Performs the development and programming of machine learning integrated software algorithms to structure, analyze, and leverage data in a production environment. Leverages detailed understanding of machine learning models and their deployment architecture.

　　Core Responsibilities

　　Develops complex data pipelines and implements data engineering design principles for iterative data pipeline development to drive scale and efficiency. Proficient in model development environments and coding best practices to enable model deployment.

　　Integrates and optimizes existing data and model pipelines in a production environment. Identifies and diagnoses data inconsistencies and errors, documents assumptions, and forages to fill data gaps. Applies knowledge of experimental methodologies, statistics, optimization, probability theory, and machine learning concepts to create self-running artificial intelligence (AI) systems to automate predictive models. Proficient in SDLC processes and related tools and technologies.

　　Partners with data science teams to review model ready dataset document/feature documentation. Develops data model design and document and reviews for completeness with data science teams.

　　Partners with data science teams to understand data requirements, performs data discovery for model development. Performs detailed analysis of raw data sources for data quality, applies business context, and model development needs. Drives efficiency through the use of data discovery tools.

　　Engages with internal stakeholders to understand and probe business processes and develop hypotheses. Brings structure to requests and translates requirements into an analytic approach. Participates in and influences ongoing business planning and departmental prioritization activities.

　　Writes model monitoring scripts as needed. Diagnoses root causes based on model monitoring alerts and triages issues. Coordinates and plans response to model monitoring alerts and resolves issues.

　　Serves as a machine learning engineering subject matter expert on cross functional teams for large strategic initiatives and contributes to the growth of the Vanguard analytic community.

　　Participates in special projects and performs other duties as assigned.

　　Qualifications

　　PhD or Master in a relevant discipline such as Computer Science, Cognitive Science, Mathematics, Statistics, Physics, Electrical & Computer Engineering.

　　At least 7+ years of experience in AI research in industry or academic setting

　　Strong expertise in various AI/ML concepts and paradigm. Strong expertise in at least one or more of the following areas: Speech Recognition, Natural Language Processing, Reinforcement Learning, Generative AI, Language modeling, Knowledge Graph, Time-Series Analysis, or Generative AI.

　　Experience with machine learning development lifecycle and deep learning methods such as Transformers, GANs , DQN, VAE , SHAP , Attention networks, Counterfactuals and Adversarial examples etc.

　　Strong software engineering capabilities and hands-on experience with various machine learning and deep learning frameworks including numpy , scikit-learn, keras , PyTorch and Tensorflow

　　A strong understanding of the real-world advantages and drawbacks of various algorithms and the ability to measure success

　　Ability to write clean, understandable code that follows leading industry standards and practices and is well-documented, and to build easily reproducible models

　　Special Factors

　　Sponsorship

　　Vanguard is not offering visa sponsorship for this position.

　　About Vanguard

　　We are Vanguard. Together, we’re changing the way the world invests.

　　For us, investing doesn’t just end in value. It starts with values. Because when you invest with courage, when you invest with clarity, and when you invest with care, you can get so much more in return. We invest with purpose – and that’s how we’ve become a global market leader. Here, we grow by doing the right thing for the people we serve. And so can you.

　　We want to make success accessible to everyone. This is our opportunity. Let’s make it count.

　　Inclusion Statement

　　Vanguard’s continued commitment to diversity and inclusion is firmly rooted in our culture. Every decision we make to best serve our clients, crew (internally employees are referred to as crew), and communities is guided by one simple statement: “Do the right thing.”

　　We believe that a critical aspect of doing the right thing requires building diverse, inclusive, and highly effective teams of individuals who are as unique as the clients they serve. We empower our crew to contribute their distinct strengths to achieving Vanguard’s core purpose through our values.

　　When all crew members feel valued and included, our ability to collaborate and innovate is amplified, and we are united in delivering on Vanguard's core purpose.

　　Our core purpose: To take a stand for all investors, to treat them fairly, and to give them the best chance for investment success.

　　How We Work

　　Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.

　　Vanguard, one of the world's largest investment management companies, serves individual investors, institutions, employer-sponsored retirement plans, and financial professionals. We have a diverse and talented crew with a culture that promotes teamwork, along with an unwavering focus on serving our clients' best interests.

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