Senior Machine Learning Engineer
Red Cell PartnersSalary not specified
- Full Time
- Senior (5 to 8 years)
Not SpecifiedCompensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Financial ServicesIndustries
Requirements
Candidates should possess an undergraduate degree or equivalent experience, and a graduate degree is preferred, with a minimum of 8 years of relevant work experience and at least 3 years of hands-on experience designing ETL pipelines using AWS services such as Glue and SageMaker. Proficiency in Python (including PySpark and PySQL) and familiarity with machine learning libraries and frameworks are required, along with a strong understanding of cloud technologies like AWS and Azure, and experience with NoSQL databases. Familiarity with Feature Store usage, LLMs, GenAI, RAG, Prompt Engineering, and Model Evaluation is also necessary, as is experience with API design and development. A solid understanding of software engineering principles, including design patterns, testing, security, and version control, is expected, along with knowledge of the Machine Learning Development Lifecycle (MDLC) best practices and protocols.
Responsibilities
The Senior Machine Learning Engineer will develop and optimize complex data pipelines, applying machine learning engineering principles to enhance efficiency and scalability, integrate and optimize data and model pipelines within production environments, diagnose data inconsistencies, and document assumptions. They will employ experimental methodologies, statistics, and machine learning concepts to create self-running AI systems for predictive modeling, collaborate with data science teams to review model-ready datasets and feature documentation, perform data discovery and analysis of raw data sources, and apply business context to meet model development needs. The role involves comfort with exploratory data exploration and tracking data lineage, engaging with internal stakeholders to understand business processes and translate requirements into analytical approaches, writing and maintaining model monitoring scripts, diagnosing issues, and coordinating resolutions based on alerts, serving as a domain expert in machine learning engineering on cross-functional teams for significant initiatives, and staying updated with the latest advancements in AI/ML. Additionally, the engineer will participate in special projects and additional duties as assigned.
Skills
Machine Learning
Deep Learning
Data Pipelines
Model Deployment
Cloud AI Services
Data Analysis
Model Monitoring
ETL Pipeline Design
Data Lineage
Statistical Methods
Experimentation
Feature Engineering
Vanguard
Client-owned investment management firm offering low-cost funds
About Vanguard
Vanguard provides financial services with a focus on investment management. The company offers a variety of products, including mutual funds, exchange-traded funds (ETFs), individual retirement accounts (IRAs), and 401k rollovers, aimed at individual investors, financial advisors, and institutions. Vanguard's unique ownership structure means it is owned by its funds, which are in turn owned by the clients, allowing it to prioritize the needs of its investors over external shareholders. This model enables Vanguard to offer low-cost investment options, as it primarily earns revenue through management fees that are generally lower than industry standards. Additionally, Vanguard provides personalized investment advisory services, charging fees based on the assets managed. The company's goal is to help clients grow their wealth and achieve their financial objectives through effective investment strategies, while maintaining a competitive performance track record.
Kline Township, PennsylvaniaHeadquarters
1975Year Founded
SECONDARYCompany Stage
Fintech, Financial ServicesIndustries
10,001+Employees