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Graduate Machine Learning Jobs in Dallas, TX (NOW HIRING)

Vanguard

Manager, Machine Learning Engineer

Dallas, TX

$101K - $133K/yr

Leads a team of Machine Learning Engineers responsible for designing, building, deploying, and ... Graduate degree preferred. * Minimum of eight years related work experience. Special Factors ...

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Graduate Machine Learning information

See Dallas, TX salary details

$25.2K

$42.1K

$87.1K

How much do graduate machine learning jobs pay per year?

As of Sep 12, 2026, the average yearly pay for graduate machine learning in Dallas, TX is $42,125.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,200.00 and $45,500.00 per year, depending on experience, location, and employer.

What is a graduate machine learning?

A Graduate Machine Learning job is an entry-level role designed for recent graduates with a background in machine learning, data science, or a related field. It typically involves working on data-driven projects, developing machine learning models, and assisting in research or engineering tasks. Graduates may collaborate with data scientists, software engineers, and business teams to design algorithms, optimize models, and deploy AI solutions. This role helps build practical experience in applying ML techniques to real-world problems while contributing to the organization's AI initiatives.

What does the typical career progression look like for a graduate machine learning?

As a Graduate Machine Learning professional, you will usually begin your career by working on smaller projects or supporting senior scientists with data preparation, model training, and performance evaluations. Over time, as you gain experience and demonstrate technical proficiency, you’ll be given more complex, independent projects and may specialize in areas like natural language processing, computer vision, or deep learning. Many organizations provide opportunities for mentorship, professional development, and advanced certifications, paving the way for roles such as Machine Learning Engineer, Data Scientist, or Research Scientist. This path offers significant opportunities for growth, both in terms of technical expertise and leadership potential.

What are the key skills and qualifications needed to thrive in the graduate machine learning position, and why are they important?

To thrive as a Graduate Machine Learning professional, you need a solid understanding of statistics, data analysis, machine learning algorithms, and programming languages such as Python or R, typically supported by a relevant degree. Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch), data visualization tools, and version control systems like Git is common. Strong problem-solving abilities, communication skills, and a collaborative mindset will help you stand out in team-based environments. These competencies are vital for effectively building, analyzing, and refining models to address real-world business challenges.

What are popular job titles related to Graduate Machine Learning jobs in Dallas, TX?

For Graduate Machine Learning jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Graduate Machine Learning jobs in Dallas, TX look for?

The top searched job categories for Graduate Machine Learning jobs in Dallas, TX are:

Graduate Machine Learning jobs near you
Infographic showing various Graduate Machine Learning job openings in Dallas, TX as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 73% Full Time, 22% Part Time, and 3% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $42,125 per year, or $20.3 per hour.

Manager, Machine Learning Engineer

Dallas, TX

Vanguard
Photography Services • 1 - 5K employees
Learn more about Vanguardexternal

$101K - $133K/yr

Full-time

Re-posted 10 days ago

Key responsibilities

  • Leads a team of Machine Learning Engineers in designing, building, deploying, and scaling AI/ML solutions.

  • Partners with cross-functional teams to deliver production-grade AI capabilities and ensure alignment with business objectives.

  • Oversees the end-to-end solution delivery, including architecture planning, implementation, deployment, monitoring, and continuous improvement.

Job description

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 workstreams.

  • 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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