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Master’s degree in Analytics, Economics, Engineering, Statistics, Mathematics, or Information Systems Management plus 3 years of experience in data querying with SQL and programming in Python for developing applications for a large organization (>10,000 employees) is required. Must have experience with: (i) handling, manipulation and analysis of large datasets (multiple gigabytes of data) persisted on Hadoop, Neo4j and cloud data platforms; (ii) using statistical analysis techniques including logistic regression, time series analysis, and hypothesis testing; (iii) utilizing data query tools including SQL, R, and Python to manipulate, analyze and interpret data; (iv) writing and implementing code to clean and transform large tabular and text datasets (typically exceeding 1 million rows of data) to a consistent format usable in data visualization and developing machine learning models; (v) enriching in-house data by integrating with external data sources (Bureau and third party vendor data) to extract and analyze trends for risk management; (vi) designing rich data visualizations to communicate complex ideas to customers or company leaders; (vii) programmatically extracting data from a Hadoop database and transforming the data into a presentable form using Python plotting libraries (Matplotlib and Seaborn) and Tableau visualizations; and (viii) building machine learning models to drive business insights and improve financial outcomes.
This position is subject to the requirements of Section 19 of the Federal Deposit Insurance Act (FDIA) and, for any registered role, the Secure and Fair Enforcement for Mortgage Licensing Act of 2008 (SAFE Act) and/or the Financial Industry Regulatory Authority (FINRA), which prohibit the hiring of individuals with certain criminal history.
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Position Responsibilities:
- Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications.- Routinely build and deploy ML models on available data.
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
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- Pioneer new approaches to foundation models
- Publish and present research at top-tier conferences and journals
- Work with state-of-the-art LLMs and multi-modal foundation models
- Access to substantial computational resources for researchKey job responsibilities
- Research and develop novel techniques for efficient runtime inference (low latency, high throughput)
- Design and evaluate efficient foundation model architectures
- Create new methods for improving training efficiency
- Conduct experimental studies to validate efficiency improvements
- Write high-quality Python code to implement research ideas- Author technical documentation and research papers
- Present findings to technical and non-technical stakeholders
A day in the life
Your day might start with a team stand-up to discuss ongoing projects and brainstorm solutions to technical challenges. You'll spend time implementing and testing new efficiency optimization techniques in Python, analyzing performance metrics, and iterating on approaches. You'll collaborate with team members to review code and research results, participate in technical discussions about architecture designs, and engage with other AGI teams to understand their efficiency needs. You might end your day analyzing experimental results or writing up findings for a research paper. Throughout the week, you'll have opportunities to present your work to stakeholders and contribute to the team's research roadmap.
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
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