Machine Learning Engineer, Specialist

Malvern, PA, US • Posted 2 days ago • Updated 20 hours ago
Full Time
On-site
Fitment

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Job Details

Skills

  • Wealth Management
  • Financial Planning
  • Artificial Intelligence
  • Amazon SageMaker
  • Amazon Lambda
  • Step-Functions
  • Electronic Health Record (EHR)
  • Data Engineering
  • Modeling
  • Software Development
  • Jupyter
  • Optimization
  • Supervised Learning
  • Deep Learning
  • Generative Artificial Intelligence (AI)
  • Distribution
  • Distributed Computing
  • PySpark
  • Extract
  • Transform
  • Load
  • Software Development Methodology
  • Data Modeling
  • Data Science
  • Data Quality
  • Business Process
  • Analytical Skill
  • Business Planning
  • Scripting
  • Python
  • Pandas
  • TensorFlow
  • PyTorch
  • Software Design
  • Data Collection
  • Data Analysis
  • Evaluation
  • Amazon Web Services
  • Cloud Computing
  • Cloud Architecture
  • Amazon EC2
  • Amazon S3
  • Virtual Private Cloud
  • Remote Desktop Services
  • Amazon RDS
  • Training
  • Machine Learning (ML)
  • Finance
  • Collaboration

Summary

Job Description

Join the visionary team of Vanguard s Advice Wealth Management Technology Data & Analytics Engineering! We are looking for a competitive engineer to join us as a Machine Learning Engineer, pioneering innovative models that tackle complex financial planning and portfolio construction challenges. Our AI/ML group stands at the forefront of technological advancement, delivering sophisticated machine learning models powered by cutting-edge methodologies and strategies. We continuously explore the latest machine learning technologies, including GenAI, to enhance our solutions and stay ahead of the curve.

The successful candidate will:

  • Bring strong proficiency and understanding of the AWS cloud platform and services, including (but not limited to) AWS SageMaker, AWS Lambda, Amazon S3, Step Functions, EMR, Glue, and other services supporting machine learning platforms.

  • Demonstrate an excellent understanding of the machine learning development lifecycle, including data engineering, exploratory data analysis, modeling, and ML implementation and operations.

  • 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.

  • Be proficient in software development and well-versed in developer tools such as Python, VS Code, and Jupyter Notebooks.

  • Be passionate about advances in machine learning, with knowledge of supervised learning, reinforcement learning, deep learning, and GenAI.

  • Demonstrate knowledge of AWS security practices, including IAM, S3 bucket policies, security groups, and VPCs.

  • Understand best practices for model training, deployment, and operations, including hyperparameter optimization, model evaluation, and operationalizing ML solutions.

  • Utilize popular Python frameworks such as TensorFlow, PySpark, PyTorch, and Pandas.

  • Leverage software design patterns to develop modular, maintainable, and scalable code.

Responsibilities:

  • Participate in end-to-end machine learning projects, from conception through deployment and ongoing support.

  • Collaborate with data scientists to solve complex machine learning challenges, including supervised learning, reinforcement learning, deep learning, and GenAI.

  • Work closely with methodology researchers to integrate insights and strategies that improve investor outcomes.

  • Solve complex problems using multilayered datasets, enhance existing libraries, frameworks, and models, and collaborate with data analysts, data engineers, and architects to identify data distribution differences that affect model performance.

  • Leverage data pipeline designs and support the development of data pipelines for model development.

  • Use software tools to build data pipelines in distributed computing environments (e.g., PySpark, Glue ETL).

  • Support the integration of model pipelines into production environments and develop an understanding of the SDLC for model production.

  • Review pipeline designs, make data model changes as needed, and document and review design changes with data science teams.

  • Support data discovery and automated ingestion for model development by analyzing raw data sources for data quality, applying business context, and addressing model development needs.

  • Engage with internal stakeholders to understand business processes, develop hypotheses, structure requests, and translate requirements into analytic approaches.

  • Participate in and influence ongoing business planning and departmental prioritization activities.

  • Run model monitoring scripts, follow alerting processes, and address issues identified through model monitoring.

  • Participate in special projects and perform other duties as assigned.

Qualifications:

  • 5 7 years of experience in programming with strong coding proficiency.

  • Proficiency in Python and its ecosystem, including Pandas, TensorFlow, PyTorch, software design patterns, data and model pipelines, data collection and preparation, exploratory data analysis, model evaluation, monitoring, and maintenance.

  • 3 5 years of experience with AWS cloud services, including core services, monitoring and logging, cloud architecture, CloudFormation templates, EC2, S3, Lambda, VPC, IAM, RDS, and CloudWatch.

  • Undergraduate degree or an equivalent combination of education, training, and experience.

What Sets You Apart: (nice to have)

  • Experience in other engineering disciplines related to machine learning is a plus.

  • Minimum of 2 5 years of hands-on 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.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: zipfeed
  • Position Id: 277b78416c9cf3dc
  • Posted 2 days ago
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