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Freelance Google Machine Learning Engineer Jobs in Missouri

Kohl's

$95K - $131K/yr

... a Machine Learning Engineer with a proven track record of successful project delivery * In-depth knowledge of cloud platform, preferably Google Cloud Platform services, particularly Vertex AI ...

Bass Pro Shops

Lead Engineer AI/ML - Onsite

Springfield, MO · On-site

$93K - $122K/yr

The Machine Learning Engineer designs, builds, tests, and optimizes machine learning systems that support enterprise AI initiatives across the business. This role is responsible for developing ...

Jobgether

The role combines hands-on technical delivery with collaboration across data, engineering ... Integrate machine learning models into applications, business processes, and operational workflows.

Brooksource

MLE II

Saint Louis, MO · On-site

$50 - $55/hr

Machine Learning Engineer II Remote (U.S.) Remote Role Compensation: $50 - $55 per hour ABOUT THE ROLE Brooksource is partnering with a Fortune 50 healthcare organization to hire a Machine Learning ...

Third-Party Job Posts

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 ...

Catawiki

Working with cross-disciplinary teams involving product owners, developers, UX designers, and ... PyTorch/Tensorflow, LightFM, Git, Docker, Kubernetes, Google BigQuery, MySQL, Spark, Airflow, Kafka ...

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 ...

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 ...

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Freelance Google Machine Learning Engineer information

What are the key skills and qualifications needed to thrive as a freelance Google Machine Learning Engineer?

To thrive as a Freelance Google Machine Learning Engineer, you need a solid background in computer science, statistics, and machine learning, typically supported by a relevant degree and experience with real-world data projects. Familiarity with Google Cloud Platform (GCP), TensorFlow, and certifications like Google Professional Machine Learning Engineer are commonly required. Strong problem-solving abilities, self-motivation, and effective client communication distinguish top freelancers in this field. These skills and qualifications are crucial for delivering robust machine learning solutions tailored to client needs and efficiently navigating remote, project-based work.

What does a freelance Google Machine Learning Engineer do?

A Freelance Google Machine Learning Engineer is a technical specialist who designs, develops, and deploys machine learning models using Google’s tools and platforms, such as TensorFlow and Google Cloud AI services. They work independently or with clients to solve data-driven problems, build predictive models, and automate processes using machine learning techniques. Their responsibilities may include data preprocessing, feature engineering, model training and evaluation, and integrating models into production systems. Freelancers often manage multiple projects and must stay updated on the latest ML advancements and Google technologies.

What are some common challenges freelance Google Machine Learning Engineers face when working with clients remotely?

Freelance Google Machine Learning Engineers often encounter challenges such as clearly defining project scopes, aligning on deliverables, and managing expectations, especially when working remotely. Communication can be more complex due to time zone differences and varying levels of technical understanding among clients. Staying updated with Google’s latest ML tools and ensuring secure, efficient data sharing are also important. Building strong documentation and regular progress updates can help foster trust and smooth collaboration.

What is the difference between Freelance Google Machine Learning Engineer vs Freelance Data Scientist?

AspectFreelance Google Machine Learning EngineerFreelance Data Scientist
CredentialsKnowledge of Google Cloud ML tools, programming skills in Python, TensorFlowStatistical expertise, programming in Python/R, data analysis skills
Work EnvironmentCloud platforms, AI/ML projects, collaboration with developersData analysis, reporting, model development, client communication
Industry UsageTech companies, AI startups, cloud service providersFinance, healthcare, marketing, research organizations

While both roles involve working with data and models, a Freelance Google Machine Learning Engineer specializes in deploying ML solutions on Google Cloud, focusing on AI/ML engineering tasks. A Freelance Data Scientist primarily analyzes data, builds statistical models, and provides insights. The roles overlap in skills but differ in focus and tools used.

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

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

What are popular job titles related to Freelance Google Machine Learning Engineer jobs in Missouri?

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

What job categories do people searching Freelance Google Machine Learning Engineer jobs in Missouri look for?

The top searched job categories for Freelance Google Machine Learning Engineer jobs in Missouri are:

What cities in Missouri are hiring for Freelance Google Machine Learning Engineer jobs?

Cities in Missouri with the most Freelance Google Machine Learning Engineer job openings:

Freelance Google Machine Learning Engineer jobs near you
Infographic showing various Freelance Google Machine Learning Engineer job openings in Missouri as of June 2026, with employment types broken down into 97% Full Time, 1% Part Time, and 2% Nights. Highlights an 77% Physical, 2% Hybrid, and 21% Remote job distribution.

Lead Machine Learning Engineer - News

Jobtailor

California, MO • On-site

$180 - $240/hr

Other

Posted 10 days ago

Job description

Responsibilities
  • Own complex technical initiatives end-to-end, from technical design through production deployment and operational excellence
  • Design and develop infrastructure supporting the full cycle of machine learning, including data pipelines and workflow orchestration, data discovery and quality tools, and feature libraries
  • Drive data and ML-driven solutions for diverse engineering use cases such as recommendation systems, object detection, autogenerated tagging solutions, RAGs
  • Partner with product, editorial, and engineering stakeholders to translate business requirements into robust technical solutions
  • Strategically prioritize initiatives and technical workstreams to deliver the highest-impact and most time-sensitive outcomes, while proactively identifying, communicating, and mitigating risks to ensure successful execution
  • Champion engineering best practices across code quality, testing, CI/CD, observability, and incident response
  • Mentor and coach engineers, fostering a culture of ownership, collaboration, and continuous improvement
  • Contribute to technical documentation and promote knowledge sharing across teams
Requirements
  • Bachelor’s degree in computer science, Information Systems, Statistics, Math, or comparable field of study, and/or equivalent work experience
  • 7+ years of software engineering experience
  • 5+ years of hands‑on experience developing and deploying machine learning systems in production
  • Expertise in data science, deep learning algorithms, or statistical methods to solve real‑world engineering problems
  • Comfortable operating at all levels of the predictive stack, including data collection, data analysis, feature engineering, batch training and low‑latency online serving
  • Experience designing and developing backend microservices for large-scale distributed systems using REST
  • Experience with cloud infrastructure, preferably AWS (Step Functions, Lambda, Glue, SQS, SNS, Personalize)
  • Familiarity with developing and deploying Spark and ML pipelines
  • Hands‑on experience with big data technologies such as Databricks, Kinesis, Kafka
  • Proven leadership, coaching, and mentoring skills, with the ability to inspire and empower a team towards achieving business goals
  • Experience with observability tools for metrics, logging, and monitoring such as Datadog
  • Experience working in Agile/Scrum development environments
  • Excellent communication skills and a commitment to collaboration in a fast‑paced, guest‑focused environment.
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