ZipRecruiter

Log In

1

Lead Machine Learning Engineer Jobs in Texas (NOW HIRING)

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

Senior Machine Learning Engineer Location: Ann Arbor, Michigan Experience Level: 7+ Years Department: Data Science / Engineering Employment Type: Full-time About the Role: We are looking for an ...

Intuit

Staff Machine Learning Engineer

Plano, TX · On-site

Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI scientists and machine learning engineers to create AI-powered experiences. You'll be expected to help ...

Intuit

Staff Machine Learning Engineer

Plano, TX

Overview Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI scientists and machine learning engineers to create AI-powered experiences. You'll be expected ...

Oxy

AI Machine Learning Engineer

Houston, TX · On-site

We are looking for an experienced and innovative individual contributor to fill the position of AI Machine Learning Engineer within our AI Center of Excellence group based in Houston, TX. The ...

Q2

Machine Learning Engineer

Austin, TX · Hybrid

Summary The Machine Learning Engineer designs and evolves enterprise AI systems and architectures that enable scalable, secure, and high-impact adoption across the organization. This role defines end ...

Bumble Inc.

Staff Machine Learning Engineer

Austin, TX · On-site

Bumble Inc. is dedicated to creating healthy and equitable relationships through their products, and they are seeking a Staff Machine Learning Engineer to lead the development of advanced machine ...

Q2 Software, Inc.

Machine Learning Engineer

Austin, TX · On-site

Summary The Machine Learning Engineer designs and evolves enterprise AI systems and architectures that enable scalable, secure, and high-impact adoption across the organization. This role defines end ...

CVS Health

Machine Learning Engineer

Irving, TX · On-site +1

$96K - $144K/yr

Caremark LLC, a CVS Health company, is hiring for the following role in Irving, TX: Machine Learning Engineer to Design, develop, and implement enterprise ML products and platforms for data ...

CVS Health

Machine Learning Engineer

Irving, TX · On-site +1

$96K - $144K/yr

Aetna Resources, LLC., a CVS Health company, is hiring for the following role in Irving, TX: Machine Learning Engineer to build, deploy, and monitor artificial intelligence (AI)/machine learning (ML ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing ...

Vitol

Senior Machine Learning Engineer

Houston, TX

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing ...

Vanguard

Manager, Machine Learning Engineer

Dallas, TX

$101K - $133K/yr

Leads a team of Machine Learning Engineers responsible for designing, building, deploying, and ... To lead through product and services that transform our clients' lives. To learn and develop our ...

Vitol

Senior Machine Learning Engineer

Houston, TX

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing ...

next page

Showing results 1-20

All JobsLead Machine Learning Engineer JobsLead Machine Learning Engineer Jobs in Texas

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 Jun 28, 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.

What is a $900,000 AI job?

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

Which 3 jobs will survive AI?

Lead Machine Learning Engineers are likely to continue to be in demand as they develop, implement, and oversee AI systems, requiring advanced skills in programming, data analysis, and domain expertise. Jobs that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, and skilled trades—are also expected to persist despite AI advancements. These roles typically require emotional intelligence, adaptability, and specialized knowledge that AI cannot easily replicate.

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 engineers make $500,000?

Senior-level 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 $500,000 or more annually. Compensation may include base salary, bonuses, and stock options, especially in competitive markets or executive roles.
What are popular job titles related to Lead Machine Learning Engineer jobs in Texas? For Lead Machine Learning Engineer jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Lead Machine Learning Engineer jobs in Texas look for? The top searched job categories for Lead Machine Learning Engineer jobs in Texas are:
Lead Machine Learning Engineer jobs near you
Infographic showing various Lead Machine Learning Engineer job openings in Texas as of June 2026, with employment types broken down into 1% As Needed, 93% Full Time, 4% Part Time, 1% Contract, and 1% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $115,324 per year, or $55.4 per hour.
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Ascentt

Plano, TX • On-site

$100K - $137K/yr

Full-time

Posted 22 days ago

Key responsibilities

  • Design, develop, and deploy scalable machine learning models for real-world business problems using structured and unstructured data.

  • Analyze large datasets using PySpark and other distributed computing frameworks to extract insights and prepare features for ML pipelines.

  • Own end-to-end ML pipelines from data ingestion, preprocessing, training, validation, tuning, and deployment.

Job description

Ascentt is building cutting-edge data analytics & AI/ML solutions for global automotive and manufacturing leaders. We turn enterprise data into real-time decisions using advanced machine learning and GenAI. Our team solves hard engineering problems at scale, with real-world industry impact. We're hiring passionate builders to shape the future of industrial intelligence.
Job Title: Senior Machine Learning Engineer
Location: Ann Arbor, Michigan
Experience Level: 7+ Years
Department: Data Science / Engineering
Employment Type: Full-time
About the Role:
We are looking for an experienced Senior Machine Learning Engineer with deep expertise in statistical and machine learning techniques, large-scale data processing, and model deployment in cloud environments. The ideal candidate will be a self-starter with strong problem-solving skills and hands-on experience in building and deploying ML models using big data technologies like PySpark and cloud platforms like Amazon SageMaker.
Key Responsibilities:
  • Design, develop, and deploy scalable machine learning models for real-world business problems using structured and unstructured data.
  • Analyze large datasets using PySpark and other distributed computing frameworks to extract insights and prepare features for ML pipelines.
  • Apply a wide range of statistical, machine learning, and deep learning techniques, including but not limited to regression, classification, clustering, time-series forecasting, and NLP.
  • Own end-to-end ML pipelines from data ingestion, preprocessing, training, validation, tuning, and deployment.
  • Utilize Amazon SageMaker or similar platforms for building, training, and deploying models in a production-grade environment.
  • Collaborate closely with data engineers, data scientists, and product teams to integrate models with business workflows.
  • Monitor and improve model performance, scalability, and reliability in production.
  • Contribute to setting up and maintaining the ML environment and tooling (including environment configuration, CI/CD pipelines for ML, model versioning, etc.).

Required Qualifications:
  • 7+ years of experience in machine learning, data science, or related fields.
  • Strong programming skills in Python with experience in ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch).
  • Hands-on experience with PySpark for big data processing and model development.
  • Proficient in building models on large-scale datasets (terabytes to petabytes).
  • Solid understanding of statistical analysis, probability, hypothesis testing, and experimental design.
  • Experience with Amazon SageMaker (or similar cloud-based ML platforms).
  • Strong knowledge of ML Ops practices including version control, model monitoring, and retraining strategies.
  • Familiarity with containerization (Docker) and CI/CD practices for ML projects is a plus.
  • Excellent communication skills and the ability to clearly explain complex concepts to non-technical stakeholders.

Preferred Qualifications:
  • Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative discipline.
  • Experience with workflow orchestration tools (e.g., Airflow, Kubeflow).
  • Prior experience in domains like Manufacturing, finance, healthcare, or e-commerce is a plus.

Apply