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Machine Learning Jobs in Houston, PA (NOW HIRING)

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Machine Learning information

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$23.4K

$39.1K

$80.9K

How much do machine learning jobs pay per year?

As of Jun 16, 2026, the average yearly pay for machine learning in Houston, PA is $39,138.00, according to ZipRecruiter salary data. Most workers in this role earn between $29,900.00 and $42,300.00 per year, depending on experience, location, and employer.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning engineer, AI research director, or chief AI officer, often requiring advanced skills in deep learning, data analysis, and programming. These roles usually involve leadership responsibilities, strategic planning, and may require extensive experience and specialized certifications, with compensation reflecting the seniority and impact of the role.

What is a Machine Learning job?

A Machine Learning job involves developing algorithms and models that enable computers to learn from data and make predictions or decisions without explicit programming. Professionals in this field work with large datasets, design and train machine learning models, and optimize them for performance and accuracy. Roles often require knowledge of programming languages like Python or R, experience with frameworks like TensorFlow or PyTorch, and an understanding of statistics and data science principles. Machine learning engineers and data scientists collaborate with software developers and domain experts to build AI-driven solutions for various industries.

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 of $500,000 or more, 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.

What are some typical day-to-day responsibilities in a Machine Learning role?

As a machine learning professional, your daily tasks may include data preprocessing, developing and training models, evaluating performance metrics, and experimenting with algorithms to optimize results. You’ll often collaborate closely with data scientists, software engineers, and business stakeholders to align technical solutions with organizational goals. Regular activities can also involve deploying models to production, monitoring performance, and troubleshooting any issues that arise post-deployment. Staying up to date with recent ML research and participating in team discussions or code reviews are also common parts of the job.

What jobs can I get with machine learning?

With a background in machine learning, you can pursue roles such as machine learning engineer, data scientist, AI researcher, or data analyst. These jobs typically require skills in programming languages like Python or R, knowledge of algorithms, and experience with tools like TensorFlow or PyTorch.

What are the key skills and qualifications needed to thrive in the Machine Learning position, and why are they important?

To thrive in Machine Learning, you need a solid background in mathematics, statistics, programming (especially Python or R), and a formal degree in computer science, data science, or a related field. Experience with popular ML frameworks (such as TensorFlow, PyTorch, or Scikit-learn), version control, and relevant certifications like AWS Certified Machine Learning are highly valued. Strong problem-solving skills, curiosity, clear communication, and the ability to work both independently and within multidisciplinary teams make candidates stand out. These skills and qualities are essential for developing robust models, staying updated with technology advancements, and collaborating effectively on complex projects.

Which 3 jobs will survive AI?

Machine learning engineers, data scientists, and AI ethics specialists are likely to continue thriving as AI advances, due to their expertise in developing, managing, and overseeing AI systems. These roles require specialized skills, critical thinking, and understanding of complex algorithms that are difficult to fully automate. Continuous learning and certification in relevant tools like Python, TensorFlow, or ethical frameworks will support job security in these fields.
What cities near Houston, PA are hiring for Machine Learning jobs? Cities near Houston, PA with the most Machine Learning job openings:
Machine Learning jobs near you
Infographic showing various Machine Learning job openings in Houston, PA as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $39,138 per year, or $18.8 per hour.
Machine Learning Operations Engineer

Machine Learning Operations Engineer

CGI

Pittsburgh, PA

$62K - $139K/yr

Other

Retirement, PTO

Posted 8 days ago

CGI rating

7.2

Company rating: 7.2 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

112th of 204 rated it services

Job description

Machine Learning Operations Engineer

We are seeking an experienced MLOps Engineer with strong expertise in Python and big data technologies to join our team. This role focuses on operational excellence, including optimizing feature engineering pipelines and maintaining machine learning models in production environments. Desired candidate will work closely with platform and data science teams to ensure scalable, reliable, and high-performance ML workflows using existing frameworks.

This position will be performed onsite five days a week from any our client sites in Dallas, Strongsville, OH/Pittsburg, PA. Future duties and responsibilities include:

  • Optimize and maintain large-scale feature engineering pipelines using PySpark, Pandas, and PyArrow on Hadoop-based infrastructure.
  • Refactor and modularize ML codebases to enhance reusability, maintainability, and performance.
  • Collaborate with platform teams on compute capacity planning, resource allocation, and system upgrades.
  • Integrate with existing model serving frameworks to support testing, deployment, and rollback processes.
  • Monitor and troubleshoot production ML pipelines, ensuring high reliability, low latency, and cost efficiency.
  • Contribute to internal ML platforms by sharing insights, proposing improvements, and documenting best practices.
  • Build near real-time ML pipelines using Kafka and Spark Streaming.
  • Work with AWS and SageMaker MLOps ecosystem.

Required qualifications to be successful in this role include:

  • 6+ years of experience in software engineering, data engineering, or MLOps roles.
  • Strong programming expertise in Python, with hands-on experience in Pandas, PySpark, and PyArrow.
  • Deep understanding of the Hadoop ecosystem, distributed computing, and performance tuning.
  • Experience with CI/CD pipelines and best practices in ML environments.
  • Hands-on experience with monitoring tools for ML pipeline health and performance.
  • Strong collaboration skills with experience working in cross-functional teams (platform, data science, engineering).
  • Experience contributing to or building internal MLOps frameworks/platforms.
  • Familiarity with SLURM clusters or other distributed job schedulers.
  • Exposure to Kafka, Spark Streaming, or other real-time data processing technologies.
  • Understanding of ML lifecycle management, including versioning, deployment, and drift detection.

Compensation range for this role in the U.S. is $62,900.00 - $139,300.00. CGI's benefits are offered to eligible professionals on their first day of employment to include competitive compensation, comprehensive insurance options, matching contributions through the 401(k) plan and the share purchase plan, paid time off for vacation, holidays, and sick time, paid parental leave, learning opportunities and tuition assistance, wellness and well-being programs.

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