H
HireSeeker
Л

Middle/Middle+ Data Scientist GEN AI + Agentic AI

ID 3696 — Middle/Middle+ Data Scientist GEN AI + Agentic AI

лемана_про · На сервисе с: 29.09.26 12:16

Зарплата не указанаРоссияМоскваУдалёнка

ID 3696 — Middle/Middle+ Data Scientist GEN AI + Agentic AI

🌍 Локация: РФ/РБ
💼 Удаленно
🕔 Занятость: фулл тайм

🏢 Проект: Лемана ПРО

💡 Требования:
- Опыт коммерческой разработки на Python от 2 лет
- Высшее образование: IT, техническое, математическое (или эквивалентный практический опыт)
- Уверенное знание Python: async/await, typing, ООП, структуры данных
- Опыт разработки REST API на FastAPI
- Продвинутый SQL: оконные функции, работа с PostgreSQL/asyncpg
- Практический опыт работы с LLM: инференс через OpenAI API или совместимые (vLLM, TGI)
- Понимание ограничений LLM: галлюцинации, контекстное окно, стохастичность, latency
- Навыки prompt engineering: системные промпты, управление контекстом, JSON-mode
- Базовый опыт контейнеризации: Docker, сборка образов, запуск контейнеров
- Базовое понимание CI/CD: запуск пайплайнов, чтение логов
- Понимание принципов работы с GPU: память, утилизация, параллелизм
- Умение работать с Git: ветки, pull requests, code review
- Опыт написания юнит-тестов
- Базовое понимание архитектурных паттернов для агентов: ReAct, Plan-and-Execute, Agent-as-a-Judge и знакомство с фреймворками LangChain, LangGraph, LlamaIndex, AutoGen

- ML-алгоритмы и теория (базовое понимание):
- Классический ML: линейные модели, деревья решений, ансамбли (Random Forest, градиентный бустинг)
- Метрики качества: precision, recall, F1, ROC-AUC, accuracy для задач классификации, метрики для регрессии
- Валидация моделей: train/test split, кросс-валидация, bootstrapping
- Предобработка данных: нормализация, стандартизация, кодирование категориальных признаков
- Feature engineering: отбор признаков, работа с пропусками, выбросами
- Библиотеки: scikit-learn, pandas, numpy, matplotlib/seaborn для визуализации

📌Желательные (будет преимуществом):
- Опыт развертывания LLM через vLLM (настройка параметров, оптимизация)
- Знакомство с Kubernetes: deployment, services, probes, resources
- Опыт работы с векторными базами (Qdrant, Pinecone, Weaviate)
- RAG-системы: поиск чанков, reranking, контекстуализация запросов
- Оптимизация инференса: batching, caching, quantization, streaming

📋Задачи:
- Разработка сервисов на Python для инференса LLM (FastAPI + vLLM через OpenAI-compatible API)
- Интеграция ML-компонентов в микросервисную архитектуру (асинхронные HTTP-клиенты, WebSocket)
- Интеграция с внешними API (HR-системы, базы знаний)
- Работа с промптами: системные инструкции, few-shot, управление контекстом диалога
- Настройка параметров генерации и инференса LLM
- Работа с векторными базами данных (Qdrant): поиск, reranking, score-boosting
- Сборка и оптимизация Docker-образов для ML-сервисов
- Участие в код-ревью: проверка кода согласно гайдлайнам, выявление типовых ошибок

📨 Отклик — через форму: •••••••• или напрямую рекрутеру: ••••••••

❗️Откликайтесь только при релевантном опыте.

❗️При первичном отклике:
ID вакансии / ФИО / локация / возраст / занятость (работаете/нет) / формат работы (удаленка, гибрид, офис) / стек / опыт / резюме / сверка с требованиями

❗️Повторный отклик: ID вакансии + сверка.

#Data #Scientist #Удаленно #вакансия

Статьи для Data Science & ML

Похожие вакансии Data Science & ML

Сайты компаний
Y

ML Developer for Speech Recognition Team (Kyrgyzstan)

yangoНа сервисе с: 03.10.26 22:14
Зарплата не указанаНе указана странаЛокация не указана
Yandex Kyrgyzstan is looking for an ML Developer to join our Speech Recognition Team. In this role, you will help improve speech recognition technologies, work with large ASR models, and contribute to launching ML solutions into production. Our team develops and improves speech recognition systems for various Yandex services, including voice assistant technologies. We are expanding our technologies to new languages and continue improving voice understanding solutions for international markets.
Yandex Kyrgyzstan is part of Yango Group, a global technology ecosystem building digital services that simplify and enhance everyday life. Operating in more than 30 countries across Europe, Africa, the Middle East, South Asia, and Latin America, we deliver solutions in ride-hailing, delivery, e-commerce, mapping, entertainment, AI, and beyond. Headquartered in Dubai, Yango Group unites advanced technological capabilities with deep local market knowledge to create products that fit naturally into people’s daily routines across diverse communities.
You will be responsible for
• Expanding speech recognition technologies • Studying and applying scientific publications, building hypotheses, and conducting experiments • Collecting and analyzing data for low-resource languages • Training large ASR models • Launching ML solutions into production • Collaborating with the team on improving speech recognition technologies
You might be a fit if you have
• Strong Python skills and experience working with PyTorch • Experience in deep learning (for example, in CV or NLP) • Basic C++ skills It’d be a plus if you: • Have worked with deep learning in speech technologies • Have experience deploying neural network models into production • Have experience working with large datasets
Explore our benefits
Health & WellbeingWork Environmentbonuses & perks

  • Life in balance with Yango

    We know how to work hard, but we also know how to have fun together, and we are true believers that the wellbeing of our teams is important

  • Psychological support

    Available in different languages to support you when you need it most

  • Life and private health cover

    Life and private health insurance
*different conditions apply based on hiring location and position type
Открыть на сайте компании
Сайты компаний
Y

ML Developer (Kyrgyzstan)

yangoНа сервисе с: 03.10.26 22:08
Зарплата не указанаНе указана странаЛокация не указанаГибрид
Yandex Kyrgyzstan is seeking an ML developer for our LLM team building language models for Alice, with a focus on prompt interpretation, VA personality, and speech recognition/synthesis tech.
We are a small but savvy team developing a bilingual (Arabic/English) language model that enables users to seamlessly switch between languages while interacting with our voice assistant, helping them with their day-to-day needs: putting on music, setting alarms and reminders, checking the weather, controlling smart home devices, or looking something up. We then leverage this experience in our new projects focused on LLM data generation and automated QA. This is a hybrid position where you'll oversee the project's LLM core, from data preparation and model training to evaluation and deployment. The role spans the entire production cycle, giving you the opportunity to influence technical decisions from the outset. Yandex Kyrgyzstan is part of Yango Group, a global technology ecosystem building digital services that simplify and enhance daily life. Operating in more than 30 countries across Europe, Africa, the Middle East, South Asia, and Latin America, we deliver solutions in ride-hailing, delivery, e-commerce, mapping, entertainment, AI, and beyond. Headquartered in Dubai, Yango Group unites advanced technological capabilities with deep local market knowledge to create products that fit naturally into people's daily routines across diverse communities.
You will be responsible for
• Fine-tuning language models (SFT, DPO, Reinforcement Learning) • Configuring system prompts and influencing the language model's behavior • Generating prompts and multi-step conversations, improving our existing corpora, and filtering examples using language models • Comparing automated scoring (LLM-as-a-Judge) with expert annotation • Teaching the model to use the correct functions given the context, ask clarifying questions, and correctly interpret numbers, dates, names, and locations • Developing benchmarks for conversations and commands • Ensuring that the language model functions correctly as a whole (language authenticity, context memory, personality, AI safety) • Integrating models into the product infrastructure, optimizing response times and inference • Contributing to the development process from closed beta to post-launch
You might be a fit if you have
• Good knowledge of Python, with experience in developing ML/NLP systems and working with PyTorch • A solid idea of how transformers and LLMs work under the hood • Hands-on experience with fine-tuning language models using SFT, DPO, or RL (production, research, or a compelling pet project) • An understanding of QA processes: creating test datasets, analyzing data slices, using LLM judges, and running A/B tests • An independent mindset and the willingness to understand a complex system and drive results, keeping in close contact with editors and adjacent teams It’s a plus if you • Have experience with multi-language models, synthetic data, and enhancing models by improving training datasets • Know about tool calling, agent architectures, and RAG • Are familiar with LLM inference (vLLM and alternatives, distributed training) • Speak English at a level sufficient for understanding technical literature and articles
Explore our benefits
Health & WellbeingWork Environmentbonuses & perks

  • Life in balance with Yango

    We know how to work hard, but we also know how to have fun together, and we are true believers that the wellbeing of our teams is important

  • Psychological support

    Available in different languages to support you when you need it most

  • Life and private health cover

    Life and private health insurance
*different conditions apply based on hiring location and position type
Открыть на сайте компании
Сайты компаний
T

Engineering Manager (ML)

tabbyНа сервисе с: 03.10.26 18:48
Зарплата не указанаПольшаУдалёнка

About the role

Tabby creates financial freedom in the way people shop, earn and save by reshaping their relationship with money. Over 25 million users choose Tabby to stay in control of their spending and make the most out of their money.

The company’s flagship offering allows shoppers to split their payments online and in-store with no interest or fees. Over 70,000 global brands and small businesses, including Amazon, Noon, IKEA, and SHEIN use Tabby to accelerate growth and gain loyal customers by offering easy and flexible payments online and in stores.
Tabby generates over $18 billion in annual transaction volume for its partner brands and is the highest-rated, most-reviewed, largest, and fastest-growing FinTech in the GCC region.

Tabby launched in 2019 and has since raised +$1 billion in equity and debt funding from global and regional investors, and is now valued at $6,5 billion.

About the team

Tabby Marketplace is where our users discover what to buy. The Content Quality & Personalisation team owns the data that makes the marketplace work: a catalogue of 25M+ products from thousands of merchants, ingested through feeds and e-commerce plugins (Shopify, Salla, Zid, Amazon and more), then categorised, enriched, translated, moderated and published, largely by ML.


You will lead a cross-functional team of ML engineers, backend and frontend engineers, QA and a product analyst. The team runs the LLM-based enrichment pipeline (categorisation, attribute extraction, translation), the item representation model and embeddings that power search and recommendations, ML-assisted moderation that is replacing manual review, and the labeling and evaluation platform behind all of it.


You will work closely with the Shopping, Offers and Monetisation teams, as well as catalogue operations and partner support.

Responsibilities

  • 6+ years of engineering experience, including 3+ years building production ML systems (NLP, LLM applications, embeddings, or classification at scale)
  • 2+ years as an Engineering Manager or ML Team Lead at a fast-growing e-commerce, marketplace or fintech company
  • Hands-on experience shipping LLM-based products: prompt and pipeline design, fine-tuning, evaluation, cost and latency control, self-hosted and API-based models
  • Experience building and operating large-scale data and ML pipelines (batch and streaming), and making them observable, reproducible and reliable
  • Solid backend fundamentals; you are comfortable reviewing Go and Python services and reasoning about distributed systems
  • Our stack: Python, Go, PostgreSQL, Pub/Sub, BigQuery, GCS, Kubernetes, Google Cloud Platform, Airflow, and a microservices architecture
  • A strong grasp of ML evaluation: golden datasets, labeling workflows, offline metrics, and A/B testing tied to business outcomes
  • Product sense: you connect catalogue quality to conversion, discovery and merchant growth, and you can prioritise accordingly
  • A proactive mindset and the ability to work independently
  • Strong communication skills in English (B2 level or higher)

Nice to have:
  • Experience with product catalogues, PIM systems, or marketplace content moderation
  • Experience with Arabic-language content
  • Familiarity with data residency and regulated-data requirements

Qualifications

  • Own the end-to-end product data pipeline: ingestion from feeds and plugins, ML enrichment, moderation and publication, with clear SLAs for freshness, coverage and quality
  • Lead the ML roadmap for catalogue intelligence: category tree and attribute coverage, translation quality, ML-assisted moderation, item embeddings and recommendations
  • Lead large cross-team projects and drive them to production
  • Contribute to quarterly planning and roadmap definition; define and report OKRs for catalogue quality and personalisation
  • Review feature designs and ensure non-functional requirements are met, including ML evaluation, inference cost, latency and data residency
  • Build and maintain the evaluation and labeling infrastructure that lets the team measure every model change before it reaches production
  • Oversee technical debt management and incident handling across ML and backend services
  • Hire, evaluate, and motivate team members; grow ML engineers into owners of business outcomes
  • Build cross-team and cross-functional collaboration with Shopping, Offers, Monetisation, catalogue operations and partner support to increase efficiency
  • Foster a results- and business-oriented culture
  • Monitor key team performance indicators
  • Ensure process and delivery transparency for stakeholders and partner functions
  • Optimise processes to improve productivity

Benefits

  • Full-time B2B contract
  • Fully remote setup
  • Up to 20% tax allowance
  • 22 paid leave days annually
  • Stock options (ESOP) in a fast-scaling, pre-IPO company
  • Flexi benefits you can use for wellness, travel, or learning
  • Work alongside a high-performing, international engineering team in a global fintech unicorn
Открыть на сайте компании

HireSeeker собирает вакансии со всех площадок и присылает только релевантные. Бесплатно.

Посмотреть полный каталог →Свежие вакансии Data Science & ML