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Python Ml Developer Jobs in Missouri (NOW HIRING)

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Strong background in Python, distributed systems, and backend development, with a firm grasp of software engineering best practices. * Technical Strategy: Experience defining SLIs/SLOs and managing ...

MetroStar

$147K - $156K/yr

As Sr. AI/ML Engineer I , you'll MetroStar is seeking an AI / ML Engineer to support a high ... Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or similar * Experience ...

Brain Corp

$46.25 - $60.25/hr

Collaborate cross-functionally with ML, DevOps, and robotics teams to define APIs, data models, and ... Strong proficiency in Go, Python, or TypeScript, with an emphasis on maintainable, production ...

Pwc

GenAI Python Systems Engineer-Manager

Saint Louis, MO · On-site

$99K - $232K/yr

... and ML solutions to drive innovation and enhance business processes. Your work will involve ... and deploying DevOps pipelines with cloud services - Enhancing cloud resources for cost and ...

Walmart

Staff, Machine Learning Engineer

Anderson, MO · On-site

$130K - $260K/yr

... developer, and a passion for great customer-centric products. * Design, architect, build AI/ML models, AI Agents and deploy, operate, optimize the solutions * Work on Python and mainstream machine ...

Walmart

Staff, Machine Learning Engineer

Noel, MO · On-site

$130K - $260K/yr

... developer, and a passion for great customer-centric products. * Design, architect, build AI/ML models, AI Agents and deploy, operate, optimize the solutions * Work on Python and mainstream machine ...

Walmart

Staff, Machine Learning Engineer

Cassville, MO · On-site

$130K - $260K/yr

... developer, and a passion for great customer-centric products. * Design, architect, build AI/ML models, AI Agents and deploy, operate, optimize the solutions * Work on Python and mainstream machine ...

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Python Ml Developer information

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 are popular job titles related to Python Ml Developer jobs in Missouri? For Python Ml Developer jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Python Ml Developer jobs in Missouri look for? The top searched job categories for Python Ml Developer jobs in Missouri are:
Python Ml Developer jobs near you

Staff ML Engineer

Third-Party Job Posts

Remote

Other

Posted 8 days ago

Job description

Location - Remote (Europe)

How You'll Make an Impact:

As a Staff Machine Learning Engineer, you will play a key role in building and implementing features that empower lodging customers to make data-driven pricing decisions. Some of these features will use simple heuristic data, while others will leverage advanced machine learning techniques to optimize revenue strategies.

You'll work closely with product and engineering teams to identify opportunities for improvement, develop innovative solutions, and drive revenue growth for the hotels that rely on our platform. Your impact will be focused on ensuring the reliability, scalability, and high quality of our ML systems from development to production. You'll be instrumental in establishing robust ML practices and rigorous testing processes across the entire ML lifecycle. From structuring data pipelines to implementing and validating ML models, you'll own the end-to-end development of our revenue management application-ensuring hotels have the reliable, accurate insights they need to maximize their success.

Our Machine Learning Team:

Our machine learning team is energized by the unique challenge of revolutionizing guest experiences through AI-driven insights, transforming traditional hospitality with cutting-edge predictive algorithms. 

We thrive on collaborative innovation, where data scientists, engineers, and product experts seamlessly blend their expertise to prototype bold ideas and directly impact operational efficiency. 

People who are passionate about continuous learning, unafraid to challenge conventions, and excited by the intersection of hospitality and deep technical prowess will find their home among our forward-thinking team.

What You Bring to the Team:

  • Architectural Expertise: Proven track record in designing, deploying, and maintaining production-grade, distributed ML systems (Sagemaker)
  • Deep MLOps Proficiency: Expert-level knowledge of CI/CD, orchestration (e.g., Apache Airflow, Flink), and model monitoring/drift detection at scale.
  • Software Engineering Rigor: Strong background in Python, distributed systems, and backend development, with a firm grasp of software engineering best practices.
  • Technical Strategy: Experience defining SLIs/SLOs and managing large-scale technical roadmaps.
  • Leadership: Demonstrated ability to influence cross-functional teams, mentor junior talent, and drive consensus on complex technical decisions.
  • Domain Knowledge: Ability to apply statistical and ML methods to optimize revenue management and pricing strategies.

What Sets You Up for Success:

  • 5+ years of experience in a machine learning role, with demonstrated success in ML Engineering and deploying models to production.
  • Proven expertise in designing and implementing ML testing strategies (e.g., data validation, model correctness, performance testing).
  • Great understanding of machine learning principles (experimental design, statistical distributions and test, machine learning algorithms)
  • Expertise in deploying ML models at scale on AWS, with experience using MLFlow, Sagemaker or similar platforms.
  • Strong Python programming skills and adherence to software engineering best practices (e.g., clean code, version control, code reviews, using Docker, Terform, Kubernetes).
  • Expert-level SQL skills and experience working with large datasets for analysis and modeling.
  • Strong problem-solving skills with the ability to apply creative, data-driven solutions to complex business challenges.
  • Excellent communication and collaboration skills, with experience working cross-functionally with product and engineering teams.
  • Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.

Bonus Skills to Stand Out (Optional):

  • Experience with CI/CD tooling (e.g., GitHub Actions, Jenkins) specifically for ML pipelines and Airflow DAG deployment.
  • Experience with data quality monitoring tools and frameworks.
  • Master's or PhD in Computer Science, Mathematics, or a related field. 

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