Join the visionary team of Vanguard’s Advice Wealth Management Technology’s Data & Analytics Engineering! We are on the lookout for a passionate Machine Learning Engineer to pioneer innovative models that tackle the most intricate financial planning and portfolio construction challenges. Our AIML group stands at the forefront of technological advancement, boasting the most sophisticated machine learning models driven by cutting-edge methodologies and strategies. Continuously investigating the latest in machine learning technologies, including GenAI, we strive to enhance our solutions and stay ahead of the curve. Embark on this exciting journey with Data & Analytics Engineering and shape the future of Advice Wealth Management Technology!
This person will participate in end-to-end machine learning projects from conception through deployment and ongoing support. Collaborating with data scientists to dive into complex machine learning challenges that push the boundaries of current technological capabilities, including supervised learning, reinforcement learning, deep learning, and GenAI. In addition, working closely with methodology researchers to integrate valuable insights and strategies to improve investor outcomes. Solve complex problems with multilayered data sets, enhance existing libraries, frameworks and models, and work with data analysts, data engineers, and architecture to identify data distribution differences affecting model performance.
The successful candidate will:
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Bring proficiency and excellent understanding of the AWS cloud platform and services, including but not limited to AWS Sage Maker, AWS Lambda, S3 buckets, Step Functions, EMR, Glue, and other services that support building machine learning platforms.
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Have an excellent understanding of the machine learning development cycle, including data engineering, exploratory data analysis, modeling, and machine learning implementation and operations.
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Design and implement scalable machine learning solutions, develop predictive models using advanced deep learning and statistical techniques, collaborate with data science and engineering teams to integrate ML solutions, and perform rigorous model evaluation and optimization.
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Be proficient in software development and well-versed with developer tools such as, but not limited to, Python, VS Code, and Jupiter Notebooks.
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Be passionate about new advances in machine learning, knowledgeable about supervised learning, reinforcement learning, deep learning, and GenAI.
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Demonstrate knowledge of AWS security practices, including IAM, S3 bucket policies, security groups, and VPCs.
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Understand best practices for model training, deployment, and operations, including hyperparameter optimization, model evaluation, and operationalizing ML solutions.
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Utilize popular Python frameworks such as TensorFlow, PySpark, PyTorch, and Pandas.
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Leverage software design patterns to develop modular, maintainable, and scalable code.
Responsibilities:
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Leverages data pipeline designs and supports the development of data pipelines to support model development. Proficient with software tools that develop data pipelines in a distributed computing environment (PySprak, GlueETL).
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Supports integration of model pipelines in a production environment. Develops understanding of SDLC for model production.
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Reviews pipeline designs, makes data model design changes as needed. Documents and reviews design changes with data science teams.
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Supports data discovery & automated ingestion for model development. Performs detailed analysis of raw data sources for data quality, applies business context, and model development needs.
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Engages with internal stakeholders to understand and probe business processes in order to develop hypotheses. Brings structure to requests and translates requirements into an analytic approach. Participates in and influences ongoing business planning and departmental prioritization activities.
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Runs model monitoring scripts, follows process for alerts to management as needed. Addresses issues found in data pipelines from model monitoring alerts.
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Participates in special projects and performs other duties as assigned.
Qualifications:
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5 to 7 years experience with programming and coding proficiency.
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Proficiency in Python and its ecosystem of frameworks such as Pandas, Tensor flow, PyTorch, Software Design patterns, data and model pipelines, data collection & preparation, exploratory data analysis, model evaluation, model monitoring and maintenance
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3 to 5 years' experience with AWS cloud skills – core AWS services, monitoring & logging, cloud architecture, Cloud Formation Templates, EC2 Instances, S3 Buckets, Lambda Functions, VPC (Virtual Private Cloud), IAM RDS, Cloud Watch, etc.
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Undergraduate degree or equivalent combination of training and experience.
Additional Skills:
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If you have experience in other engineering disciplines similar to machine learning, please apply.
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Minimum of 2-5 years of related work experience in Machine Learning.
Special Factors
Sponsorship
Vanguard is not offering visa sponsorship for this position.
About Vanguard
At Vanguard, we don't just have a mission—we're on a mission.
To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.
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.
Top Skills
What We Do
We are a community of 30 million who think – and feel – differently about investing. Together, we’re changing the way the world invests.
Since our founding in 1975, helping our investors achieve their goals is our sole reason for existence. With no other parties to answer to and therefore no conflicting loyalties, we make every decision—like keeping investing costs as low as possible—with only your needs in mind.
Vanguard is one of the world's largest investment companies, offering a large selection of high-quality low-cost mutual funds, ETFs, advice, and related services. Individual and institutional investors, financial professionals, and plan sponsors can benefit from the size, stability, and experience Vanguard offers. As of April 30, 2019, we managed more than $5.6 trillion in global assets. In addition, we have 189 funds in the United States and 225 funds in global markets.
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