ZipRecruiter

Log In

1

Machine Learning Engineer Python Jobs in Irving, TX

AppFolio

Sr. Machine Learning Engineer

Richardson, TX · Remote

$94.30K - $129.50K/yr

Who we are looking for We're seeking a Sr Machine Learning Engineer to play a critical role in ... Strong software engineering expertise with languages such as Python, Go, Ruby, or JavaScript * Deep ...

AppFolio

Sr. Machine Learning Engineer

Richardson, TX · Remote

$94.30K - $129.50K/yr

Who we are looking for We're seeking a Sr Machine Learning Engineer to play a critical role in ... Strong software engineering expertise with languages such as Python, Go, Ruby, or JavaScript * Deep ...

Vanguard

Machine Learning Engineer, Specialist

Dallas, TX · On-site

$113.30K - $136K/yr

Performs the development and programming of machine learning integrated software algorithms to structure, analyze, and leverage data in a production environment. Leverages detailed understanding of ...

Cisco

Principal Machine Learning Engineer

Dallas, TX · On-site

The Principal Machine Learning Engineer will define the vision for AI across platforms, lead the ... in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) • Experience translating ...

New

next page

Showing results 1-20

People also search for

All JobsMachine Learning Engineer Python JobsMachine Learning Engineer Python Jobs in Irving, TX

Machine Learning Engineer Python information

See Irving, TX salary details

$22.1K

$134.4K

$194.4K

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

As of May 30, 2026, the average yearly pay for machine learning engineer python in Irving, TX is $134,407.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,100.00 and $158,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer Python, and why are they important?

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 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 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 are popular job titles related to Machine Learning Engineer Python jobs in Irving, TX? For Machine Learning Engineer Python jobs in Irving, TX, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Python jobs in Irving, TX look for? The top searched job categories for Machine Learning Engineer Python jobs in Irving, TX are:
What cities near Irving, TX are hiring for Machine Learning Engineer Python jobs? Cities near Irving, TX with the most Machine Learning Engineer Python job openings:
Machine Learning Engineer Python jobs near you
Principal Machine Learning Engineer (MLE)

Principal Machine Learning Engineer (MLE)

Equinix

Dallas, TX • On-site

Full-time

Posted 2 days ago

Job description

Job Summary:
Equinix is the world’s digital infrastructure company®, enabling innovations that enrich our work, life, and planet. As a Principal Machine Learning Engineer, you will design, build, deploy, and scale machine learning and generative AI systems for real-world products, collaborating with teams to translate advanced capabilities into reliable solutions across multi-cloud environments.
Responsibilities:
• Design, develop, and deploy machine learning and Large Language Model (LLM)–based solutions for production use cases
• Collaborate with Generative AI Center of Excellence leaders and business stakeholders to evaluate buy vs. build decisions for generative AI applications
• Develop end-to-end ML pipelines, covering data ingestion, feature engineering, model training, evaluation, deployment, and monitoring
• Architect and implement LLM-powered systems that integrate agents and services across multiple cloud platforms into a unified solution
• Optimize ML workflows for performance, scalability, reliability, and cost efficiency in cloud environments (GCP, Azure, AWS)
• Implement and maintain MLOps best practices, including CI/CD, model versioning, experiment tracking, and automated retraining
• Work extensively with deep learning frameworks such as PyTorch and TensorFlow
• Containerize ML services and deploy them using Docker, Kubernetes, App Engine, or virtual machines
• Apply strong knowledge of NLP fundamentals, including transformers, attention mechanisms, embeddings, and text preprocessing
• Deploy and manage models in production, conduct A/B testing, and measure performance improvements using statistical methods
• Develop features, run experiments, analyze results, and translate insights into actionable improvements
• Build and deploy classical ML models (regression, classification, clustering), NLP applications (sentiment analysis, summarization, Q&A, chatbots, information retrieval), and computer vision solutions (image classification, object detection, segmentation using models such as YOLOv7, DDRNet, RFTM with datasets like COCO and Cityscapes)
Qualifications:
Required:
• PhD with 5+ years, Master’s with 6+ years, or Bachelor’s with 7+ years of experience in Machine Learning, Computer Science, Data Science, or a related field
• Strong proficiency in Python for machine learning and production systems
• Solid understanding of software engineering fundamentals, system design, and design patterns
• Hands-on experience with at least one major cloud platform (GCP, Azure, or AWS)
• Experience building and deploying production-grade ML systems
• Strong communication skills with the ability to explain technical concepts and results to both technical and non-technical stakeholders
• Excellent time management, collaboration, and organizational skills
Company:
Equinix is an internet company that provides data center services for companies, businesses, and organizations. Founded in 1998, the company is headquartered in Redwood City, USA, with a team of 10001+ employees. The company is currently Late Stage.

Apply