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ML Engineer / Инженер машинного обучения (Python)

- Обучение моделей компьютерного зрения для детекции нарушений на изображениях: (мусор / загрязнение, повреждения инфраструктуры, несоответствие стандартам)

рц дит · На сервисе с: 02.10.26 13:48

до 200k ₽РоссияДонецкУдалёнка

Обязанности:
- Сбор и разметка датасетов
- Обучение моделей компьютерного зрения для детекции нарушений на изображениях: (мусор / загрязнение, повреждения инфраструктуры, несоответствие стандартам)
- Использование OCR-моделей (Tesseract, PaddleOCR) с постобработкой, нормализацией и валидацией данных
- Разработка AI-чатов с использованием RAG (retrieval-augmented generation), проектирование prompt engineering и chain logic
- Анализ геотреков: выявление отклонений, сопоставление фото, координат и времени, детекция аномалий
- Работа с локально развернутыми ML/AI моделями
- Участие в проектировании архитектуры решений и выборе алгоритмов
- Консультация по профильным вопросам

Требования:
- Опыт работы с Python и фреймворками PyTorch / TensorFlow / Keras;
- Практический опыт использования OCR-систем (Tesseract, PaddleOCR, EasyOCR);
- Опыт обработки изображений (OpenCV, PIL, torchvision);
- Знание архитектур сверточных сетей (ResNet, EfficientNet, ConvNeXt, YOLO, DETR и др.);

Похожие вакансии Data Science & ML

Другие площадки
getmatch agency

ML Lead / Head of DS (Credit Risk)

getmatch agencyНа сервисе с: 04.10.26 12:05↑ Вакансия с автоподнятием
Зарплата не указанаРоссияМоскваГибрид

Мы в поисках ML Lead / Head of DS (Credit Risk) для одного из крупнейших банков страны.

Задачи

  • Управление командой Data Science (4–5 человек).
  • Приоритизация и ведение бэклога.
  • Взаимодействие с бизнес-заказчиками и презентация результатов.
  • Помощь команде в выборе и реализации технических решений.
  • Разработка и улучшение ML-моделей для кредитного риска.
  • Тестирование новых источников данных и оценка их влияния на качество моделей.
  • Контроль внедрения моделей и достижения бизнес-эффекта.

Требования

  • Опыт разработки ML-моделей в банковской сфере.
  • Желателен опыт кредитования юридических лиц (SME/Corporate), кредитование ФЛ также рассматривается.
  • Опыт управления командой DS от 3–5 человек.
  • Понимание и практический опыт построения моделей PD, LGD, EAD, скоринга, antifraud и других риск-моделей.
  • Опыт работы с классическим ML на табличных данных.
  • Уверенное владение Python и SQL.
  • Опыт работы со стеком: Python, Pandas, NumPy, Scikit-learn, CatBoost, LightGBM, XGBoost, Spark, Hadoop, Hive, Impala.

Условия и бенефиты

  • Стабильная работа в одном из крупнейших банков страны.
  • Конкурентная заработная плата, соцпакет.
  • Формат работы: гибрид (достаточно 1 раз в неделю / 1 раз в 2 недели). Офис — Технопарк.
  • Сильное DS community, большое разнообразие рабочих и внерабочих активностей.
  • Дружный коллектив единомышленников (все специалисты, занимающиеся машинным обучением, объединены одним департаментом для максимально плотного и продуктивного обмена знаниями).
  • Условия для роста и развития (в т.ч. конференции, тренинги, внутренние программы развития).
Сайты компаний
T

Data Scientist

Tripledot StudiosНа сервисе с: 03.10.26 19:25↑ Вакансия с автоподнятием
Зарплата не указанаJakartaГибрид

Who are we?

Tripledot Studios is one of the largest independent mobile games companies in the world.

We are a multi-award-winning organisation, with a global 2,500+ strong team across 12 studios.

Our expanded portfolio includes some of the biggest titles in mobile gaming, collectively reaching top chart positions around the world and engaging over 25 million daily active users.

Tripledot’s guiding principle is that when people love what they do, what they do will be loved by others.

We’re building a company we’re proud of. One filled with driven, incredibly smart and detail-orientated people, who LOVE making games.

Our ambition is to be the most successful games company in the world, and we’re just getting started.

The role is working within our studio: Tripledot Games

About Tripledot Games

Tripledot Games is a leading developer and publisher of casual and puzzle games, with a strong presence in London, Warsaw, and Barcelona. The studio is responsible for multiple top 10 titles, including Woodoku, Woodoku Blast, Solitaire, and TripleTile. Our best-in-class data-driven approach spans the entire lifecycle from publishing to machine learning puzzle levels, helping us make fast, smart decisions at every stage of development.

We are also one of the largest IAA operators worldwide. Tripledot Games is a diverse and collaborative studio, home to people from over 36 nationalities. We take pride in our craftsmanship, strong focus on outcomes, and continuous improvement, building high-quality, scalable games that players around the world love.

Role Overview

As a Data Scientist in our Experimentation team, you will help deliver and improve Tripledot’s company-wide experimentation analysis platform. Working closely with Data Engineering, you will define the statistical logic and methodologies behind platform features, build prototypes in Python, and ensure the platform produces accurate, reliable results for product teams across our games portfolio.

Your initial focus will include hands-on quality assurance: running independent analyses, comparing results with platform outputs, investigating discrepancies, and validating features and metrics. This offers the opportunity to develop deep expertise in experimentation and A/B testing across a sophisticated internal platform. As the platform evolves, the role will expand into more advanced statistical and machine learning work that delivers value across the business.

Key Responsibilities

  • Define statistical logic, calculation methods, and detailed requirements for experimentation platform features.
  • Prototype statistical methodologies and analyses in Python before implementation.
  • Partner closely with Data Engineers as they develop and improve the experimentation platform.
  • Perform thorough data and feature QA by independently calculating results and comparing them with platform outputs.
  • Investigate discrepancies, identify root causes, and help ensure metrics and analyses are accurate and reliable.
  • Explore opportunities to automate QA processes and improve the efficiency and quality of validation.
  • Build a deep understanding of experimentation methodologies, including A/B testing, monitoring, segmentation, and analysis.
  • Collaborate with BI, Machine Learning, product teams, and other stakeholders to understand requests and shape effective solutions.
  • Contribute to future statistical, algorithmic, and machine learning initiatives as the team’s priorities evolve.

Skills, Knowledge and Expertise

  • 3-5 years of professional experience as a Data Scientist or in a closely related role
  • Strong Python skills, including the ability to prototype analyses and write clear, reliable scripts.
  • Solid knowledge of statistics and standard statistical methodologies.
  • Practical understanding of experimentation and A/B testing, including how metrics and results should be calculated and validated.
  • Familiarity with machine learning methods and the ability to apply relevant approaches when needed.
  • Excellent attention to detail and a disciplined approach to repetitive or methodical QA work.
  • Strong problem-solving skills, with the initiative to propose creative solutions and process improvements.
  • Clear communication skills and the ability to explain analytical methods, results, and rationale.
  • Experience with experimentation platforms or high-volume digital products, such as gaming, e-commerce, or ride-hailing, would be valuable.
  • Ability to critically evaluate and validate AI-generated code, analyses, or modelling suggestions to ensure correctness and reproducibility.
  • Experience using AI-assisted tools (e.g. code assistants or analytical copilots) to accelerate data exploration, research prototyping, and development workflows while maintaining scientific and statistical rigor.
  • Interest in exploring AI-driven approaches that improve experimentation platforms, developer productivity, or data science research workflows.

Working at Tripledot

  • Hybrid Working
  • 20 days of remote working: Work from anywhere in the world, or use the time to cover mandatory office days to WFH, 20 days of the year.
  • Regular company events and rewards: Join in regular events and rewards that celebrate cultural events, our achievements, and our team spirit.
  • Breakfast & Lunch: Relish daily breakfast and lunch provided in the office to keep you fueled and focused.
  • BPJS HEALTH: Elevate your well-being and peace of mind, ensuring robust health security with seamless enrolment in BPJS Health.
  • BPJS SOCIAL: Secure your employment rights with BPJS Social.
  • Festivity Allowance: Celebrate festive occasions with an additional festive allowance.
  • Private Health Insurance: Stay covered with comprehensive health insurance for you and your loved ones.
  • Employee Assistance Program: Anytime you need it, tap into confidential, caring support with our Employee Assistance Program, always here to lend an ear and a helping hand.
  • Family Forming Support: Receive vital support on your family forming/ fertility journey with our support program [subject to policy]
  • English Classes: Enhance your English skills with our provided English classes
Сайты компаний
T

Senior Machine Learning Engineer

tolokaНа сервисе с: 03.10.26 19:22↑ Вакансия с автоподнятием
Зарплата не указанаЕвропаПольшаКипрВеликобританияГерманияНидерландыИспанияПортугалияСербияЧехияЛюксембургМолдоваЛатвияЧерногорияЛитваШвейцарияЭстонияВенгрияИсландияНорвегияРумынияФинляндияФранцияАвстрияГрецияДанияИталияСловакияУдалёнка

About Toloka

At Toloka AI we create data that powers leading GenAI models and innovations. We work with frontier labs, big tech, renowned AI startups, enterprises and non-profit research organizations worldwide. We use a combination of Experts + Crowd + Tech Platform to teach AI models to reason and evaluate their efficacy and safety. We have experts in more than 50 different domains—from doctors and lawyers to physicists and engineers—and boast one of the most diverse global crowds, representing over 100 countries and speaking 40+ languages. We are a well-funded startup with an enviable portfolio of clients including Anthropic, Amazon, Microsoft, Poolside, Recraft, and Shopify.

Recently, we secured strategic investment led by Bezos Expeditions and Nebius Group with participation from Mikhail Parakhin, CTO of Shopify and board advisor to leading GenAI companies, who now serves as our Chairman of the Board. Our remote-first team is globally distributed around the world: USA, UK, the Netherlands, Serbia, and more.

 

About the Team

We are the ML team inside Toloka — we build the machine-learning products that power the platform itself, so every project running on Toloka is faster, cheaper, and more reliable.

A few examples of what we own:

  • LLM QA — the core technology behind Toloka's automated quality-check mechanism. Every annotation flowing through Self-Service is reviewed by an LLM agent we design, train, and operate.
  • Model distillation and fine-tuning — adapting frontier and open-source models to Toloka's tasks to hit the right quality at the right cost.
  • Evaluation, benchmarking, cost modeling, and model selection across providers.

We own the full chain. The same team designs the ML solution, ships it to production, keeps it running 24/7, analyzes the results coming back from real projects, and feeds that signal into the next iteration. No hand-off between research, engineering, and operations — it's all us.

 

About the Position

As a Senior ML Engineer, you will design, train, and deploy the AI agents that drive our core products. You will focus on end-to-end ML tasks—including fine-tuning and Reinforcement Learning (RL)—to build resilient agentic workflows in Python. You will own the full lifecycle of your models, closing the loop from research and benchmarking to production scaling and monitoring.

 

What you’ll do

  • Train, fine-tune, and distill ML models (including RL approaches) to power autonomous AI agents.
  • Build and operate agentic workflows in Python, handling complex reasoning and hybrid human-expert interactions.
  • Own evaluation and benchmarking, selecting foundational models and establishing cost models.
  • Manage the full ML lifecycle: design solutions, ship to production, and monitor real-time signals.
  • Implement observability metrics tailored for agent logic, model performance, and system reliability.

 

What we're looking for

  • 3+ years of experience in ML: Strong background in model training, fine-tuning, and Reinforcement Learning (RL);
  • 1+ year in Agent Development: Practical experience building, evaluating, and launching autonomous AI agents;
  • Agentic Frameworks: Proven experience working with frameworks such as LangChain, LlamaIndex, or AutoGen;
  • Open-Source LLMs: Practical knowledge of model distillation and adapting open-source models (e.g., Llama, Mistral);
  • Python Mastery: Advanced proficiency in Python with a drive to apply disciplined software engineering standards to ML;
  • End-to-End Ownership: Ability to work across the entire chain, from research to production operations;
  • Language: Fluency in English (B2 or above).

 

What we can offer

  • You will be part of an international, dynamic environment that drives innovation and sets new standards in the AI and technology sector.
  • Competitive compensation package including base salary, bonus, and ESOP.
  • Paid PTO and benefits will vary depending on location.
  • We offer a full remote or hybrid model (if you are based in NL or Serbia).
  • IT setup and home office allowances.

 

Equal Opportunity Employer:

Toloka is committed to providing equal opportunity and fostering an inclusive environment. We welcome applications from all qualified individuals and do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, gender identity, age, marital status, veteran status, disability, or any other characteristic protected by applicable law. Selection decisions are made based on qualifications, merit, and business need.

 

[Important Notice] Scam Alert Regarding Fake Job Postings

It has come to our attention that an individual or group is fraudulently impersonating Toloka to post fake jobs and solicit personal information from applicants. Please be aware:

  • Official Communication: Our recruiting team will only contact you from an official "toloka.ai" email address. We will NEVER use Gmail, Yahoo, Tolokainc, toloka.inc, or other personal or seemingly business email accounts.
  • Our Process: We will never ask for your bank account details, credit card number, or any fees as part of the application or interview process.
  • Official Listings: All legitimate job openings are posted on our official careers page: https://toloka.ai/careers#job-list

What to do: If you see a suspicious job posting or have been contacted by someone you suspect is a scammer, please do not provide any personal information. Instead, report the incident to us directly at security@toloka.ai and report the profile/post to LinkedIn.We are taking this matter very seriously and are working with the appropriate parties to resolve it.

Thank you for your vigilance!

To learn how we collect, use, disclose, and store personal data, check out our Privacy Notice.

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