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Machine Learning Engineer Python Jobs in Irving, TX

Cambium Learning Group

Software Engineer / Python

Dallas, TX · On-site +1

$46.25 - $63.75/hr

Train machine learning models, analyze performance metrics, and communicate results with visual and ... Extensive experience with Python and python frameworks (e.g. CherryPy, Bottle, Flask, Django)

Cisco

Principal Machine Learning Engineer

Dallas, TX · On-site

$291.50K - $369.10K/yr

Partner with executive leadership, engineering, product, and data science teams to ensure AI ... Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) * Experience ...

New

Resolve Tech Solutions

Senior ML Engineer

Addison, TX

$101.20K - $138.90K/yr

Proficiency in programming languages such as Python, Java, or Scala. Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn. Strong understanding of ...

Resolve Tech Solutions

Senior ML Engineer

Addison, TX · On-site

$101.20K - $138.90K/yr

... machine learning, data science, or a related field. • Proficiency in programming languages such as Python, Java, or Scala. • Experience with machine learning frameworks and libraries such as ...

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Machine Learning Engineer Python information

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$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
Senior Staff Machine Learning Engineer - IC5 (MCHLRN - Machine Learning)

Senior Staff Machine Learning Engineer - IC5 (MCHLRN - Machine Learning)

PowerSchool Group LLC

Dallas, TX • On-site

$121.20K - $159.80K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 7 days ago

PowerSchool rating

9.2

Company rating: 9.2 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

12th of 183 rated software companies

Job description

Overview
At PowerSchool, we are a dedicated team of innovators guided by our shared purpose of powering personalized education for students around the world. From the central office to the classroom to the home, PowerSchool supports the entire educational ecosystem as the global leader of cloud-based software for K-12 education. Our employees make it all possible, and a career with us means you're joining a successful team committed to engaging, empowering, and improving the K-12 education experience everywhere.
Team Overview
Our Research & Development (R&D) team is the technical talent at the heart of our product suite, overseeing the product development lifecycle from concept to delivery. From engineering to quality assurance to data science, the R&D team ensures our customers seamlessly use our products and can depend on their consistency.
This position, under the general direction of the Lead and/or Manager, Machine Learning Engineering, will be responsible for technical and development support for our award-winning K-12 software. This role will help in all AI/Generative AI/Agents products in the areas of engineering, data, deployment and infrastructure.
Responsibilities
Essential duties and responsibilities include the following. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions
  • Uses Generative AI models (GPT4, Claude, Gemini), other LLMs, Agents and LangChains, CrewAI, Strands to build different AI, Agents driven intelligent solutions
  • Experience in building GenAI based solution in auto-pilot or co-pilot mode which run in production at scale
  • Experience in building Responsible AI guardrails and metrics around traditional AI or Gen AI models
  • Familiar with latest Gen AI, Agent based products and AI coding tools in the market
  • Fundamental understanding of NLP, transformer, embedding space and evaluation metrics
  • Design and implement finetuning SLMs, Core Machine learning models and data ingestion pipelines
  • Experience in dealing with "messy" enterprise data and building ETL transformations to facilitate more effective AI decision-making
  • Experience in building software products used in production
  • Create and maintain optimal data pipeline architecture by assembling large, complex data sets to meet functional and non-functional business requirements
  • Support the building of machine learning, data platforms, and infrastructure required for optimal data extraction, transformations, and loading of data from a wide variety of data sources
  • Work with architecture, data, and design teams to assist with data related technical issues and support data infrastructure needs
  • Deploy ML models in AWS environment specifically in AWS Sage Maker environment
  • Perform root cause analysis for production issues where the root cause is in infrastructure, environment, configuration, or deployment routines; understand when to escalate to product development teams; remediate root causes and implement preventative actions
  • Establish standards and practices around MLOps, including governance, compliance, and data security
  • Experience with AI or Agent driven complex ETL generation and data transformation preferred

Qualifications
To be considered for and to perform this job successfully, an individual must be able to perform each essential duty and responsibility satisfactorily. The requirements listed below are representative of the knowledge, skill and/or ability required.
  • Qualifications include:
    • You're a highly technical research engineer with a strong understanding of the latest advancements in AI, especially GenAI - LLMs and Agents
    • You have 5+ years of professional experience in software engineering, GenAI, machine learning, or applied research, with a proven ability to drive high-impact AI initiatives end to end.
    • Strong working knowledge of deep learning, machine learning and statistics
    • Some experience in complex SQLs and ETL transformations
    • Experience related to AWS services such as SageMaker, Bedrock, EMR, S3, OpenSearch Service, Step Functions, Lambda, and EC2
    • Hands on experience with deep learning (e.g., CNN, RNN, LSTM, Transformer), machine learning, CV, GNN, or distributed training
    • Strong communication skills, with attention to detail and ability to convey rigorous mathematical concepts and considerations to non-experts
    • Demonstrated ability to design, implement, and scale machine learning workflows (ML OPs); including deployment and delivery of production-ready model APIs
    • Proficiency with at least one machine learning lifecycle platform (Sagemaker, MLFlow, TensorFlow, etc.), orchestration platform (Airflow, Dagster, etc.) and data platform like SnowFlake/DataBricks
    • You have a track record of implementing cutting-edge research into robust, scalable, and well-tested code.
    • You bring a strong engineering mindset and write clean, efficient code that performs reliably in production.
    • 3+ years experience with AWS or other public cloud platforms (GCP, Azure, etc.)
    • Excellent verbal and written communication skills.
    • Experience with Infrastructure-as-Code tools and frameworks
    • Master's degree in computer science, data science, mathematics, or a related field.

Compensation & Benefits
Compensation & Benefits
PowerSchool offers the following benefits:
  • Comprehensive Insurance Coverage (including Medical, Dental, Vision, Pharmacy benefits, Life Insurance and AD&D)
  • Flexible Spending Accounts and Health Savings Accounts
  • Short-Term Disability and Long-Term Disability
  • Comprehensive 401(k) plan
  • Generous Parental Leave
  • Unrestricted paid time off (known as Discretionary Time Off - DTO)
  • Wellness Program, including ClassPass & Employee Assistance Program
  • Tuition Reimbursement
  • Optional Benefits: Pet Insurance, Identity Theft Protection, Student Debt Repayment Program and Prepaid Legal coverage

A reasonable estimate of the base compensation range for this position is $159,000 - $198,700 USD. This compensation range is specific to the United States and it incorporates many factors including but not limited to an applicant's skills and prior relevant experience and training; licensures, degrees, and certifications; internal equity; internal pay ranges; and market data/range parameters.
EEO Commitment
EEO Commitment
PowerSchool is committed to a diverse and inclusive workplace. PowerSchool is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. Our inclusive culture empowers PowerSchoolers to deliver the best results for our customers. We not only celebrate the diversity of our workforce, we celebrate the diverse ways we work. If you have a disability and need an accommodation regarding our recruiting process, please let us know by emailing accomodations@powerschool.com.
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