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Flexible Remote Machine Learning Engineer Jobs in Missouri

Third-Party Job Posts

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 ...

Catawiki

We believe in creating flexible models that can be applied to a variety of use cases, and in ... Working with cross-disciplinary teams involving product owners, developers, UX designers, and ...

Varsity Tutors

Machine Learning Tutor

Columbia, MO · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Saint Louis, MO · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Kansas City, MO · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Jobgether

You will contribute to features spanning data preparation, machine learning, visualization, MLOps ... Remote working opportunity within the United Kingdom. * Strong focus on innovation, engineering ...

Koantek

Senior AI Engineer

Chesterfield, MO · Remote

$54.75 - $70.50/hr

Sr AI Engineer / Data Scientist / MLOps Consultant Location: United States - Remote Employment Type ... This remote role requires a blend of advanced Machine Learning (ML) expertise, deep knowledge of ...

Jobgether

$100K - $120K/yr

You will combine software engineering, machine learning, and MLOps/LLMOps expertise to create ... remote working model . * Opportunity to work on cutting-edge AI, machine learning, and GenAI ...

Jobgether

Fully remote work from India. * Opportunity to work on large-scale machine learning models and high-performance inference systems. * Exposure to advanced model optimization, systems engineering, and ...

Jobgether

You will work at the intersection of machine learning research and systems engineering to develop ... Remote working arrangement with the flexibility to contribute from locations worldwide. * Direct ...

Jobgether

$97K - $132K/yr

... machine learning fundamentals, predictive modeling, feature engineering, and model evaluation ... Fully remote work environment with a standard 40-hour work week . * Limited travel, generally less ...

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Flexible Remote Machine Learning Engineer information

What is a flexible remote machine learning engineer?

A Flexible Remote Machine Learning Engineer is a professional who designs, builds, and deploys machine learning models while working remotely, often with flexible hours. They use programming, data analysis, and statistical skills to create algorithms that solve real-world problems, collaborating with teams through digital communication tools. This role allows for a better work-life balance and can be performed from anywhere with a reliable internet connection. Flexible remote positions are especially popular in the tech industry, where project-based work and results matter more than strict office hours.

What are the key skills and qualifications needed to thrive as a flexible remote machine learning engineer?

To thrive as a Flexible Remote Machine Learning Engineer, you need strong programming skills (especially in Python), a solid understanding of machine learning algorithms, and typically a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, cloud platforms (AWS, GCP, or Azure), and experience with data pipelines are essential, and certifications in machine learning or cloud technologies can be advantageous. Excellent communication, self-motivation, and time management skills help you collaborate effectively and stay productive in a remote, flexible work environment. These skills ensure you can independently deliver high-quality ML solutions, maintain clear team communication, and adapt to evolving project requirements.

How does a flexible remote work arrangement impact collaboration and project delivery for machine learning engineers?

In a flexible remote setting, Machine Learning Engineers often rely on digital collaboration tools to communicate with team members and manage projects. This setup allows for asynchronous work, enabling engineers to focus deeply on model development and data analysis without constant interruptions. However, it also means proactively scheduling check-ins and maintaining clear documentation are crucial to ensure alignment across distributed teams. While remote work offers autonomy and work-life balance, successful engineers build strong communication habits to keep projects on track and foster effective collaboration with data scientists, product managers, and software engineers.

What is the difference between Flexible Remote Machine Learning Engineer vs Data Scientist?

AspectFlexible Remote Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, ML, or related fields; experience with ML frameworksBachelor's or higher in CS, Statistics, or related fields; proficiency in data analysis
Work EnvironmentRemote, collaborative teams, project-basedRemote or on-site, data analysis-focused
Industry UsageTech, finance, healthcare, e-commerceTech, marketing, finance, research
Common Search IntentRoles involving ML model development and deploymentRoles focused on data analysis and insights

The main difference is that a Flexible Remote Machine Learning Engineer primarily develops and deploys machine learning models, while a Data Scientist focuses on analyzing data to generate insights. Both roles often require similar educational backgrounds and can be remote, but their core responsibilities differ in application and focus.

What are the most commonly searched types of Remote Machine Learning Engineer jobs in Missouri?

The most popular types of Remote Machine Learning Engineer jobs in Missouri are:

What are popular job titles related to Flexible Remote Machine Learning Engineer jobs in Missouri?

For Flexible Remote Machine Learning Engineer jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Flexible Remote Machine Learning Engineer jobs in Missouri look for?

The top searched job categories for Flexible Remote Machine Learning Engineer jobs in Missouri are:

What cities in Missouri are hiring for Flexible Remote Machine Learning Engineer jobs?

Cities in Missouri with the most Flexible Remote Machine Learning Engineer job openings:

Flexible Remote Machine Learning Engineer jobs near you
Infographic showing various Flexible Remote Machine Learning Engineer job openings in Missouri as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, and 2% Contract. Highlights an 80% Physical, 1% Hybrid, and 19% Remote job distribution.

Staff ML Engineer

Remote

Third-Party Job Posts
See more jobs at Third-Party Job Postsexternal

Full-time

Re-posted 10 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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