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Lead Machine Learning Engineer Jobs in Texas (NOW HIRING)

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

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.

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

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.

Lead the design and delivery of end-to-end ML systems powering recommendations, ranking, and ... Strong expertise in machine learning, with a track record of delivering end-to-end systems in ...

Lead Machine Learning Engineer

Austin, TX · On-site

$255K - $280K/yr

Lead the design and delivery of end-to-end ML systems powering recommendations, ranking, and ... Strong expertise in machine learning, with a track record of delivering end-to-end systems in ...

Machine Learning Engineer

Austin, TX · On-site

$140K - $180K/yr

🚀 Machine Learning Engineer 📍 Austin, TX (Hybrid/Remote Considered) 💰 $140,000 - $180,000 Base We're partnering with a fast-growing energy firm looking to hire a Machine Learning Engineer to ...

Avride develops autonomous vehicle and delivery robot technology, and they are seeking an experienced Machine Learning Engineer to enhance their autonomous systems. The role involves developing and ...

About the role We are looking for an experienced Machine Learning Engineer with a strong background in developing and deploying modern machine learning solutions for complex real-world challenges. In ...

We are looking for a passionate, highly motivated, and hands-on applied Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and develop ...

Machine Learning Engineer LOCATION San Antonio, TX 78208 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative ...

About the role We are looking for an experienced Machine Learning Engineer with a strong background in developing and deploying modern machine learning solutions for complex real-world challenges. In ...

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and scaling AI solutions, while collaborating with cross-functional teams to advance machine learning ...

About the Role As a Machine Learning Engineer at Shipwell, you'll play a pivotal role in building and scaling our AI-powered logistics solutions. You'll design, develop, and maintain the data ...

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and scaling AI solutions, while collaborating with cross-functional teams to advance machine learning ...

Overview Quarterhill is seeking a Machine Learning Engineer to join our forward-thinking team building the next generation of Intelligent Transportation Systems . In this role, you will design ...

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Showing results 1-20

Lead Machine Learning Engineer information

See Texas salary details

$39.6K

$115.3K

$168.2K

How much do lead machine learning engineer jobs pay per year?

As of Jul 20, 2026, the average yearly pay for lead machine learning engineer in Texas is $115,324.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,500.00 and $125,800.00 per year, depending on experience, location, and employer.

How much does a lead machine learning engineer make?

A lead machine learning engineer typically earns between $120,000 and $180,000 annually, depending on experience, location, and industry. Senior roles often include responsibilities such as designing models, leading teams, and working with advanced tools like TensorFlow or PyTorch.

How does a Lead Machine Learning Engineer typically collaborate with cross-functional teams during a project?

As a Lead Machine Learning Engineer, you'll frequently work alongside data scientists, software engineers, product managers, and sometimes domain experts to drive projects from conception to deployment. You are often responsible for translating business requirements into scalable machine learning solutions, coordinating model development, and ensuring integration with existing systems. Clear communication and the ability to explain complex technical concepts to non-technical stakeholders are essential, as you may need to guide team members and align everyone's efforts toward project goals. This collaborative environment fosters both technical and leadership growth.

What are the key skills and qualifications needed to thrive as a Lead Machine Learning Engineer, and why are they important?

To thrive as a Lead Machine Learning Engineer, you need advanced expertise in machine learning algorithms, data modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Familiarity with frameworks such as TensorFlow, PyTorch, cloud computing platforms, and version control systems is essential, along with relevant certifications. Strong leadership, collaboration, and problem-solving skills help you manage teams and communicate complex technical ideas effectively. These skills and qualities are crucial for driving successful AI initiatives, ensuring project delivery, and fostering innovation within cross-functional teams.

Will MLE be replaced by AI?

Lead Machine Learning Engineers (MLEs) design, develop, and oversee AI systems, and while AI automation can handle certain tasks, MLEs are essential for creating, tuning, and maintaining complex models. AI tools support MLEs but do not replace the need for human expertise in understanding data, ethical considerations, and system deployment. The role evolves with advancements in AI, emphasizing skills in model development, programming, and problem-solving.

What does a Lead Machine Learning Engineer do?

A Lead Machine Learning Engineer oversees the design, development, and deployment of machine learning models within an organization. They guide a team of engineers and data scientists, ensuring best practices in model architecture, data management, and production pipelines. Their responsibilities often include collaborating with stakeholders, mentoring junior team members, and staying up-to-date with the latest advancements in machine learning. Lead ML Engineers also play a key role in translating business objectives into technical solutions and ensuring scalability and reliability of AI systems.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position such as Lead Machine Learning Engineer or senior AI executive roles that offer compensation in this range, including salary, bonuses, and stock options. These roles usually require extensive experience, advanced skills in machine learning, deep learning, and data science, and often involve leadership responsibilities in developing AI strategies and solutions.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or at large tech companies can earn salaries approaching or exceeding $500,000 annually, especially when including bonuses and stock options. Achieving this level typically requires a strong educational background, specialized certifications, and a track record of impactful projects.
Lead Machine Learning Engineer

Lead Machine Learning Engineer

Capital One

Plano, TX • On-site

$98K - $129K/yr

Full-time

Re-posted 4 days ago


Capital One rating

7.8

Company rating: 7.8 out of 10

Based on 143 frontline employees who took The Breakroom Quiz

76th of 149 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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