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Senior Meta Machine Learning 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 ...

DISCO

Senior Machine Learning Scientist

Austin, TX · On-site

$97K - $124K/yr

Your Impact The Senior Machine Learning Research Scientist is a key contributor to DISCO's machine learning and AI research initiatives, leading the development of advanced algorithms and ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

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 ...

DISCO

Senior Machine Learning Scientist

Austin, TX · On-site

$97K - $124K/yr

Your Impact The Senior Machine Learning Research Scientist is a key contributor to DISCO's machine learning and AI research initiatives, leading the development of advanced algorithms and ...

Avride

Senior / Staff Machine Learning Engineer

Austin, TX

$124K - $171K/yr

Senior / Staff Machine Learning Engineer Austin, TX About the Team Avride develops autonomous vehicle and delivery robot technology, leveraging deep expertise in autonomous systems. With the recent ...

Apple

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

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

PayPal

Machine Learning Engineer

Austin, TX · On-site

Collaborate with senior engineers and data scientists on model deployment. * Conduct experiments and run machine learning tests. * Stay updated with the latest advancements in machine learning.

Indeed

Senior Machine Learning Engineer

Austin, TX

$103K - $142K/yr

Comscore, Total Visits, March 2025) Day to Day As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be ...

Apple

Senior Machine Learning Engineer

Austin, TX

$181K - $318K/yr

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

Apple

Senior Machine Learning Engineer

Austin, TX

$181K - $318K/yr

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

Bumble Inc.

Senior Machine Learning Engineer

Austin, TX

$220K - $250K/yr

As a Senior Machine Learning Engineer, you'll own impactful problems end-to-end-from data exploration through to production deployment, while collaborating closely with Product, Engineering, and Data ...

Avride

Senior / Staff Machine Learning Engineer

Austin, TX

$124K - $171K/yr

About the role We are hiring experienced Machine Learning Engineers across Senior, Staff, and Principal levels. to site onsite in Austin, Texas. Whether you're a strong individual contributor ready ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$116K - $154K/yr

They are seeking an experienced Machine Learning Engineer to join their data science and machine ... and senior management • Genuine intellectual curiosity about commodities markets, global energy ...

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Senior Meta Machine Learning information

Is L7 senior at Google?

L7 at Google is considered a senior-level position, typically involving significant technical expertise and leadership responsibilities. It is often regarded as a senior or staff level role within Google's engineering hierarchy, requiring extensive experience and advanced skills in areas like machine learning or software development.

How much does L7 make at Meta?

An L7 Senior Meta Machine Learning engineer typically earns a base salary ranging from $250,000 to $350,000 annually, with additional compensation such as bonuses and stock options. Total compensation can exceed $400,000 depending on performance and stock grants. These figures are based on industry reports and may vary by location and experience.

What engineer makes $500,000 a year?

Senior Meta Machine Learning engineers can earn $500,000 or more annually, especially with bonuses and stock options in large tech companies. High compensation typically requires advanced skills in deep learning, extensive experience, and a strong track record of impactful projects.

What is the difference between Senior Meta Machine Learning vs Data Scientist?

AspectSenior Meta Machine LearningData Scientist
Required CredentialsMaster's or PhD in CS, ML, or related fields; experience with meta-learning frameworksBachelor's or higher in CS, Statistics, or related fields; proficiency in data analysis
Work EnvironmentResearch-focused teams developing advanced ML models, often in AI companiesData analysis, modeling, and visualization across various industries
Employer & Industry UsageTech firms, AI startups, research institutionsFinance, healthcare, e-commerce, tech companies

While both roles involve machine learning expertise, Senior Meta Machine Learning specialists focus on developing advanced meta-learning algorithms, often in research settings, whereas Data Scientists apply data analysis and modeling techniques across diverse industries. The roles share similar educational backgrounds but differ in focus and application.

How much does a Meta senior machine learning engineer make?

A senior machine learning engineer at Meta typically earns between $150,000 and $200,000 annually, with total compensation including bonuses and stock options often exceeding this range. Compensation varies based on experience, location, and performance, and the role requires strong skills in deep learning, data analysis, and programming in Python or C++.
What are the most commonly searched types of Meta Machine Learning jobs in Texas? The most popular types of Meta Machine Learning jobs in Texas are:
What are popular job titles related to Senior Meta Machine Learning jobs in Texas? For Senior Meta Machine Learning jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Senior Meta Machine Learning jobs in Texas look for? The top searched job categories for Senior Meta Machine Learning jobs in Texas are:
What cities in Texas are hiring for Senior Meta Machine Learning jobs? Cities in Texas with the most Senior Meta Machine Learning job openings:
Senior Meta Machine Learning jobs near you
Infographic showing various Senior Meta Machine Learning job openings in Texas as of June 2026, with employment types broken down into 67% Full Time, 25% Part Time, 4% Temporary, and 4% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution.
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Ascentt

Plano, TX • On-site

$100K - $137K/yr

Full-time

Posted 14 days ago

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.

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