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Senior Machine Learning Engineer Jobs in St Louis, MO

Koantek

Senior AI Engineer

Chesterfield, MO · On-site

$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 ...

Booz Allen Hamilton

Agentic AI Developer

O Fallon, IL · On-site

$99K - $225K/yr

As a machine learning engineer on our Defense Technology team, you'll train, test, deploy, and maintain models that learn from data to create real-world, mission-critical impacts. In this role, you ...

Booz Allen Hamilton

Agentic AI Developer

O Fallon, IL · On-site

$99K - $225K/yr

As a machine learning engineer on our Defense Technology team, you'll train, test, deploy, and maintain models that learn from data to create real-world, mission-critical impacts. In this role, you ...

Boeing

Senior Data Scientist

Hazelwood, MO · On-site

Senior Data Scientist Company: The Boeing Company Boeing Defense, Space & Security (BDS) is hiring ... Implement and deploy machine learning models, working closely with software engineering teams to ...

Boeing

Senior Data Scientist

Hazelwood, MO

Senior Data Scientist Company: The Boeing Company Boeing Defense, Space & Security (BDS) is hiring ... Implement and deploy machine learning models, working closely with software engineering teams to ...

Boeing

Senior Data Scientist

Hazelwood, MO

Senior Data Scientist Company: The Boeing Company Boeing Defense, Space & Security (BDS) is hiring ... Implement and deploy machine learning models, working closely with software engineering teams to ...

Arka Infotech Inc

Sr. Scala Developer

Saint Louis, MO · On-site

$53 - $70/hr

Sr. Scala Developer 12+ Months St. Louis, Missouri 08-03-2015 Senior Scala Developer w/hands-on ... such as Machine Learning and Bayesian Methods. Must be familiar w/NoSQL on the back-end. ...

Pwc

AI Solutions Engineering Delivery Lead

Saint Louis, MO · On-site

$99K - $131K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... As a senior technical leader, you will leverage deep technical specialization, strategic vision ...

The Boeing Company

Senior Data Scientist

Hazelwood, MO · On-site

$162.35 - $219.65/hr

Boeing Defense, Space & Security (BDS) is hiring a Senior Data Scientist for a Proprietary Program ... Implement and deploy machine learning models, working closely with software engineering teams to ...

New

Deloitte

Lead Forward Deployed Engineer - AWS

Saint Louis, MO · On-site

$99K - $131K/yr

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ ... Work you'll do As an AWS AI&Data FDE, you will work side by side with senior functional and ...

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Showing results 21-40

All JobsMachine Learning Engineer JobsSenior Machine Learning Engineer JobsSenior Machine Learning Engineer Jobs in St Louis, MO

Senior Machine Learning Engineer information

See St Louis, MO salary details

$57.8K

$123K

$178.4K

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

As of Aug 12, 2026, the average yearly pay for senior machine learning engineer in St Louis, MO is $123,042.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,600.00 and $139,500.00 per year, depending on experience, location, and employer.

What are some common challenges senior machine learning engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What does a senior machine learning engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

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

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

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

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What cities near St Louis, MO are hiring for Senior Machine Learning Engineer jobs? Cities near St Louis, MO with the most Senior Machine Learning Engineer job openings:
Senior Machine Learning Engineer jobs near you
Infographic showing various Senior Machine Learning Engineer job openings in St Louis, MO as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $123,042 per year, or $59.2 per hour.

Senior AI Engineer

Koantek

Chesterfield, MO • On-site

$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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