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Python Ml Developer Jobs in Missouri (NOW HIRING)

... 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 ...

ML Algorithm Development * Python Programming * Go Programming * Scala Programming * Java ... Programming * C++ Programming * C# Programming * AutoML Techniques * Optimizing Training And ...

New

Staff Software Engineer

Saint Louis, MO · On-site

$110K - $165K/yr

Proven expertise in Python and ML frameworks (MLFlow, TensorFlow, PyTorch, Scikit- learn, or ... Experience with feature engineering, data preprocessing, and data * Seasoned hands-on coder; still ...

Staff Software Engineer

Saint Louis, MO · On-site

$110K - $165K/yr

Proven expertise in Python and ML frameworks (MLFlow, TensorFlow, PyTorch, Scikit- learn, or ... Experience with feature engineering, data preprocessing, and data * Seasoned hands-on coder; still ...

Collaborate closely with infrastructure, ML engineering, product, and governance teams to deliver ... Strong skills in Python, Java and SQL with expert level skill in either Python or Java. * Proven ...

New

$80K - $110K/yr

Our partner is looking for a Senior ML Engineer (AI Research/ Portability) based in Netherlands ... Strong Python programming skills with excellent software engineering and algorithm design abilities.

... 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 ...

... 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 ...

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 ...

AI Solutions Architect

California, MO · On-site

$180 - $270/hr

Collaborate with data engineers, ML engineers, full-stack developers, and product owners to ... NET/Python) development, API design (REST/GraphQL), and microservices architecture. * Cloud ...

Showing results 41-60

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 the key skills and qualifications needed to thrive as a Python ML Developer?

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 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.

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.

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:

Infographic showing various Python Ml Developer job openings in Missouri as of June 2026, with employment types broken down into 87% Full Time, 6% Part Time, and 7% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution.

Senior/Staff Machine Learning Engineer, Data Infrastructure

Jobtailor

California, MO • On-site

$120 - $160/hr

Other

Posted yesterday

New


Job description

  • Develop infrastructure supporting batch and stream big data processing using Flink, Spark, Ray, and similar technologies
  • Design and operate large-scale data pipelines generating training datasets for machine learning training and experimentation
  • Integrate data pipelines with workflow orchestration systems such as Flyte and Airflow for reliable multi-stage training workflows
  • Improve pipeline reproducibility and observability through dataset validation, monitoring, and automated testing
  • Optimize performance and resource utilization across distributed compute systems
  • Partner with ML engineers to enable large-scale experimentation and model iteration
  • Lead architectural improvements to keep offline data pipelines scalable, reliable, and cost-efficient
Requirements
  • Experience working with distributed computing frameworks such as Flink, Spark, and Ray for distributed data processing
  • Experience building infrastructure for training data generation, dataset preparation, or ML feature pipelines
  • Experience optimizing big data pipelines and infrastructure for cost efficiency
  • Strong programming skills in Python and experience with large-scale distributed workloads
  • Experience with modern data infrastructure, including data lakes, warehouses, orchestration systems, and streaming platforms
  • Strong systems thinking and ability to reason about performance, scalability, reliability, and cost tradeoffs in distributed systems
  • Proven ability to lead technical direction and influence architectural decisions across teams without formal authority
  • Sufficient knowledge of English for professional verbal and written exchanges
  • Work visa/immigration sponsorship is not available for this position
Core Competencies

Demonstrates expertise in developing and optimizing large-scale data pipelines for machine learning, utilizing distributed computing frameworks like Flink, Spark, and Ray. Proficient in integrating orchestration systems and ensuring pipeline reliability and cost efficiency.

Highest-signal resume keywords
  • Flink
  • Spark
  • Ray
  • Python Programming
  • Data Pipeline Optimization
ATS Optimization Keywords Hard Skills
  • Distributed Computing
  • Data Pipeline Development
  • Machine Learning Feature Engineering
  • Dataset Validation
  • Automated Testing
Soft Skills
  • Systems Thinking
  • Technical Leadership
  • Influencing Architectural Decisions
Industry Keywords
  • Big Data Processing
  • Performance Optimization
  • Resource Utilization
  • Scalability
  • Reliability
Tools & Technologies
  • Flyte
  • Airflow
  • Data Lakes
  • Data Warehouses
  • Streaming Platforms
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