Senior LLM Engineer

• Design and implement strategies for creating, sourcing, and augmenting datasets tailored for LLM training and fine-tuning.

• Develop scalable pipelines to collect, clean, filter, annotate, and validate large volumes of text data, ensuring quality, ethical compliance, etc.

• Collaborate with ML engineers, researchers, and software engineers to achieve ambitious goals in the preparation of LLMs and complementary work (preparing datasets, model evaluation, model serving, etc.).

• Develop and integrate new routines for modifying and enhancing LLMs, and extending their functionality.

• Make effective use of distributed compute resources and clusters (GPU’s), identify opportunities for further optimization.

• End-to-end preparation of compressed and specialized LLMs for use in production.

• Keep up to date with research trends in LLM foundation models, dataset curation, LLM pretraining data, and benchmarking.

• Contribute to building documentation, development standards, and a healthy shared code base.

• Mentor other engineers and provide knowledge sharing of cutting-edge techniques.

• Master’s, or Ph.D. in Computer Science, AI, Data Science, Physics, Math, or a related field. Or equivalent industry experience.

• 3+ years of experience in data science, machine learning, or related roles, with demonstrated experience with NLP or LLMs.

• In-depth knowledge of large foundational model architectures (language and multimodal models) and their lifecycle: training, fine-tuning, alignment, and evaluation.

• Proficient in Python and data tooling ecosystems (Pandas, NumPy, Hugging Face Datasets & Transformers libraries).

• Hands-on experience with text data collection from diverse sources: web scraping, APIs, proprietary corpora, etc.

• Strong understanding of data quality metrics including bias detection, toxicity, and readability.

• Experience working in large shared distributed computing environments, familiarity with relevant tools for hardware optimization (vLLM, TensorRT, NeMo, etc.).

• Experience with version control (git), unit testing, and other fundamental aspects of software development.

• Effective communication and interpersonal abilities.

• Experience building or contributing to datasets used in LLM pretraining or supervised fine-tuning.

• Experience building foundational LLMs from the ground up

• Familiarity with alignment techniques (e.g., reinforcement learning, preference modeling, reward modeling).

• Exposure to multilingual and low-resource language datasets.

• Contributions to open-source datasets, tools, or publications in dataset-centric research.

• Knowledge of ethical AI, data governance, privacy laws (e.g., GDPR), and responsible data use.

• Familiarity with the software development lifecycle and agile methodologies

• Indefinite contract.

• Equal pay guaranteed.

• Variable performance bonus.

• Signing bonus.

• We offer work visa sponsorship (If applicable).

• Relocation package (if applicable).

• Private health insurance.

• Eligibility for educational budget according to internal policy.

• Hybrid opportunity.

• Flexible working hours.

• Language classes and discounted lunch options

• Working in a high paced environment, working on cutting edge technologies.

• Career plan. Opportunity to learn and teach.

• Progressive Company. Happy people culture

Multiverse Computing