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Machine Learning Manager Jobs in Missouri (NOW HIRING)

... manage machine learning models and large language models. • Conduct research to provide technical solutions to scale AI/ML powered features for real-world challenges, making trade-offs based on ...

... manage machine learning models and large language models. • Conduct research to provide technical solutions to scale AI/ML powered features for real-world challenges, making trade-offs based on ...

Design, develop, and maintain AI and machine learning solutions using Python and modern data science frameworks. * Build, optimize, and manage scalable data pipelines and ETL processes to support ...

You will lead a team responsible for the data and machine learning backbone that powers critical ... Collaborate with data scientists, product managers, and engineering leaders to translate data ...

AI Solutions Architect

Saint Louis, MO

$61.25 - $80.75/hr

Leading sales, solution design, and delivery for artificial intelligence, machine learning, automation, and data-driven Human Capital engagements * Developing account growth strategies, managing ...

Option 3: 6-8 years of direct experience in data science, machine learning, or applied risk management within an e-commerce or marketplace setting. Preferred Qualifications: * Expertise in using ...

AI Solutions Architect

Kansas City, MO

$61.50 - $81/hr

Leading sales, solution design, and delivery for artificial intelligence, machine learning, automation, and data-driven Human Capital engagements * Developing account growth strategies, managing ...

Option 3: 6-8 years of direct experience in data science, machine learning, or applied risk management within an e-commerce or marketplace setting. Preferred Qualifications: * Expertise in using ...

Experience in MLOps and deploying/managing machine learning models. * Exceptional analytical and problem-solving skills, with the ability to think strategically and innovatively. * Excellent verbal ...

Option 3: 6-8 years of direct experience in data science, machine learning, or applied risk management within an e-commerce or marketplace setting. Preferred Qualifications: * Expertise in using ...

Experience in MLOps and deploying/managing machine learning models. * Exceptional analytical and problem-solving skills, with the ability to think strategically and innovatively. * Excellent verbal ...

Experience in MLOps and deploying/managing machine learning models. * Exceptional analytical and problem-solving skills, with the ability to think strategically and innovatively. * Excellent verbal ...

This includes large-scale data analysis, advanced statistical modeling, case investigation, and production-grade machine learning systems to manage risk on the ecommerce platform. We partner closely ...

This includes large-scale data analysis, advanced statistical modeling, case investigation, and production-grade machine learning systems to manage risk on the ecommerce platform. We partner closely ...

This includes large-scale data analysis, advanced statistical modeling, case investigation, and production-grade machine learning systems to manage risk on the ecommerce platform. We partner closely ...

Senior AI Engineer

Chesterfield, MO · Remote

$54.75 - $70.50/hr

Required Qualifications 4+ years of hands-on professional experience developing, deploying, and managing Machine Learning models, with a mandatory requirement for productionizing and maintaining ...

Senior AI Engineer

Chesterfield, MO · On-site

$54.75 - $70.50/hr

Required Qualifications • 4+ years of hands-on professional experience developing, deploying, and managing Machine Learning models, with a mandatory requirement for productionizing and maintaining ...

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Showing results 1-20

Machine Learning Manager information

See Missouri salary details

$47.8K

$76.6K

$110.7K

How much do machine learning manager jobs pay per year?

As of May 30, 2026, the average yearly pay for machine learning manager in Missouri is $76,643.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,900.00 and $86,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Manager, and why are they important?

To thrive as a Machine Learning Manager, you need a robust background in machine learning algorithms, statistical analysis, and software engineering, typically supported by an advanced degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and project management platforms, along with experience in deploying ML systems, is essential. Strong leadership, communication, and strategic thinking skills set exceptional managers apart, enabling them to guide teams and align projects with business objectives. These skills are crucial to successfully leading technical teams, ensuring project delivery, and translating complex ML solutions into organizational value.

What are some of the main challenges a Machine Learning Manager faces when leading a team?

A Machine Learning Manager often navigates challenges such as balancing project deadlines with the need for thorough experimentation and research, ensuring clear communication between technical and non-technical stakeholders, and fostering collaboration among data scientists, engineers, and product teams. Additionally, managers must keep their team's skills current with rapidly evolving technologies while also addressing issues like data quality and model deployment in production environments. Successfully overcoming these challenges requires strong leadership, adaptability, and a deep understanding of both business objectives and technical intricacies.

What are Machine Learning Managers?

Machine Learning Managers are professionals responsible for leading teams that develop, implement, and maintain machine learning models and systems. They oversee data scientists, engineers, and other specialists, ensuring projects align with business goals and are delivered on time. Their role often involves coordinating cross-functional teams, managing project timelines, and staying current with the latest advancements in artificial intelligence and machine learning. Additionally, they may be involved in hiring, mentoring, and providing technical guidance to their team.
What are the most commonly searched types of Machine Learning jobs in Missouri? The most popular types of Machine Learning jobs in Missouri are:
What are popular job titles related to Machine Learning Manager jobs in Missouri? For Machine Learning Manager jobs in Missouri, the most frequently searched job titles are:
What cities in Missouri are hiring for Machine Learning Manager jobs? Cities in Missouri with the most Machine Learning Manager job openings:
Infographic showing various Machine Learning Manager job openings in Missouri as of May 2026, with employment types broken down into 84% Full Time, 13% Part Time, and 3% Contract. Highlights an 50% Physical, 5% Hybrid, and 45% Remote job distribution, with an average salary of $76,643 per year, or $36.8 per hour.
AI Data Engineer - Manager

AI Data Engineer - Manager

Deloitte

Kansas City, MO • On-site

Full-time

Posted 10 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

59th of 138 rated financial services


Job description

Job Summary:
Deloitte is a leading consulting firm focused on transforming the nature of work through innovative solutions. They are seeking an AI Data Engineer - Manager to lead data architecture and engineering delivery for AI/ML/GenAI solutions, ensuring data integrity and scalability while managing a team and collaborating with various stakeholders.
Responsibilities:
• Lead the data architecture and engineering delivery that enables AI/ML/GenAI solutions, ensuring data is trusted, secure, observable, and scalable from ingestion through consumption.
• Design and operationalize modern data and retrieval foundations to support LLM-powered applications (e.g., Claude, GPT/Codex, Gemini) including patterns such as RAG, embeddings, vector search, and governed access to structured and unstructured data.
• Manage day-to-day delivery with an onshore/offshore team, partnering with data science, ML engineering, and product stakeholders to translate use cases into production-ready pipelines and platforms with strong data governance, lineage, quality controls, and monitoring.
• Help define the AI/ML/GenAI technical direction and vision, ensuring alignment with strategic goals and digital transformation efforts.
• Translate the vision of business leaders into realistic technical implementations, while identifying misaligned initiatives and impractical use cases.
• Design end-to-end AI architectures, from data ingestion to model deployment, integrating with cloud and on-premises systems.
• Select appropriate technologies from a pool of open-source and commercial offerings, considering deployment models and integration with existing tools.
• Understand and contribute to MLOps and LLMOps, focusing on operational capabilities and infrastructure to deploy and manage machine learning models and large language models.
• Conduct research to provide technical solutions to scale AI/ML powered features for real-world challenges, making trade-offs based on quality, scalability, performance, and cost.
• Lead the development of AI models (e.g., machine learning, natural language processing, computer vision) and implement scalable AI solutions.
• Collaborate with Enterprise, Application, Data & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to pilot use cases and discuss best design.
• Gather inputs from multiple stakeholders to align technical implementation with existing and future requirements.
• Serve as a technical advisor to leadership, providing insights on AI trends, potential business impacts, and implementation best practices.
• Be responsible for the successful execution of AI-powered applications using agile methodology.
• Audit AI tools and practices across data, models and software engineering, focusing on continuous improvement and feedback mechanisms.
• Contribute to standardizing CI/CD pipelines, user and service roles, and container creation, model consumption, testing, and deployment methodology based on business and security requirements.
• Work closely with security and risk leaders to foresee and mitigate risks, ensuring ethical AI implementation and compliance with upcoming regulations.
• Address potential issues such as training data poisoning, AI model theft, and adversarial samples.
• Help AI product managers and business stakeholders understand the potential and limitations of AI when planning new products.
• Break down client problems and bring an understanding of leading technology, analytics methods, tools, and operating model approaches.
• Build tools and capabilities that assist with data ingestion, feature engineering, data management, and organization.
• Design, implement, and maintain distributed computing solutions for data processing and model training, ensuring the security, scalability, and reliability of machine learning infrastructure.
Qualifications:
Required:
• Bachelor's degree in Computer Science, Statistics, Data Science, Information Systems or related field.
• 6+ years of consulting experience leading delivery teams, including onshore and offshore team members
• 6+ years of experience gathering non-functional requirements and defining application architecture frameworks, including validation and testing deliverables
• 5+ years of experience working in an AI environment
• 5+ years of experience translating requirements into client ready design documents
• 5+ years of experience in software application architecture analysis, design, and delivery
• 5+ years of experience executing full system development life cycle implementations
• Ability to travel 0-25%, on average, based on the work you do and the clients and industries/sectors you serve.
• Limited immigration sponsorship may be available.
Preferred:
• Advanced degrees such as Masters or PhD are preferred
• Certifications in AI/ML technologies and Cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Azure AI Engineer, Azure Data Scientist, or Azure Solutions Architect
• 5 + years of experience in Data Science, Statistics, and Machine Learning
• 5+ years of experience in Generative AI/LLMs, preferably experienced in delivering and productionizing
• 5+ years of experience in machine learning model development, natural language processing, and data analysis; Experienced in Supervised and Unsupervised learning, feature engineering, model training, and deployment
• 5+ year of experience in implementing cloud-based AI/ML workloads on any of AWS, Microsoft and Azure.
Company:
Deloitte is a business consulting company that offers audit, consulting, financial advisory, and tax services. Founded in 1845, the company is headquartered in London, GBR, with a team of 10001+ employees. The company is currently Late Stage.

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