aipythondata analysispandasllmmachine learningmatplotlibscikit learnjupyteragentic systems
Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Зарплата и рынок
Выше рынка
$209к-250к/год
$130к$150кмедиана$170к
По похожим ролям (49) ~ $150к/год
На СНГ рынке: $1.2к/мес ($893 - $1.4к)
100
Крутая вакансия
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Чёткая роль ML-инженера в AI-подразделении S&P Global сочетает разработку моделей для продакшена, исследования и финансовые данные; также заявлены сильные льготы и поддержка обучения.
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Выше рынкаСовременный ML-стекСильный соцпакетПоддержка развитияРабота рядом с офисом
Оценка от Hirify AI
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Machine Learning Engineer (AI): Building predictive data-driven products and production machine learning models for financial data and documents with an accent on statistical research, data analysis, and agentic systems. Focus on designing and evaluating models, implementing reliable production code, and developing LLM code-generation and tool-utilization capabilities.
Location: New York, New York, United States; telecommuting permitted only within normal commuting distance of the New York office.
Base salary: $209,000–$250,300 annually, plus eligibility for an annual incentive plan.
Company
Kensho is S&P Global’s AI innovation hub, developing machine learning, natural language processing, data discovery, and generative AI solutions for business and financial applications.
What you will do
Identify, research, prototype, and build predictive data-driven products using statistical analysis and machine learning.
Analyze large proprietary and open-source datasets to discover patterns, correlations, outliers, and anomalies.
Formulate and test hypotheses about data distributions and regularities.
Design, implement, and evaluate models for financial data and documents.
Write production code and tests for robust, reliable predictive models and algorithms.
Review research, prototypes, models, and code with peers while maintaining expertise in statistical and machine learning methods.
Requirements
Master’s degree in Computer Science, Statistics, Data Science, or a related quantitative field.
At least one year of experience in data science or a related quantitative occupation.
At least one year of experience must include machine learning and artificial intelligence tools.
Experience with data preprocessing, exploration, and visualization tools, including Jupyter, Matplotlib, Pandas, and Scikit-learn.
Experience with data management and storage tools, deployment, and machine learning operations.
Experience conducting and publishing machine learning research and producing code.
Experience with agentic systems, including large language model code generation and tool utilization.
Culture & Benefits
Autonomy and support for building scalable, robust technology through open, efficient collaboration.
Medical, dental, and vision insurance with 100% company-paid premiums.
Unlimited paid time off, 26 weeks of fully paid parental leave, compassion leave, and elder care leave.
401(k) plan with 6% employer matching and charitable donation matching.
Up to $20,000 in tuition assistance for degree programs and up to $4,000 annually for professional education.
Mentoring, learning opportunities, conference participation, catered lunches, snacks, and a dog-friendly office.
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