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Full Time Machine Learning Engineer New Grad Jobs in Dallas, TX

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

The minimum and maximum full-time annual salaries for this role are listed below, by location ... New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other ...

... new environments -- and building the infrastructure that makes world-scale RL training possible ... Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ...

... new environments -- and building the infrastructure that makes world-scale RL training possible ... Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ...

... new environments -- and building the infrastructure that makes world-scale RL training possible ... Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ...

Eligible full-time teammates enjoy access to medical, dental, vision, life, disability, and AD&D ... new parent leave, and more. Eligible positions may also qualify for restricted stock unitsand/or a ...

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 ...

Sr. Machine Learning Engineer

Richardson, TX · On-site

$94K - $129K/yr

It enables a new generation of intelligent capabilities across our products, including Realm-X ... Regular full-time employees are eligible for benefits - see here. #LI-KB1

Showing results 21-40

Full Time Machine Learning Engineer New Grad information

See Dallas, TX salary details

$31.2K

$127.4K

$191.4K

How much do full time machine learning engineer new grad jobs pay per year?

As of Aug 15, 2026, the average yearly pay for full time machine learning engineer new grad in Dallas, TX is $127,383.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,400.00 and $153,300.00 per year, depending on experience, location, and employer.

What does a full time machine learning engineer new grad do?

A Full Time Machine Learning Engineer New Grad is an entry-level professional who designs, builds, and deploys machine learning models as part of a technical team. They often work on tasks such as data preprocessing, developing and testing algorithms, and integrating models into production systems. New grad engineers usually collaborate with data scientists, software engineers, and product teams to solve real-world problems using machine learning. Their responsibilities also include staying updated with the latest advancements in the field and learning best practices for model development and deployment.

What are the key skills and qualifications needed to thrive as a full time machine learning engineer new grad, and why are they important?

To excel as a Full Time Machine Learning Engineer New Grad, you typically need a solid background in computer science, statistics, and mathematics, often demonstrated through a relevant degree or coursework. Familiarity with programming languages like Python, and experience with machine learning libraries such as TensorFlow or PyTorch, as well as tools for data analysis and version control, are essential. Strong problem-solving abilities, effective communication, and a willingness to learn new technologies help new grads stand out in collaborative and fast-paced environments. These skills and qualities are crucial for building effective models, working well within teams, and adapting to the rapidly evolving field of machine learning.

What are some common challenges new graduates face when transitioning into a full-time machine learning engineer role?

New graduates entering a full-time Machine Learning Engineer position often encounter challenges such as adapting to large-scale production systems, collaborating with cross-functional teams, and bridging the gap between academic projects and real-world business problems. Unlike school assignments, industry projects require scalable, maintainable code and thorough documentation. Additionally, new grads must quickly learn to communicate their technical findings to non-technical stakeholders and prioritize tasks amid fast-paced development cycles.

What is the difference between Full Time Machine Learning Engineer New Grad vs Data Scientist New Grad?

AspectFull Time Machine Learning Engineer New GradData Scientist New Grad
Required CredentialsBachelor's in CS, Math, or related; some internshipsBachelor's in Statistics, CS, or related; some internships
Work EnvironmentDeveloping ML models, deploying algorithms, coding in Python/C++Analyzing data, creating reports, statistical modeling
Industry UsageTech, finance, healthcare, focusing on ML systemsTech, marketing, finance, focusing on data analysis

Full Time Machine Learning Engineer New Grad roles focus on building and deploying machine learning models, requiring coding and engineering skills. Data Scientist New Grad roles emphasize data analysis, statistical modeling, and insights. Both roles often share similar educational backgrounds but differ in daily tasks and technical focus.

What are popular job titles related to Full Time Machine Learning Engineer New Grad jobs in Dallas, TX?

For Full Time Machine Learning Engineer New Grad jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Full Time Machine Learning Engineer New Grad jobs in Dallas, TX look for?

The top searched job categories for Full Time Machine Learning Engineer New Grad jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Full Time Machine Learning Engineer New Grad jobs?

Cities near Dallas, TX with the most Full Time Machine Learning Engineer New Grad job openings:

Lead Machine Learning Engineer

Capital One

Plano, TX • On-site

$98K - $129K/yr

Full-time

Re-posted 19 hours ago


Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 147 frontline employees who took The Breakroom Quiz

91st of 171 rated banks


Job description

Lead Machine Learning Engineer
As a Capital One Lead Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing Generative AI and advanced agentic systems at scale. You'll lead the detailed technical design, development, and implementation of core agentic architectures and multi-agent workflows using emerging technologies. You'll focus on system-level architectural design, develop and review complex models and application code, and ensure the high availability, performance, and security of our generative AI applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in generative and agentic machine learning engineering.
What you'll do in the role:
  • Architect Agentic Platforms: Design, develop, and scale core agentic engines and multi-agent workflow solutions, enabling seamless composition of conversational and business automation workflows.
  • Drive AI Evaluation & Trust: Build and integrate scalable evaluation (Evals) and observability frameworks into solutions to ensure model predictability, performance monitoring, and mitigation of model risk.
  • Deliver High-Impact Use Cases: Partner with cross-functional product and business teams to deploy production AI solutions, including next-generation consumer AI experiences, intelligent recommendation engines, and advanced conversational assistants.
  • Enforce Enterprise Guardrails: Ensure all AI/ML applications strictly adhere to robust data privacy standards, regulatory postures, and framework auditability/explainability.
  • Translate Practical Research: Stay abreast of practical advancements in LLM optimization, retrieval-augmented generation (RAG), and multi-agent design patterns, judiciously applying these novel techniques to production systems.
  • Technical Leadership & Code Excellence: Provide technical direction, architectural oversight, and rigorous code reviews for engineering teams, fostering a culture of modern engineering excellence.

Basic Qualifications:
  • Bachelor's Degree
  • At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)
  • At least 4 years of experience programming with Python, Scala, or Java

Preferred Qualifications:
  • Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
  • 3+ years of experience with GenAI frameworks (e.g., LangChain, LangGraph, LlamaIndex) and Vector Databases
  • 3 years of experience building, scaling, and optimizing Large Language Model (LLM) or GenAI orchestration systems in production
  • 2+ years of experience building automated evaluations (Evals) and observability pipelines for LLMs
  • 3+ years of on-the-job experience with an industry-recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
  • Experience deploying AI solutions within a strictly regulated environment, incorporating data privacy and model risk governance
  • Demonstrated ability to lead technical architecture design and provide deep technical guidance to engineering teams
  • Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
  • ML industry impact through conference presentations, papers, blog posts, open-source contributions, or patents

At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer).
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
Plano, TX: $179,400 - $204,700 for Lead Machine Learning Engineer
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.
No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

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