Job description

Come join the Fintech Risk AI/ML credit risk team(Team Apollo) as a Senior Machine Learning Engineer. Team Apollo is responsible for detecting and preventing credit risk for all lending money movement Services products. Responsibilities • In this role, you’ll be embedded inside a vibrant team of data scientists • You’ll be expected to help conceive, code, and deploy data science models at scale using the latest industry tools • Help develop and maintain web services for the AI team which orchestrate various ML functions • Important skills include data wrangling, feature engineering, developing models, and 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 to determine how they might connect with the customer benefits we wish to deliver Qualifications • BS, MS, or PhD degree in Computer Science or related field, or equivalent work experience • 6+ years of experience • Knowledgeable with Data Science tools and frameworks (i.ePython, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark) • Understand machine learning principles (training, validation, etc.) • Demonstrated experience with web services (e.g. REST) and API design.Experience with any of the following Object Oriented Languages (OOD): Scala, Python, Java preferred • 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) and workflows, and ability to write production-ready code • Experience deploying highly scalable software supporting millions or more users • Experience with GPU acceleration (i.e CUDA and cuDNN) • Experience with integrating applications and platforms with cloud technologies (i.e AWS) • Strong oral and written communication skills • Ability to conduct meetings and make professional presentations, and to explain complex concepts and technical material to non-technical users Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits ). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is: Mountain View $171,000 - $231,500

Requirements

Must-haves

Come join the Fintech Risk AI/ML credit risk team(Team Apollo) as a Senior Machine Learning Engineer. Team Apollo is responsible for detecting and preventing credit risk for all lending money movement Services products.
In this role, you’ll be embedded inside a vibrant team of data scientists
You’ll be expected to help conceive, code, and deploy data science models at scale using the latest industry tools
Help develop and maintain web services for the AI team which orchestrate various ML functions
Important skills include data wrangling, feature engineering, developing models, and 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 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 work experience
6+ years of experience
Knowledgeable with Data Science tools and frameworks (i.ePython, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark)
Understand machine learning principles (training, validation, etc.)
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) and workflows, and ability to write production-ready code
Experience deploying highly scalable software supporting millions or more users
Experience with GPU acceleration (i.e CUDA and cuDNN)
Experience with integrating applications and platforms with cloud technologies (i.e AWS)
Strong oral and written communication skills
Ability to conduct meetings and make professional presentations, and to explain complex concepts and technical material to non-technical users

Nice-to-haves

Demonstrated experience with web services (e.g. REST) and API design.Experience with any of the following Object Oriented Languages (OOD): Scala, Python, Java preferred

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlmachine learningrestapipythonjavasqlaws

Platform: career-feeds
Effort: medium