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Manager, Machine Learning Engineer

Job in Dallas, Dallas County, Texas, 75201, USA
Listing for: Hackajob
Full Time position
Listed on 2026-08-15
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Job Description & How to Apply Below

Machine Learning Engineering Lead

Leads a team of Machine Learning Engineers responsible for designing, building, deploying, and scaling AI/ML solutions that support Financial Advisory Services (FAS) business objectives. Partners closely with Product, Data Science, Architecture, and Technology teams to deliver production-grade AI capabilities with a strong focus on scalability, reliability, governance, and operational excellence. Drives end-to-end solution delivery from architecture planning through implementation, deployment, monitoring, and continuous improvement.

Core

Responsibilities
  • Provides leadership in hiring, coaching, talent development, performance management, and compensation decisions in accordance with Human Resources policies and procedures.
  • Partners with Enterprise, Solution, and Domain Architects to define AI/ML solution architectures and translate strategic initiatives into executable roadmaps, epics, and engineering work streams.
  • Leads cross-functional delivery across Product, Data Science, Platform, and Engineering teams, driving solutions from concept through production while ensuring alignment to business objectives and enterprise standards.
  • Establishes engineering practices, reusable frameworks, and platform capabilities that improve scalability, consistency, and delivery efficiency across AI/ML initiatives.
  • Oversees the design, implementation, and evolution of data, feature, and model pipelines to support reliable and scalable AI/ML solutions.
  • Applies expertise in machine learning, statistics, optimization, and experimentation methodologies to operationalize predictive and decision-support capabilities.
  • Evaluates data quality, feature readiness, and model inputs in partnership with Data Science teams to support successful model development and deployment.
  • Drives operational excellence through automation, observability, monitoring, incident management, and continuous improvement practices for production AI/ML systems.
  • Ensures adherence to enterprise governance, security, risk, compliance, and model lifecycle management requirements.
  • Engages business and technology stakeholders to understand objectives, assess opportunities, and translate complex requirements into actionable technical solutions.
  • Supports departmental planning, prioritization, and execution of strategic objectives while balancing delivery commitments, operational needs, and organizational goals.
  • Establishes scalable operating models, support processes, and service standards that enable long-term sustainability of AI/ML products and platforms.
  • Communicates technical strategy, solution recommendations, delivery progress, and business impact to senior technology and business leaders.
  • Participates in special projects and performs other duties as assigned.
Qualifications
  • Undergraduate degree or equivalent combination of training and experience. Graduate degree preferred.
  • Minimum of eight years related work experience.
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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