Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,394 postings in the last year. Stated ranges, not salaries paid.
Malvern, PA
Actively hiring, first seen by us 2 days agoEmployment type in the employer’s posting: Full timeFrom the employer’s posting
Vanguard is not offering visa sponsorship for this position
Develop and support data pipelines for model development using PySpark and Glue ETL
Support integration of model pipelines into production environments
Analyze raw data sources for quality and automate data ingestion for models
Run model monitoring scripts and fix pipeline issues raised by alerts
Review pipeline designs and document design changes with data science teams
Proficient with software tools that develop data pipelines in a distributed computing environment (PySprak, GlueETL)
Supports integration of model pipelines in a production environment.
Performs detailed analysis of raw data sources for data quality, applies business context, and model development needs.
Runs model monitoring scripts, follows process for alerts to management as needed.
Reviews pipeline designs, makes data model design changes as needed. Documents and reviews design changes with data science teams.
Proficiency in programming languages, particularly Python (including PySpark, PySQL) and familiarity with machine learning libraries and frameworks.
Strong understanding of cloud technologies, including AWS and Azure, and experience with NoSQL databases.
Familiarity with Feature Store usage, LLMs, GenAI, RAG, Prompt Engineering, and Model Evaluation.
Solid understanding of software engineering principles, including design patterns, testing, security, and version control.
Knowledge of Machine Learning Development Lifecycle (MDLC) best practices and protocols.
Understanding of solution architecture for building end-to-end machine learning data pipelines.
Experience with API design and development is a plus.
From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.
In the employer’s words · Read in context
Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,394 postings in the last year. Stated ranges, not salaries paid.
Day 2
Early. Similar jobs usually come down between day 8 and day 76.
From 5,460 similar postings that came down. Coming down is not always a hire.
36 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordAdd your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- At least 3 years of hands-on experience designing ETL pipelines using AWS services (e.g., Glue, SageMaker). - Proficiency in programming languages, particularly Python (including PySpark, PySQL) and familiarity with machine learning libraries and frameworks. - Strong understanding of cloud technologies, including AWS and Azure, and experience with NoSQL databases.
- Minimum of 5 years of relevant work experience. - At least 3 years of hands-on experience designing ETL pipelines using AWS services (e.g., Glue, SageMaker). - Proficiency in programming languages, particularly Python (including PySpark, PySQL) and familiarity with machine learning libraries and frameworks.
- Proficiency in programming languages, particularly Python (including PySpark, PySQL) and familiarity with machine learning libraries and frameworks. - Strong understanding of cloud technologies, including AWS and Azure, and experience with NoSQL databases. - Familiarity with Feature Store usage, LLMs, GenAI, RAG, Prompt Engineering, and Model Evaluation.
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New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Supports and performs the development and programming of machine learning integrated software algorithms to structure, analyze, and leverage data in a production environment.
Core Responsibilities
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).
Supports integration of model pipelines in a production environment. Develops understanding of SDLC for model production.
Reviews pipeline designs, makes data model design changes as needed. Documents and reviews design changes with data science teams.
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.
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.
Runs model monitoring scripts, follows process for alerts to management as needed. Addresses issues found in data pipelines from model monitoring alerts.
Participates in special projects and performs other duties as assigned.
Qualifications
Undergraduate degree or equivalent experience; a graduate degree is preferred.
Minimum of 5 years of relevant work experience.
At least 3 years of hands-on experience designing ETL pipelines using AWS services (e.g., Glue, SageMaker).
Proficiency in programming languages, particularly Python (including PySpark, PySQL) and familiarity with machine learning libraries and frameworks.
Strong understanding of cloud technologies, including AWS and Azure, and experience with NoSQL databases.
Familiarity with Feature Store usage, LLMs, GenAI, RAG, Prompt Engineering, and Model Evaluation.
Experience with API design and development is a plus.
Solid understanding of software engineering principles, including design patterns, testing, security, and version control.
Knowledge of Machine Learning Development Lifecycle (MDLC) best practices and protocols.
Understanding of solution architecture for building end-to-end machine learning data pipelines.
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.
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Malvern, PA
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.
Special Factors Sponsorship Vanguard is not offering visa sponsorship for this position. About Vanguard