Senior AI/ML Engineer

Reposted 3 Days Ago
3 Locations
In-Office
Senior level
Fintech
The Role
Develop and optimize data pipelines, integrate model pipelines, collaborate with data science teams, and maintain model monitoring scripts. Stay updated on AI/ML advancements.
Summary Generated by Built In

Overview:

We are seeking an experienced Senior Machine Learning Engineer to join our AI/ML Engineering team. You will be responsible for developing and optimizing complex data pipelines, integrating model pipelines, and building scalable AI/ML solutions, including large language models (LLMs). The ideal candidate will possess a robust background in traditional machine learning, deep learning, and significant experience with large datasets and cloud-based AI services.

Responsibilities:

  • 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, diagnosing data inconsistencies and documenting assumptions.

  • 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, ensuring completeness and accuracy.

  • Perform data discovery and analysis of raw data sources, applying business context to meet model development needs.

  • Comfort with exploratory data exploration and tracking data lineage during inception or root cause analysis.

  • Engage with internal stakeholders to understand business processes and translate requirements into analytical approaches.

  • Write and maintain model monitoring scripts, diagnosing issues and coordinating resolutions based on alerts.

  • Serve as a domain expert in machine learning engineering on cross-functional teams for significant initiatives.

  • Stay updated with the latest advancements in AI/ML and apply them to real-world challenges.

  • Participate in special projects and additional duties as assigned.

Qualifications:

  • Undergraduate degree or equivalent experience; a graduate degree is preferred.

  • Minimum of 8 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.

Skills Required

  • Minimum of 8 years of relevant work experience
  • At least 3 years of hands-on experience designing ETL pipelines using AWS services
  • Proficiency in programming languages, particularly Python (including PySpark, PySQL)
  • Strong understanding of cloud technologies, including AWS and Azure
  • Understanding of solution architecture for building end-to-end machine learning data pipelines

Vanguard Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Vanguard and has not been reviewed or approved by Vanguard.

  • Retirement Support Retirement support appears unusually strong through a 401(k) design that includes a match plus an additional employer contribution, which can materially lift long-term total rewards. HSA seeding and an enhanced employer match further strengthen the savings-and-benefits value of the package.
  • Wellbeing & Lifestyle Benefits Wellbeing and lifestyle support is reinforced by a sizable annual FlexFund stipend that can be applied across many day-to-day categories such as fitness, childcare, and other personal expenses. On-site or virtual clinics and fitness options add practical health and wellness convenience.
  • Affordable Benefits Healthcare and related benefits are positioned as comparatively affordable via heavily subsidized medical plans and broad coverage options. This affordability can offset moderate base pay for employees who place higher value on out-of-pocket cost reductions.

Vanguard Insights

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The Company
Charlotte, NC
20,252 Employees
Year Founded: 1975

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. For Commenting Guidelines & Important information, visit here: http://vanguard.com/linkedin Vanguard Marketing Corporation, Distributor.

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