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Staff Machine Learning Engineer
Woodland Hills, California
In this role, you’ll be embedded inside a vibrant team of data scientists in order tobring big data expertise and engineering rigor to our ML solutions. You’ll beexpected to help conceive, code, and deploy data science models at scale using thelatest industry tools. Important skills include distributed systems, system designand architecture, data wrangling, feature engineering, model training anddeployment pipelines, testing metrics.
- Discover data sources, get access to them, import them, clean them up, and make them “machine learning ready”.
- Work with data scientists to create and refine features from the underlying data and build pipelines to train and deploy models.
- Partner with data scientists to understand, implement, refine and design machine learning and other algorithms.
- Run regular A/B tests, gather data, perform statistical analysis, draw conclusions on the impact of your models.
- Work cross functionally with product managers, data scientists and product engineers, and communicate results to peers and leaders.
- Explore new technology shifts in order to determine how they might connect with the customer benefits we wish to deliver.
- BS, MS, or PhD degree in Computer Science or related field, or equivalent practical experience.
- Knowledge of Big Data tools and frameworks (i.e. Spark, Scala, Cassandra, Hive, SQL).
- Programming experience in Scala, Java/ Python.
- Knowledge of data query and data processing tools (i.e. SQL)
- Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning).
- Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code.
- Experience with integrating applications and platforms with cloud technologies (i.e. AWS and GCP)
- Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark) and/ or interest in learning them.
- Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering) and principles (training, validation, etc.)
- Mathematics fundamentals: linear algebra, calculus, probability
Preferred Additional Qualifications:
- Experience using deep learning architectures
- Experience deploying highly scalable software supporting millions or more users
- Experience with GPU acceleration (i.e. CUDA and cuDNN)
- Interest in reading academic papers and trying to implement state-of-the-art experimental systems
Imagine a career where your creative inspiration can fuel BIG innovation. Year-over-year, Intuit has been recognized as a best employer and is consistently ranked on Fortune's "100 Best Companies To Work For" and Fortune World's "Most Admired Software Companies" lists. Immerse yourself in our award winning culture while creating breakthrough solutions that simplify the lives of consumers and small businesses and their customers worldwide.
Intuit is expanding its social, mobile, and global footprint with a full suite of products and services that are revolutionizing the industry. Utilizing design for delight and lean startup methodologies, our entrepreneurial employees have brought more than 250 innovations to market – from QuickBooks® and TurboTax®, to GoPayment, Mint.com, big data, cloud (SaaS, PaaS) and mobile apps. The breadth and depth of these customer-driven innovations mean limitless opportunities for you to turn your ingenious ideas into reality at Intuit.
Discover what it's like to be part of a team that rewards taking risks and trying new things. It's time to love what you do! Check out all of our career opportunities at: careers.intuit.com. EOE AA M/F/Vet/Disability
Intuit will consider for employment qualified applicants with criminal histories in a manner consistent with requirements of local law.
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