10 дней назад
Staff Machine Learning Engineer
202 500 - 274 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Staff Machine Learning Engineer (Machine Learning/Python): Building and deploying scalable data science models and training pipelines for Intuit's financial technology products with an accent on data preparation, feature engineering, algorithm development, and statistical evaluation. Focus on designing production-ready machine learning systems, running A/B tests, accelerating workloads with GPUs, and supporting millions of users.
Location: Mountain View, California, United States
Base pay: $202,500–$274,000 per year, plus eligible cash bonus, equity rewards, and benefits.
Company
is a financial technology platform serving tens of millions of customers through products including TurboTax, Credit Karma, QuickBooks, and Mailchimp.
What you will do
- Discover, access, import, clean, and prepare data sources for machine learning use.
- Develop features and build pipelines for training and deploying machine learning models.
- Implement, refine, and design machine learning and other algorithms with data scientists.
- Run A/B tests, perform statistical analysis, and evaluate model impact.
- Collaborate with product managers, data scientists, and product engineers while communicating results to technical and non-technical stakeholders.
- Evaluate emerging technologies and their potential customer benefits.
Requirements
- Bachelor’s, master’s, or doctoral degree in computer science or a related field, or equivalent experience.
- 6+ years of professional experience.
- Experience with data science and machine learning tools, including Python, Scikit, NLTK, NumPy, Pandas, TensorFlow, Keras, R, or Spark.
- Knowledge of classification, regression, clustering, model training and validation, SQL, and data processing.
- Strong computer science and software engineering fundamentals, including algorithms, performance complexity, Git workflows, and production-ready coding.
- Experience deploying highly scalable software for millions or more users, using GPU acceleration and cloud platforms such as AWS or GCP.
Culture & Benefits
- Cross-functional collaboration with product, engineering, and data science teams.
- Competitive compensation with performance-based rewards.
- Eligibility for cash bonus, equity rewards, and employee benefits.
- Regular pay equity comparisons across ethnicity and gender categories.
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