (over time) multi-node clusters
- Collaborate with engineers and product teams to transfer research outcomes into real-world applications and products
- Contribute to writing internal reports, technical documentation, and, when appropriate, research papers
- Stay current with the latest advances in machine learning, deep learning, and large-scale model training
- Bachelor’s degree (completed or in final year) or Master’s degree in Computer Science, Electrical Engineering, Mathematics, or a related field, or equivalent practical experience
- Good oral and written English at a minimum level of B1-В2
- Solid background in mathematics, including linear algebra, probability, statistics, and optimization
- Strong programming skills in Python, with experience in deep learning frameworks such as PyTorch (preferably), TensorFlow, or JAX
- Practical experience training deep neural networks (e.g., for NLP, computer vision, recommendation, or related tasks), including data preprocessing, model implementation, and debugging
- Familiarity with core machine learning concepts (overfitting, regularization, evaluation metrics, cross-validation, etc.)
- Ability to read and implement methods from recent ML research papers
- Ability to work both independently and collaboratively in a fast-paced research and engineering environment
- Good communication skills, including the ability to clearly present experimental results and technical ideas
- Hands-on experience with training or fine-tuning LLMs, VLMs, or other large foundation models (e.g., using HuggingFace, LLaMA Factory, or similar frameworks)
- Familiarity with distributed and parallel training concepts (e.g., data/model parallelism, mixed-precision training, gradient accumulation, checkpoints)
- Experience using job schedulers or orchestration tools (e.g., SLURM, Kubernetes, Ray) in any setting (uni-versity, research lab, or industry)
- Exposure to model efficiency techniques such as quantization, pruning, distillation, low-rank methods, or sparsity
- Experience contributing to open-source ML projects or maintaining reproducible ML codebases
- Experience building and deploying smaller-scale ML models into real products, services, or internal tools
- 5/2, partial or full remote working scheduling, flexible start of the day
- Fixed monthly salary + quarterly bonuses
- Comfortable office 5 minutes walk from the metro station
- Medical insurance with dentistry, travel insurance, life insurance, discounts on car insurance, etc
- Participation in conferences and meetups, trainings at the expense of the company
- Free mobile communications
- Annual paid leave - 31 days
- Special offers and discounts from MTS partners
