Данные и ML вакансии

As an Applied Scientist Intern, you will become a specialist in our models, products, business and/or codebase. You will identify potential problems or opportunities for improvement, communicate these to the team and suggest solutions.

-Own and prioritise multiple concurrent production data-science projects or systems, translating broad problem statements into actionable work, managing evolving requirements, and delivering measurable outcomes. -Expert-level proficiency in Python and SQL, with a track record of writing clean, testable, production-quality code.

- ClickHouse - основная экспертиза: проектирование MergeTree, партиционирование, TTL, оптимизация запросов, шардирование/репликация, бэкапы в S3. - ETL/ELT и оркестрация: Airflow, dbt, data quality, тесты, мониторинг свежести данных, data contracts.

- Strong hands-on experience with Databricks, especially Databricks Jobs. - Advanced Python skills, writing notebooks daily from ingestion to the gold layer.

Location: Australia Workplace: remote Overview  Are you passionate about languages, writing, and quality evaluation? We are launching an exciting language evaluation project and are looking for Chinese-speaking experts to join our team.    What you will do:   Identify realistic search-related failures where an AI model provides inadequate responses. Create search queries, test them, document what went wrong, and write instructions and evaluation criteria for correct answers. Common issues: local relevance, source quality, outdated information, language mismatches, incomplete answers, and region-specific inapplicability. Testing multiple queries before finding failures is expected.   Project Details:      - Start Date: ASAP     - Duration: Ongoing Project.     - Commitment: 20 hours per week.     - Job Type: Freelance contract.     - Location: Remote, Australia     - Rate: $40 per hour.   Requirements:       - Research skills — ability to find and verify information from multiple sources; comfort navigating different websites,          databases, and documentation     - Critical thinking — Can spot contradictions between sources, identify outdated information, and recognize when                something doesn't apply to a specific locale/context     - Attention to detail — Can catch nuances in language, local variations (prices, regulations, requirements), and edge            cases     - Problem-solving mindset — Comfortable iterating and testing when things don't work; doesn't get frustrated by trial-        and-error     - Domain knowledge — Ideally someone with background in research, quality assurance, compliance, or similar work           that requires precision and source verification     - Writing clarity — Can articulate instructions and rubrics clearly so others understand the logic behind their reasoning        Locale knowledge — Deep familiarity with their specific locale (local regulations, business practices, cultural                       nuances) is valuable for spotting region-specific failures

RELOCATION TO CYPRUS Требования: • От 2 лет опыта в роли Head of Data / Data Group Lead • Уверенное владение SQL • Глубокое понимание статистики и A/B-тестирования • Опыт работы с BI-инструментами, желательно Tableau Важно: ⚠️ Готовность к релокации на Кипр и работе из офиса в Лимассоле.

Задачи: аттестационный стенд идентификации — выборка ≥1000 треков / ≥5. жанров, робастность к форматам, битрейтам, питч-сдвигам;

Location: Hybrid - San Francisco, New York City About Vercel: Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience. Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide. About the role We are looking for a Machine Learning Engineer on our Trust & Safety Engineering team to build and operate the production systems that detect and stop abuse on the platform at internet scale. This is an engineering-first role, roughly 80% writing and shipping production code (services, pipelines, and infrastructure) and 20% modeling, taking detection and classification approaches from prototype to hardened systems. This is a hybrid role based in San Francisco or New York City, with three days a week in the office. What you’ll do Design, build, and operate production systems that detect and disrupt abusive behavior across the platform, with an emphasis on reliability, scalability, and observability Build and maintain machine learning (ML) infrastructure, including training pipelines, feature pipelines, serving infrastructure, and evaluation frameworks Ship large language model (LLM) and classical ML approaches for abuse detection and classification, turning prototypes into maintainable code Own systems end to end, from integrating a model into the platform through deployment, monitoring, and iteration Work with security, product, and infrastructure teams to turn abuse patterns and detection logic into production systems What you need 5+ years of software engineering experience building and operating production systems at scale Wrote production code in Python, plus JavaScript/TypeScript or Go Built and maintained ML infrastructure, such as training and serving pipelines, feature stores, or evaluation tooling Integrated LLMs into production systems, including prompt engineering and evaluation Bonus if you Built an open source ML tool Worked in the trust and safety, fraud, or abuse prevention domain Compensation & Benefits: Competitive compensation package, including equity. Inclusive Healthcare Package. Learn and Grow - we provide mentorship and send you to events that help you build your network and skills. Flexible Time Off. We will provide you the gear you need to do your role, and a WFH budget for you to outfit your space as needed. The San Francisco, CA base pay range for this role is $208,000.00 - $312,000.00. Actual salary will be based on job-related skills, experience, and location. Compensation outside of San Francisco may be adjusted based on employee location. The total compensation package may include benefits, equity-based compensation, and eligibility for a company bonus or variable pay program depending on the role. Your recruiter can share more details during the hiring process. Disclosures: Privacy: Please review our Job Applicant Privacy Policy for more information on how we handle your data. Equal Opportunity: Vercel is committed to fostering and empowering an inclusive community within our organization. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, national origin, citizenship, age, marital status, veteran status, disability status, or any other characteristic protected by law. Vercel encourages everyone to apply for our available positions, even if they don't necessarily check every box on the job description.

Wincent is looking for a Data Platform Engineer to improve data accessibility, ensure data quality, and enhance cloud-based data processing.

• Strong Senior в ML/AI.

Location: Remote; Slovakia (Remote); Spain (Remote); Czechia (Remote); Switzerland (Remote); Portugal (Remote); USA (Remote); Austria (Remote); Iceland (Remote); Hungary (Remote); Ireland (Remote); UK (Remote); Romania (Remote); Poland (Remote) Workplace: Remote WHO WE ARE Hi, we're DuckDuckGo, the online protection company and remote-first team of 400+ on a mission to raise the standard of trust online. Founded in 2008 and profitable since 2014, our annual revenue is in the hundreds of millions USD and millions use our browser on Mac https://spreadprivacy.com/introducing-duckduckgo-for-mac/, Windows https://spreadprivacy.com/windows-browser-open-beta/, iOS https://spreadprivacy.com/duckduckgo-privacy-browser-ios14/, and Android https://spreadprivacy.com/introducing-app-tracking-protection/, our search engine https://duckduckgo.com/, and the DuckDuckGo subscription https://duckduckgo.com/pro. We also offer private, useful, and optional AI, including Duck.ai https://duck.ai/, which lets you chat privately with ChatGPT, Claude, and other AIs, all in one place.   Our culture https://duckduckgo.com/how-we-work of trust, inclusivity, and empowered project management underpins everything we do, where each team member takes full ownership of their projects, from scoping and execution to postmortem. If you're seeking end-to-end ownership of your work, you've come to the right place! YOUR TEAM AND ROLE Working on the Data Science Functional Team, you'll drive product and business impact through statistical modeling, experiment design, Bayesian marketing analysis, and classifier implementation across our search engine, instant answers, AI, and revenue optimization, and work on related projects. Recent projects include: - Defining core growth metrics for our products and building the infrastructure to monitor trends and anomalies - Measuring the impact of major marketing campaigns for Duck.ai http://duck.ai, translating full-funnel data into actionable decisions - Building monitoring pipelines to detect unexpected shifts in search traffic patterns faster and more reliably - Expanding evaluation datasets for page context understanding across complex scenarios like multi-tab browsing and content reattachment - Improving the trigger systems that determine when AI-assisted answers surface in DuckDuckGo Search, balancing quality and our privacy-first approach   Our data meets rigorous privacy standards and is necessarily sparse, so you'll need to think creatively to surface actionable insights in an evidence-first culture where quantitative rigor is the baseline, not the exception.   ABOUT YOU - You have 7+ years of experience in Data Science and a track record of leading high-complexity projects from scoping to production with minimal direction. - You can do 2 or more of the following: - Deploy and iterate on ML in production environments - Develop and deploy NLP solutions - Apply knowledge of LLMs including fine-tuning, LLM-as-judge, and AI-assisted development - Conduct marketing campaign analysis using Bayesian methods - You write production-grade code in Python or a comparable high-level language. - You have advanced SQL and query optimization skills, familiarity with columnar databases like BigQuery, Clickhouse, Redshift, or Druid; experience with a BI tool like Tableau or PowerBI is a plus. - You can design, implement, and analyze experiments across product surfaces, and are comfortable deriving insights from sparse or privacy-constrained data. - You collaborate effectively with product teams and contribute to overall team throughput. COMPENSATION This role is paid on a regional pay scale, in local currency, and stock options: - United States: $190,500 USD annually - United Kingdom: £134,600 GBP annually - Canada: C$253,500 CAD annually - Europe/Rest of World: €157,350 EUR annually In Spain, pay is expected to transition to the EUR scale on January 1, 2027, and in other Europe/Rest of World countries on February 1, 2027.   Compensation is transparent across the organization, and all team members within the same professional level and global region receive the same compensation.   Eligibility for company-sponsored health benefits is limited to team members based in the United States. This program does not extend to team members located in other countries, such as Canada or the UK.   Our Team Member Support Guide https://duckduckgo.com/assets/hiring/team_support_guide.pdf explains how we prioritize your wellbeing including paid parental leave, office setup, and co-working allowances. HIRING PROCESS Hiring works best when it's a two-way street. Learn how we help you get to know DuckDuckGo, envision your future role here, and find out more about how we hire https://duckduckgo.com/how-we-hire. DIVERSITY, EQUITY, AND INCLUSION DuckDuckGo provides equal work opportunities to all team members and applicants, and it prohibits discrimination and harassment of any type on the basis of race, color, ethnicity, caste, religion, age, sex (including pregnancy), national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by our policies or federal, state, or local laws. We want to ensure that our hiring process is accessible. If you need reasonable accommodation for any part of the application process because of a medical condition or disability, please send an email to careers@duckduckgo.com to let us know the nature of your request. PLEASE NOTE THAT: - You’ll be required to attend meetings on camera via video conferencing - Expect to travel at least two times a year: once for our all-hands meetup and again for a team retreat (each around 4-5 days). While extenuating circumstances may impact attendance, everyone is strongly encouraged to attend. - While we offer a flexible work arrangement with no core hours, expect an average full-time commitment of 40 hours per week. - A successful candidate must pass a background check as a condition of joining the team. - By applying for this role, you confirm that all information submitted is accurate and complete. You further acknowledge that providing false or fraudulent information during the application process is cause for denial of an offer, revocation of any existing offer, or other adverse action, up to and including termination after the start of your commencement of work. DISCLOSURE STATEMENT: USE OF AI IN HIRING PROCESS As part of our commitment to enhancing our recruitment process, we utilize artificial intelligence (AI) technology to assist in reviewing and summarizing job applications and test projects, including those tools integrated into our recruitment vendor platforms. We use AI to flag potentially fraudulent applications, analyze and summarize applicants’ experience, interviews, and project performance, and help streamline our selection process. KEY PRINCIPLES: - Data Privacy: All information provided in your application will be handled in accordance with our Recruiting Privacy Policy https://duckduckgo.com/static-assets/files/pages/careers/DuckDuckGo-Recruiting-Privacy-Policy-effective-February-5-2025.pdf. We ensure that your personal information is protected and used solely for recruitment purposes. - Human Oversight and Accountability: The AI technology is designed to support our hiring team by providing insights and summaries of applications and evaluations of test projects against scoring rubrics. All final evaluations and hiring decisions, however, will be made by our hiring team, who will consider the AI's input alongside other factors. - Transparency: We believe in transparency regarding our hiring practices. If you have any questions about how AI is used in our recruitment process, please feel free to reach out to us. By submitting your application, you acknowledge and consent to the use of AI technology in our review process. If you would like to request an alternative selection process, please contact us as at careers@duckduckgo.com. Thank you for your interest in joining DuckDuckGo! #LI-DNI

– Исследовать и прототипировать новые методы контроля качества данных на наших данных. – Проектировать ML- и статистические контроли для выявления аномалий, дрейфа распределений, деградации свежести данных, нарушений сезонных паттернов и нетипичных комбинаций метрик.

• Разработка моделей для recommendation, ranking, forecasting, pricing и optimization. • Тестирование гипотез и проведение экспериментов.

• ClickHouse — основная экспертиза: проектирование MergeTree, партиционирование, TTL, оптимизация запросов. • ETL/ELT и оркестрация: Airflow, dbt, data quality, тесты, мониторинг свежести данных, data contracts.

• Build and maintain data pipelines and integrations with source systems (ERP K-Soft / 1С, Qlik Sense); • Strong Python (pandas, scikit-learn, and ML/DL frameworks) and SQL;

What you'll do Own the Data team's priorities, intake, and triage;

Мы в поиске Senior / Middle+ ML-инженера на аналитический проект. • Опыт локального развертывания LLM-моделей (Llama-3, Qwen) и работы с форматами GGUF / FP8 / AWQ.

- Разрабатывать и развивать пайплайны данных и платформенный слой, от которого зависят AI-продукты компании; - Анализировать использование LLM: стоимость, экономику токенов и кеширования, финансовую отчетность по расходам на AI;