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Python Ml Developer Jobs in Addison, TX (NOW HIRING)

AI/ML Engineer

Dallas, TX · On-site

$113K - $136K/yr

Strong proficiency in Python, R, or Java, with deep knowledge of OOP principles. * ML/DL Frameworks: Hands-on experience with frameworks such as PyTorch, TensorFlow, Scikit-Learn, or Keras. * Data ...

Senior Python Developer

Plano, TX · On-site

$116K - $157K/yr

Senior Python Developer Location: Plano, TX (Onsite) Experience: 10+ Years Job Summary Persistent ... Knowledge of AI/ML libraries such as Pandas, NumPy, TensorFlow, or PyTorch. * Experience with ...

New

Need Locals who can come for Inperson interivew in Irving, TX office. 4+ years in AI/ML engineering ... SQL/Bigquery/Google Cloud Platform, Python, Prompt Engineering, Hands on experience with SOTA LLMs ...

Exposure to Python ML/agent tools like TensorFlow, PyTorch, or LangChain. Data preprocessing and feature engineering with structured and unstructured data. Strong OOP and design patterns, Git, unit ...

Tata Consultancy Services is seeking a highly skilled Data Engineer with a passion for AI/ML. The ... Required : • Strong experience in PySpark and Python to integrate with AI/ML Models. • ...

Data & ML Engineer

Dallas, TX

$113K - $136K/yr

Expertise in programming languages such as Python or Scala, experience with data processing ... ML infrastructure, CI/CD, DevOps, and MLOps pipelines to support model training and deployment ...

AI/ML Engineers Location: Dallas, TX (Hybrid 2 days/week) Local Only Duration: 3 Months Contract ... python scripting Core requirements: • Strong command of SQL and experience with relational ...

Data & ML Engineer

Dallas, TX

$113K - $136K/yr

Expertise in programming languages such as Python or Scala, experience with data processing ... ML infrastructure, CI/CD, DevOps, and MLOps pipelines to support model training and deployment ...

Data & ML Engineer

Dallas, TX · On-site

$113K - $136K/yr

Expertise in programming languages such as Python or Scala, experience with data processing ... ML infrastructure, CI/CD, DevOps, and MLOps pipelines to support model training and deployment ...

Strong proficiency in CI/CD, DevOps, and MLOps is essential to support the deployment and ... Proficiency in Python, SQL, Scala, and scripting languages * Experience building production grade ...

Data & ML Engineer

Dallas, TX · On-site

$113K - $136K/yr

Strong proficiency in CI/CD, DevOps, and MLOps is essential to support the deployment and ... Proficiency in Python, SQL, Scala, and scripting languages * Experience building production grade ...

Senior Applied ML Engineer

Irving, TX · Remote

$125K - $183K/yr

We are looking for a Senior Applied ML Engineer to be part of revolutionizing these industries. We ... Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face). * Experience ...

Core Responsibilities (AI/ML, Python, AWS, GenAI) * Design and implement end-to-end AI/ML and Generative AI solutions using Python, including model training, evaluation, optimization, and deployment.

Google Cloud ML Engineer

Dallas, TX · On-site

$55.25 - $73.75/hr

Dallas, TX (Day1 Onsite) Duration: Long Term We seek an experienced developer to design, build, and ... Advanced Python skills; experience with ML/NLP libraries (Hugging Face, TensorFlow, PyTorch)

Skills * Required: SQL/Bigquery/Google Cloud Platform, Python, Prompt Engineering, Hands on ... Experience: 4+ years in AI/ML engineering are preferred, with 1+ years specifically focused on ...

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Python Ml Developer information

See Addison, TX salary details

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How much do python ml developer jobs pay per hour?

As of Jul 9, 2026, the average hourly pay for python ml developer in Addison, TX is $56.75, according to ZipRecruiter salary data. Most workers in this role earn between $46.78 and $64.47 per hour, depending on experience, location, and employer.

What does a Python ML Developer do?

A Python ML Developer designs, builds, and deploys machine learning models using the Python programming language. They work with large datasets, clean and process data, select appropriate algorithms, and use libraries like TensorFlow, PyTorch, or scikit-learn to implement solutions. Their work often involves collaborating with data scientists and engineers to integrate machine learning models into applications. Additionally, they may be responsible for testing, tuning, and optimizing models to achieve the best possible performance in real-world scenarios.

What are some common challenges Python ML Developers face when deploying machine learning models to production?

Python ML Developers often encounter challenges such as ensuring model scalability, managing dependencies, and maintaining reproducibility when deploying models into production environments. Integrating machine learning models with existing systems can require close collaboration with DevOps and software engineering teams to streamline workflows and automate deployment pipelines. Additionally, monitoring model performance over time and handling data drift are crucial responsibilities to ensure continued accuracy and reliability of deployed solutions.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and maintain AI and machine learning systems. While AI automation tools can handle certain tasks, MLEs are essential for creating, optimizing, and interpreting complex models, making complete replacement unlikely in the near term. MLEs need skills in programming, data analysis, and model deployment to adapt to evolving AI technologies.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as senior machine learning engineer or AI research director, often requiring advanced skills in deep learning, data science, and programming with tools like Python and TensorFlow. Such roles usually involve leadership, strategic planning, and extensive experience in the field.

Which 3 jobs will survive AI?

For a Python ML Developer, roles that require complex problem-solving, creativity, and human judgment are likely to persist, such as AI research scientist, data scientist, and software engineer. These jobs involve designing, interpreting, and improving AI models, which currently require advanced expertise, critical thinking, and domain knowledge that AI cannot fully replicate. Continuous learning and staying updated with new tools and techniques are essential for long-term career resilience.

What are the key skills and qualifications needed to thrive as a Python ML Developer, and why are they important?

To thrive as a Python ML Developer, you need strong programming skills in Python, a solid understanding of machine learning algorithms, and a background in mathematics or statistics, often supported by a degree in computer science, engineering, or a related field. Familiarity with tools and libraries such as TensorFlow, scikit-learn, PyTorch, and version control systems like Git is essential, along with experience using data visualization and cloud platforms. Critical soft skills include problem-solving, adaptability, and effective communication to collaborate with cross-functional teams and explain complex models to stakeholders. These skills ensure the successful development, deployment, and maintenance of machine learning solutions that drive business value.

What is the difference between Python Ml Developer vs Data Scientist?

AspectPython Ml DeveloperData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; Python, ML certificationsBachelor's/Master's in Data Science, Statistics, or related; Python, ML certifications
Work EnvironmentSoftware development teams, AI/ML projectsResearch, data analysis, modeling teams
Employer & Industry UsageTech companies, startups, AI firmsFinance, healthcare, tech, research institutions
Common Search & ComparisonYesYes

Python ML Developers focus on building and deploying machine learning models using Python, often working closely with software engineering teams. Data Scientists analyze data, create models, and generate insights, often using Python along with statistical tools. While both roles require Python and ML knowledge, Python ML Developers are more involved in implementation and deployment, whereas Data Scientists focus on data analysis and research.

Can you do ML in Python?

Yes, Python is widely used for machine learning (ML) development due to its extensive libraries such as TensorFlow, scikit-learn, and PyTorch. Python skills are essential for a Python ML developer to build, train, and deploy ML models efficiently in various environments.
What cities near Addison, TX are hiring for Python Ml Developer jobs? Cities near Addison, TX with the most Python Ml Developer job openings:
Full Stack Engineer Python Developer / Golang Developer

Full Stack Engineer Python Developer / Golang Developer

Inficare Technologies

Lake Dallas, TX • On-site

$65/hr

Contractor

Posted 19 days ago


Job description

Job Title: Full Stack Engineer (Python / Golang)
Location: Dallas, TX (Day 1 Onsite)
Job Type: 12+ Month Contract
Experience: 10+ years
Job Overview
Our client is seeking a highly experienced Senior Full Stack Engineer with strong expertise in Python and Go (Golang) to design, develop, and scale modern enterprise applications and distributed systems. The ideal candidate will bring deep backend engineering experience, solid frontend development capabilities, and hands-on exposure to modern AI technologies including CrewAI and AI/ML-based application development.
Key Responsibilities
  • Design and develop scalable backend systems using Python and Golang
  • Build REST APIs, microservices, and distributed applications
  • Develop high-performance concurrent and asynchronous services
  • Optimize application performance, reliability, and scalability
  • Implement secure and maintainable coding practices
  • Design reusable frameworks and shared services
  • Collaborate across engineering and product stakeholders
Required Skills
  • Strong Python and GoLang development experience
  • Frameworks: Django, Flask, FastAPI
  • REST APIs and async programming
  • Databases: PostgreSQL, MySQL, MongoDB
  • Git, CI/CD pipelines
  • AI/ML Frameworks: CrewAI, LangChain
  • Machine Learning, Deep Learning, Generative AI, AI Agents