1

Machine Learning Engineer Jobs in Saint Louis, MO

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 analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Implement and deploy machine learning models, working closely with software engineering teams to integrate into customer environments. * Collaborate with subject matter experts to understand ...

Associate Engineering Data Scientist

Hazelwood, MO · On-site

$55K - $56K/yr

Implement and deploy machine learning models, working closely with software engineering teams to integrate into customer environments. * Collaborate with subject matter experts to understand ...

Associate Engineering Data Scientist

Hazelwood, MO · On-site

$55K - $56K/yr

Implement and deploy machine learning models, working closely with software engineering teams to integrate into customer environments. * Collaborate with subject matter experts to understand ...

NGA AI Engineer Manager

Saint Louis, MO · On-site

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Showing results 41-60

Machine Learning Engineer information

See Saint Louis, MO salary details

$30.6K

$125.2K

$188.1K

How much do machine learning engineer jobs pay per year?

As of Aug 8, 2026, the average yearly pay for machine learning engineer in Saint Louis, MO is $125,174.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,700.00 and $150,700.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Saint Louis, MO? The most popular types of Machine Learning Engineer jobs in Saint Louis, MO are:
What are popular job titles related to Machine Learning Engineer jobs in Saint Louis, MO? For Machine Learning Engineer jobs in Saint Louis, MO, the most frequently searched job titles are:
What cities near Saint Louis, MO are hiring for Machine Learning Engineer jobs? Cities near Saint Louis, MO with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Saint Louis, MO as of August 2026, with employment types broken down into 78% Full Time, and 22% Contract. Highlights an 74% In-person, and 26% Remote job distribution, with an average salary of $125,174 per year, or $60.2 per hour.

AI Solutions Engineering Delivery Lead

Pwc

Saint Louis, MO • On-site

$99K - $131K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 14 days ago


PwC rating

8.3

Company rating: 8.3 out of 10

Based on 76 frontline employees who took The Breakroom Quiz

26th of 72 rated business consultants


Job description

Industry/Sector

Not Applicable

Specialism

IFS - Internal Firm Services - Other

Management Level

Director

Job Description & Summary

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.
Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven decision making. You will work on developing predictive models, conducting statistical analysis, and creating data visualisations to solve complex business problems.
Translating the vision, you set the tone, and inspire others to follow. Your role is crucial in driving business growth, shaping the direction of client engagements, and mentoring the next generation of leaders. You are expected to be a guardian of PwC's reputation, understanding that quality, integrity, inclusion and a commercial mindset are all foundational to our success. You create a healthy working environment while maximising client satisfaction. You cultivate the potential in others and actively team across the PwC Network, understanding tradeoffs, and leveraging our collective strength.
Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:
Lead in line with our values and brand.
Develop new ideas, solutions, and structures; drive thought leadership.
Solve problems by exploring multiple angles and using creativity, encouraging others to do the same.
Balance long-term, short-term, detail-oriented, and big picture thinking.
Make strategic choices and drive change by addressing system-level enablers.
Promote technological advances, creating an environment where people and technology thrive together.
Identify gaps in the market and convert opportunities to success for the Firm.
Adhere to and enforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance) the Firm's code of conduct, and independence requirements.
The Opportunity
:
The AI Solutions Engineering Delivery Lead will oversee multiple multidisciplinary teams consisting of data scientists, software engineers, front-end developers, and other specialists in the design, development, deployment, monitoring, and maintenance of full-stack AI solutions. As a senior technical leader, you will leverage deep technical specialization, strategic vision, comprehensive business acumen, and exceptional stakeholder communication skills to deliver impactful AI-driven solutions. This is a "hand-on" overseeing one or more AI solution work streams, driving continuous adaptation to emerging technologies, ensuring rigorous quality standards, and fostering a culture of continuous improvement and innovation.
Responsibilities
:
- Provide strategic and technical leadership across multiple AI solution delivery teams
- Architect and oversee the delivery of comprehensive AI solutions, emphasizing full-stack development, including integration of Large Language Models (LLMs) and orchestrated applications
- Manage and own the full lifecycle of AI models and solutions, from development through deployment, monitoring, maintenance, and iterative enhancement
- Direct experiment-driven development, ensuring rapid prototyping, testing, validation, and operational excellence
- Establish and drive consistent quality control and continuous improvement of AI solutions, closely collaborating with business stakeholders to align solutions with strategic objectives
- Develop and maintain robust stakeholder relationships, clearly communicating complex solutions and strategic implications to senior business leaders
- Promote technical innovation, process improvement, and effective methodologies across teams
- Continuously evaluate and drive adoption of emerging technologies to enhance solution capabilities and maintain competitive advantage
What You Must Have
:
- Bachelor's Degree in Computer Science, Data Science, Engineering, Mathematics, or related technical field
- Minimum of 10 years of experience, including substantial experience in a senior technical leadership role managing multiple multidisciplinary teams
What Sets You Apart
:
- An advanced degree is preferred
- Proven track record of hands-on experience in architecting, delivering, and managing AI and machine learning solutions, particularly with orchestrated LLM applications
- Proven specialization in Python, Pandas, Scikit-learn, PyTorch, Langchain, Semantic Kernel, SQL, vector DBs, LLMs, and prompt engineering
- Proven specialization with major cloud platforms such as AWS, Azure, or Google Cloud Platform, with cloud foundational certifications highly desirable
- Extensive experience with Agile methodologies, continuous integration/continuous deployment (CI/CD), Git version control, and rigorous testing frameworks (unit, integration, end-to-end)
- Extensive experience translating complex technical solutions into strategic business outcomes
- Prior experience leveraging executive-level communication skills, capable of effectively articulating technical and strategic concepts to multiple stakeholders while navigating ambiguity
- Proven track record of leading strategy, emphasizing analytical, decision-making, and problem-solving capabilities
- Proven ability to navigate complexity and ambiguity, providing clear direction and maintaining composure under pressure

Travel Requirements

Up to 20%

Job Posting End Date

The salary range for this position is: $122,500 - $423,780. For residents of Washington state the salary range for this position is: $122,500 - $504,500. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glanceAs PwC is anequal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.Learn more about how we work: https://pwc.to/how-we-workFor only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines: https://pwc.to/us-application-deadlines

What PwC employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom