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Remote Senior Machine Learning Engineer Jobs in Saint Louis, MO

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 ...

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 ...

Bunge

Data Scientist

Chesterfield, MO · On-site +1

... engineers, and business leaders, to translate complex business challenges into solvable data ... Translate complex business problems into data-driven analytics and machine learning tasks, then ...

New

GeoYeti

Senior SAR Imagery Scientist

Saint Louis, MO · Remote

$190K - $235K/yr

This role blends remote sensing science with applied data engineering and AI. What You'll Do ... Experience applying machine learning or computer vision techniques to SAR or other remotely sensed ...

Koantek

Data Engineer - Multiple Positions

Chesterfield, MO · Remote

$113K - $136K/yr

United States - Remote Employment Type: Full-Time and Contract Data Engineer Description: As a Data ... Proficient in using advanced analytics and machine learning frameworks, including Apache Spark ...

GRVTY

Imagery Scientist (EO) - Senior

Saint Louis, MO · On-site +1

$160K - $190K/yr

Remote sensing phenomenology * Image formation processes * Exploitation products and methodologies ... Experience applying CV and machine learning (ML) techniques to EO imagery and data to address ...

Hitachi

Senior Transformer Engineer

Earth City, MO · On-site +1

$99K - $136K/yr

Engineering & Science Job Schedule: Full time Remote: Yes Senior Transformer Engineer The ... Access to learning platforms and career development programs * Competitive health and retirement ...

Spartech

Senior Process Engineer (REQ865)

Saint Louis, MO · On-site +1

$98K - $127K/yr

Senior Process Engineer Maryland Heights, MO Spartech offers a competitive salary, incentives, and ... Partner with Operations and Process Engineering teams to improve machine utilization, efficiency ...

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All JobsMachine Learning Engineer JobsRemote Senior Machine Learning Engineer JobsRemote Senior Machine Learning Engineer Jobs in Saint Louis, MO

Remote Senior Machine Learning Engineer information

See Saint Louis, MO salary details

$73.4K

$139.3K

$186.7K

How much do remote senior machine learning engineer jobs pay per year?

As of Aug 12, 2026, the average yearly pay for remote senior machine learning engineer in Saint Louis, MO is $139,312.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,100.00 and $157,000.00 per year, depending on experience, location, and employer.

How do remote senior machine learning engineers typically collaborate with cross-functional teams despite working remotely?

Remote Senior Machine Learning Engineers often work closely with data scientists, product managers, and software engineers using digital collaboration tools such as Slack, Jira, and video conferencing platforms. Regular virtual meetings and code reviews are standard practices to ensure alignment on project goals and to facilitate knowledge sharing. Clear communication, proactive documentation, and adaptability to different time zones are key to effective teamwork in a remote environment. This structure allows for flexibility while maintaining strong collaboration and project momentum.

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

AspectRemote Senior Machine Learning EngineerRemote Data Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models, collaborates with engineering teamsAnalyzes data, builds statistical models, provides insights
Employer & Industry UsageTech companies, startups, AI-focused firmsResearch institutions, tech companies, finance, healthcare

Remote Senior Machine Learning Engineers focus on designing, building, and deploying ML models, often working closely with engineering teams. Data Scientists analyze data and develop insights, but may not always deploy models. Both roles require strong technical skills and are highly sought after in tech industries, but their core responsibilities differ.

What are the key skills and qualifications needed to thrive as a remote senior machine learning engineer, and why are they important?

To thrive as a Remote Senior Machine Learning Engineer, you need deep expertise in machine learning algorithms, statistical analysis, and strong programming skills (often in Python or similar languages), typically supported by a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (AWS, GCP, or Azure), and experience with data engineering pipelines are commonly required, along with certifications like TensorFlow Developer or AWS Machine Learning Specialty. Excellent problem-solving, communication, and self-management skills help you collaborate remotely, lead projects, and explain complex models to stakeholders. These skills and qualities are vital for building scalable ML solutions, ensuring effective teamwork across distributed environments, and delivering impactful results.

What does a remote senior machine learning engineer do?

A Remote Senior Machine Learning Engineer designs, develops, and deploys machine learning models and systems while working from a location outside the traditional office. They collaborate with cross-functional teams, analyze large datasets, build scalable algorithms, and often mentor junior engineers. Their work helps organizations automate processes, gain insights, and improve products or services using data-driven approaches. Senior engineers are also responsible for ensuring model performance, reliability, and integration into production environments. Working remotely, they use various communication and collaboration tools to stay connected with their team.
What are popular job titles related to Remote Senior Machine Learning Engineer jobs in Saint Louis, MO? For Remote Senior Machine Learning Engineer jobs in Saint Louis, MO, the most frequently searched job titles are:
What job categories do people searching Remote Senior Machine Learning Engineer jobs in Saint Louis, MO look for? The top searched job categories for Remote Senior Machine Learning Engineer jobs in Saint Louis, MO are:
Remote Senior Machine Learning Engineer jobs near you

Senior AI Engineer

Koantek

Chesterfield, MO • Remote

$54.75 - $70.50/hr

Contractor

Re-posted 8 days ago

Job description

Sr AI Engineer / Data Scientist / MLOps Consultant Location: United States - Remote Employment Type: Full-Time and Contract We are seeking an experienced and highly technical Data Scientist to join our customer-facing consulting team. This remote role requires a blend of advanced Machine Learning (ML) expertise, deep knowledge of MLOps principles, and a proven track record in client-facing implementation. The successful candidate will be instrumental in designing, deploying, and maintaining production-grade ML solutions, including advanced Generative AI and Natural Language Processing (NLP) models, for our diverse client base.Key Responsibilities Serve as a primary technical consultant, leading and executing end-to-end ML project implementations directly with clients, translating complex business problems into robust technical solutions

Exhibit excellent communication, presentation, and stakeholder management skills to clearly articulate technical findings, proposals, and project status to both technical and non-technical audiences. Design, build, and maintain production-grade ML pipelines, focusing on continuous integration, continuous delivery (CI/CD), and advanced MLOps practices to ensure reliability and scalability of models. Implement and optimize cutting-edge Generative AI and NLP applications, demonstrating hands-on experience with technologies like Retrieval Augmented Generation (RAG) and Large Language Models (LLMs) in a production setting.

Manage underlying solution infrastructure, demonstrating proficiency in technologies such as Docker, pipeline orchestrators, and database systems. Leverage expertise in distributed computing frameworks, specifically in scalable machine learning and high-performance data processing (e.g., using technologies like Apache Spark). Contribute to the strategic growth of the ML Practice Team, including participation in technical assignments and knowledge transfer activities

Ensure all client engagements and training activities are properly documented and reported via designated partner platforms. Required Qualifications 4+ years of hands-on professional experience developing, deploying, and managing Machine Learning models, with a mandatory requirement for productionizing and maintaining models in a live environment. 3+ years of experience in a customer-facing consulting or solutions architect role, focused on technical implementation and delivery.

Excellent verbal and written communication skills for effective client and internal team interaction. Expertise in MLOps lifecycle management, including model versioning, testing, monitoring, and automated deployment best practices. Demonstrable experience with infrastructure management, encompassing containerization (Docker) and data pipeline orchestration.

Deep understanding of programming for data-intensive and scalable ML applications. Proven experience in deploying and managing Generative AI and NLP solutions for client applications. Preferred Qualifications Hands-on experience with modern ML platform stacks, such as Databricks MLOps Stacks.

Knowledge of specific tools and techniques used in scalable machine learning and large-scale data processing. Demonstrated commitment to continuous learning in emerging ML fields, such as LLMs and GenAI application architectures. Requirements Hands-on experience with modern ML platform stacks, such as Databricks MLOps Stacks.

Knowledge of specific tools and techniques used in scalable machine learning and large-scale data processing. Demonstrated commitment to continuous learning in emerging ML fields, such as LLMs and GenAI application architectures.

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