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Machine Learning Engineer Python Jobs in La Porte, TX

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 ... Fluency in Python for both data science and engineering purposes: clean, modular, well-documented ...

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 ... Fluency in Python for both data science and engineering purposes: clean, modular, well-documented ...

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 ... Fluency in Python for both data science and engineering purposes: clean, modular, well-documented ...

Beth Page tech

Senior Machine Learning Engineer

Houston, TX · On-site

$99K - $137K/yr

Senior Machine Learning Engineer Location: Houston, TX Environment: Standard, 5-days onsite : Must ... Python mastery (TensorFlow/PyTorch, Transformers, Scikit-learn). * Cloud (AWS) and containerization ...

Crowe LLP

Machine Learning Engineer

Houston, TX · On-site

$62K - $100K/yr

Expertise in Python programming and experience with version control systems like Git. * Strong ability to work independently and execute tasks efficiently in a dynamic environment. * Proficiency in ...

NobleAI

Lead Machine Learning Engineer

Houston, TX · On-site +1

$97K - $128K/yr

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI ... Strong programming proficiency in Python (5+ years) and deep experience with core ML/NLP libraries ...

NobleAI

Lead Machine Learning Engineer

Houston, TX · On-site +1

$97K - $128K/yr

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI ... Strong programming proficiency in Python (5+ years) and deep experience with core ML/NLP libraries ...

NobleAI

Lead Machine Learning Engineer

Houston, TX · Remote

$104K - $138K/yr

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI ... Strong programming proficiency in Python (5+ years) and deep experience with core ML/NLP libraries ...

Bespoke Labs

Machine Learning Engineer

Houston, TX

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Bespoke Labs

Machine Learning Engineer

Houston, TX · On-site

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

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All JobsMachine Learning Engineer Python JobsMachine Learning Engineer Python Jobs in La Porte, TX

Machine Learning Engineer Python information

See La Porte, TX salary details

$21.6K

$131.7K

$190.5K

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

As of Sep 15, 2026, the average yearly pay for machine learning engineer python in La Porte, TX is $131,675.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,000.00 and $154,800.00 per year, depending on experience, location, and employer.

What is a machine learning engineer python?

A Machine Learning Engineer Python is a professional who uses the Python programming language to design, build, and deploy machine learning models and systems. They work with large datasets, develop algorithms, and use Python libraries such as TensorFlow, scikit-learn, and PyTorch to solve complex problems. Their responsibilities also include preprocessing data, training models, evaluating performance, and integrating solutions into production environments. Machine Learning Engineers often collaborate with data scientists, software engineers, and business stakeholders to create scalable and efficient machine learning applications.

What are the key skills and qualifications needed to thrive as a machine learning engineer python?

To thrive as a Machine Learning Engineer Python, you need a solid background in computer science, statistics, and mathematics, along with proficiency in Python programming and machine learning concepts. Familiarity with frameworks such as TensorFlow, PyTorch, Scikit-learn, and experience with cloud platforms or MLOps tools are highly valued, as are certifications like Google Professional Machine Learning Engineer. Strong problem-solving abilities, communication skills, and a collaborative mindset help set you apart in this field. These skills enable engineers to design, implement, and deploy effective machine learning solutions that address real-world challenges in dynamic, team-oriented environments.

What are some common challenges faced by machine learning engineers working with Python, and how can they be addressed?

Machine Learning Engineers using Python often encounter challenges such as managing large datasets, ensuring efficient model deployment, and maintaining reproducibility of experiments. Handling data pipelines and model versioning can be complex, especially as projects scale. To address these issues, engineers typically use tools like Pandas and Dask for data handling, Docker for containerization, and MLflow or DVC for tracking experiments and models. Collaborating closely with data engineers, software developers, and product teams is also essential to streamline workflows and ensure models are production-ready.

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

AspectMachine Learning Engineer PythonData Scientist
Required CredentialsBachelor's/Master's in CS, Data Science, or related; Python skills; ML certificationsBachelor's/Master's in Statistics, CS, or related; Python/R skills; Data analysis certifications
Work EnvironmentDevelops scalable ML models, deploys algorithms, collaborates with engineering teamsAnalyzes data, builds models, interprets results, communicates insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research institutions

While both roles require Python proficiency and data skills, Machine Learning Engineers focus on building and deploying scalable ML models, whereas Data Scientists analyze data and generate insights. The roles often overlap but differ in their primary focus and responsibilities.

What cities near La Porte, TX are hiring for Machine Learning Engineer Python jobs?

Cities near La Porte, TX with the most Machine Learning Engineer Python job openings:

Senior Machine Learning Engineer

Houston, TX • On-site

Reach Velocity - Emerging Technology ?? ??
See more jobs at Reach Velocity - Emerging Technology ?? ??external

$117K - $154K/yr

Other

Posted 2 days ago

New

Job description

Our client is a large global energy and commodities business operating across international markets.

Technology, data science and machine learning play an increasingly important role across the organisation, and the business is continuing to invest in ML and Generative AI capabilities.

Due to continued growth, they are looking for an experienced Machine Learning Engineer to join their Houston-based Data Science and Machine Learning team.

The Role

This is a hands-on position with exposure across the full machine learning lifecycle.

You will work closely with data scientists, ML specialists, software engineers and commercial teams to identify problems, develop solutions and deploy production-grade machine learning applications.

Projects span machine learning, time-series forecasting, NLP and Generative AI, with the opportunity to work on commercially important problems involving pricing, supply and demand, operational optimisation and other business-critical applications.

You will also play an important role in the continued development and adoption of the organisation's internal Generative AI platform.

Responsibilities
  • Design, develop and deploy end-to-end machine learning and data science solutions.
  • Build production ML systems from data ingestion and feature engineering through model deployment and monitoring.
  • Develop and extend internal GenAI and LLM applications, including integrations, data connectors and prompt engineering.
  • Apply techniques including time-series forecasting, NLP, classification and Generative AI to real-world commercial problems.
  • Build robust, well-tested production-quality Python code.
  • Contribute to ML pipelines, data orchestration and model-serving infrastructure.
  • Integrate ML outputs into existing applications, dashboards and business workflows.
  • Work directly with commercial and operational stakeholders to identify valuable ML opportunities.
  • Communicate model results, assumptions and limitations clearly to non-technical stakeholders.
  • Participate in code reviews, experimentation and technical decision-making.
What We're Looking For
  • 5+ years' industry experience developing and deploying machine learning or statistical models.
  • Strong Python skills for both data science and software engineering.
  • Experience delivering end-to-end ML solutions into production.
  • Strong understanding of supervised and unsupervised learning.
  • Experience with time-series modelling.
  • Experience with NLP, LLMs and Generative AI applications.
  • Experience with frameworks such as PyTorch, scikit-learn and Transformers.
  • Cloud experience, preferably AWS.
  • Experience with modern MLOps practices including Docker/Kubernetes, CI/CD, model deployment and monitoring.
  • Experience with data orchestration tools such as Airflow or Dagster.
  • Strong analytical and problem-solving ability.
  • Comfortable working directly with both technical and non-technical stakeholders.

A Master's degree or equivalent in Computer Science, Statistics, Mathematics, Data Science or another quantitative discipline is preferred.

Experience within energy, commodities trading or financial markets would be beneficial but is not essential.

Additional experience with any of the following would also be valuable:

  • Financial or trading-related time-series modelling
  • Econometric approaches such as ARIMA or cointegration
  • Dash, Streamlit or similar interactive applications
  • Cloud-based ETL/ELT pipelines
The Opportunity

This is an opportunity to join an experienced ML and Data Science team within a large international organisation where machine learning is being applied to complex, commercially important problems.

You will have significant ownership over your work, direct exposure to business stakeholders and the opportunity to help shape how ML and Generative AI are adopted across the organisation.

Location:

Houston, TX

Working Pattern:

5 days per week in the office

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