About the role

Senior NLP/LLM Engineer exploring and analyzing LLM capabilities while collaborating with cross-functional teams at Social Discovery Group. Enhancing AI models' effectiveness and optimizing their performance.

Responsibilities

Conducting experiments with LLMs: Explore and analyze the effectiveness of different architectures and techniques (SFT, RLHF, Adapters, etc.) to enhance the capabilities of AI models.
Developing and implementing evaluation methodologies: Implement and maintain robust frameworks to assess the performance, accuracy, and user satisfaction of AI bots, including offline and online metrics.
Optimizing models for inference: Improve the efficiency and speed of AI models during inference to ensure they meet the performance and scalability requirements for production environments.
Collaborating with cross-functional teams: Work closely with data scientists, software engineers, and product managers to integrate AI solutions into the overall product pipeline.

Deep understanding of ML and DL principles: Strong knowledge of classical machine learning algorithms, model validation approaches, and evaluation metrics, as well as neural network architectures, training principles, loss functions, and deep learning metrics.
Deep understanding of classic NLP: Hands-on knowledge of core NLP approaches and tasks, including text preprocessing, TF-IDF and vectorization methods, text classification, named entity recognition, semantic similarity, and transformer-based models such as BERT.
Deep understanding of LLMs: Practical experience with large language models, including fine-tuning and adaptation via SFT, LoRA, QLoRA, prompt tuning, and prefix tuning; familiarity with alignment approaches such as RLHF and DPO; understanding of data preparation, instruction tuning, evaluation, inference optimization, quantization, and deployment using vLLM, SGLang, and similar high-performance serving frameworks.
Proficiency in Python and mathematics: Strong coding skills in Python and solid knowledge of linear algebra, probability, statistics, and optimization for machine learning and neural network development.
Familiarity with ML frameworks and tools: numpy, pandas, scipy, scikit-learn, pytorch, transformers.
English level: B2+.

REMOTE OPPORTUNITY to work full-time;
Vacation 28 calendar days per year;
7 wellness days per year (time off) that can be used to deal with household issues, to lie down and recover without taking sick leave;
Bonuses up to $5000 for recommending successful applicants for positions in the company;
50% payment for professional training, international conferences, and meetings;
Corporate discount for English lessons;
Health benefits. According to the paychecks, if you are not eligible for corporate medical insurance, the company will compensate you with up to $ 1,000 gross per year per employee. This can be spent on self-purchase of health insurance or on doctor’s fees for yourself and close relatives (spouse, children);
Workplace organization. The company provides all employees with an equipped workplace and all the necessary equipment (table, armchair, wifi, etc.) in our offices or co-working locations. In the other locations, the company provides reimbursement of workplace costs up to $ 1000 gross once every 3 years, according to the paychecks. This money can be spent on the rent of the co-working room, on equipping the working place at home (desk, chair, Internet, etc.) during those 3 years;
Internal gamified gratitude system: receive bonuses from colleagues and exchange them for our merchandise, team building activities, massage certificates, etc.