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Senior Machine Learning Engineer Jobs in Houston, TX

Senior Machine Learning Data Scientist

Houston, TX · On-site

$102 - $156.40/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

As our Senior Machine Learning Data Scientist, you will support the development, delivery, and ... This includes building models across the full lifecycle--from feature engineering, training, tuning ...

Lead Machine Learning Engineer

Houston, TX · On-site +1

$97K - $128K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI, you will be responsible for architecting, building, and deploying intelligent features to our VIP ...

Lead Machine Learning Engineer

Houston, TX · Remote

$104K - $138K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI, you will be responsible for architecting, building, and deploying intelligent features to our VIP ...

Lead Machine Learning Engineer

Houston, TX · On-site +1

$97K - $128K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI, you will be responsible for architecting, building, and deploying intelligent features to our VIP ...

Senior AI Engineer

Houston, TX · On-site

$99K - $137K/yr

Design, develop, and deploy advanced AI and machine learning models to solve complex business ... Mentor junior engineers and provide technical guidance on AI best practices, model development, and ...

Showing results 21-40

Senior Machine Learning Engineer information

See Houston, TX salary details

$56.8K

$120.9K

$175.2K

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

As of Aug 15, 2026, the average yearly pay for senior machine learning engineer in Houston, TX is $120,858.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,800.00 and $137,000.00 per year, depending on experience, location, and employer.

What are some common challenges senior machine learning engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What does a senior machine learning engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

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

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

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

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Houston, TX?

The most popular types of Machine Learning Engineer jobs in Houston, TX are:

What cities near Houston, TX are hiring for Senior Machine Learning Engineer jobs?

Cities near Houston, TX with the most Senior Machine Learning Engineer job openings:

Infographic showing various Senior Machine Learning Engineer job openings in Houston, TX as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 18% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $120,858 per year, or $58.1 per hour.

Senior Machine Learning Data Scientist

ENGIE Group

Houston, TX • On-site

$102 - $156.40/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 5 days ago


Job description

As our Senior Machine Learning Data Scientist, you will support the development, delivery, and continuous improvement of forecasting processes and models for ENGIE’s U.S. power supply business. Working under the guidance of the Portfolio & Load Analytics Manager, you will collaborate closely with portfolio managers, risk, IT, and other stakeholders to ensure forecasting outputs are accurate, timely, and aligned with operational needs.

In this role, you will leverage rigorous data collection, validation, and analysis to improve forecast performance and support portfolio management, hedging strategies, and risk management activities across U.S. power markets.

This position is based in Houston, TX, and reports to the Portfolio & Load Analytics Manager.

  • You will be actively involved in the design, implementation, and continuous improvement of forecasting tools, models, and methodologies, while helping build a modern forecasting platform for the US power market. Your role will include validating forecast inputs and outputs, monitoring model performance from a data science standpoint, and ensuring model drift and forecast quality remain under control over time. You will also work cross-functionally within the broader forecasting community and with forecasting teams in other countries to promote knowledge sharing, consistency, and the cross-pollination of ideas and best practices
  • You will be responsible not only for the technical development of forecasting solutions, but also for ensuring their operational reliability and relevance to business needs. This includes building models across the full lifecycle—from feature engineering, training, tuning, and execution to validation, monitoring, and ongoing refinement—while maintaining strong software engineering standards that deliver dependable, production-grade forecasts. Because these forecasts are used to support commercial decisions across ENGIE’s US power business, reliability, traceability, and robustness are essential parts of the role.
  • In addition to model development, you will provide scientific expertise for bespoke analyses and contribute to the continuous improvement of forecasting practices, performance measurement, and platform capabilities. A strong understanding of forecasting methodology, model governance, and production-quality software development is essential to succeed in this role, along with the ability to translate complex analytical outputs into practical business value for stakeholders across the organization.
What You’ll Bring
  • You hold a Bachelor’s degree in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, Finance, or Economics, or a related field. In lieu of a degree, we will consider a combination of relevant experience that demonstrates strong quantitative rigor and practical business acumen
  • You have the technical expertise to build, analyze, and productionize forecasting models, along with the communication skills needed to align diverse stakeholders around a clear and informed point of view
  • A minimum of five (5) years of experience building and deploying forecasting models and data pipelines using Python and SQL, with ownership of production deliverables
  • You hold a strong foundation in probability, statistics, data science, and machine learning, with practical experience in time series forecasting
  • You have advanced proficiency in Python, SQL, Git, and modern data platforms such as Databricks and Spark, with the ability to build scalable data pipelines and automate workflows.
  • You are knowledgeable in developing and deploying forecasting models, including regression, time series, and machine learning techniques, with experience improving forecast accuracy and backcasting performance
  • You have experience designing and maintaining end-to-end forecasting systems including data ingestion, feature engineering, model training, hyperparameter tuning, deployment, and performance monitoring
  • You are knowledgeable in energy markets, load forecasting, or commodity trading, and understand how market dynamics and regulatory changes impact forecasting outputs
  • You are an effective communicator who can translate complex analytical insights into clear recommendations for both technical and non-technical stakeholders, including portfolio managers, traders, and risk teams
  • You have strong analytical and problem-solving skills, with the ability to manage multiple priorities, work independently, and deliver accurate, high-quality results in a fast-paced environment
  • This role is eligible for our hybrid work policy
  • Must be willing and able to comply with all ENGIE ethics and safety policies
Compensation

Salary Range: $102,000 – $156,400 USD annually

This represents the average expected pay range for a qualified candidate.

ENGIE complies with all federal, state, and local minimum wage laws. Actual salary offered may vary depending on geography, experience, education, internal pay alignment, or other bona fide factors.

In addition to base pay, this position is eligible for a competitive bonus / incentive plan.

Your Talent Acquisition Partner can share more specific information regarding the benefits or the salary for the position based on the work location.

At ENGIE, we take your well-being seriously. Our comprehensive benefits package includes options for medical, dental, vision, life insurance, employer-paid short-term and long-term disability insurance, ESPP, generous paid time off including wellness days, holidays and leave programs. We also help you plan for retirement by offering a 401(k) Retirement Savings Plan with a company match. But that's not all – we're dedicated to the health and happiness of your entire family, offering supplemental benefits for full time employees that enhance emotional and physical well-being through all stages of life from family forming to caregiver benefits. Explore our benefits package to see how we can support you. Learn more .

Why ENGIE?

ENGIE North America isn’t just participating in the Zero-Carbon Transition, we’re leading it! Join us as we develop energy that is renewable, efficient, and accessible to everyone.

ENGIE is proud to be an equal opportunity workplace, and we are firmly committed to creating an inclusive workplace for all employees. We are committed to providing employees with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, disability, veteran status, or other legally protected status.

If you need assistance with this application or a reasonable accommodation due to a disability, you may contact us at ENGIENA-ENGIEHR@engie.com. This email address is reserved for individuals with disabilities in need of assistance and is not a means of inquiry regarding positions or application status.

We are unable to sponsor or take over sponsorship of an employment visa for this role at any time.

The safety of our employees is our number one priority. All employees at ENGIE have both a duty and the authority to STOP WORK if unsafe acts are observed.

Business Unit: Supply & Energy Management

Division: BP B2B US

Company Name: ENGIE North America

Minimum Base Salary:

Maximum Base Salary:

Pay Basis:

Why this matters to us

Our organisation is an equal opportunity employer and is committed to fostering a diverse and inclusive workplace. We offer reasonable accommodations upon request for individuals with disabilities.

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