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Machine Learning Engineer Jobs in St Louis, MO (NOW HIRING)

Comscore, Total Visits, March 2025) Day to Day As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

As an experienced machine learning engineer, you understand goodsoftware is more than just a good user experience. To compete in today's technical landscape, mission-oriented machine learning ...

As an experienced machine learning engineer, you understand goodsoftware is more than just a good user experience. To compete in today's technical landscape, mission-oriented machine learning ...

As an experienced machine learning engineer, you understand goodsoftware is more than just a good user experience. To compete in today's technical landscape, mission-oriented machine learning ...

As an experienced machine learning engineer, you understand goodsoftware is more than just a good user experience. To compete in today's technical landscape, mission-oriented machine learning ...

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Showing results 1-20

Machine Learning Engineer information

See St Louis, MO salary details

$30.6K

$125.2K

$188.1K

How much do machine learning engineer jobs pay per year?

As of Jun 14, 2026, the average yearly pay for machine learning engineer in St. Louis, MO is $125,193.00, 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.

Is ML full of coding?

Machine Learning Engineers typically do a significant amount of coding, especially in languages like Python or R, to develop algorithms, preprocess data, and build models. Strong programming skills are essential, along with knowledge of frameworks such as TensorFlow or PyTorch, but the role also involves data analysis, model evaluation, and collaboration with teams. Coding is a core component of the job, though some tasks may involve model deployment and optimization that require different skills.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or technology can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

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.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as they develop, implement, and maintain AI systems, requiring specialized skills in programming, data analysis, and model optimization. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and certain managerial positions—are also expected to persist despite AI advancements. These jobs typically require emotional intelligence, adaptability, and domain expertise that AI cannot easily replicate.

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 job categories do people searching Machine Learning Engineer jobs in St. Louis, MO look for? The top searched job categories for Machine Learning Engineer jobs in St. Louis, MO are:
What cities near St. Louis, MO are hiring for Machine Learning Engineer jobs? Cities near St. Louis, MO with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in St. Louis, MO as of June 2026, with employment types broken down into 88% Full Time, and 12% Contract. Highlights an 72% In-person, 16% Hybrid, and 12% Remote job distribution, with an average salary of $125,193 per year, or $60.2 per hour.
Machine Learning Engineer

$140K - $180K/yr

Other

Medical, Dental, Vision, Life, Retirement

Posted 15 days ago


Job description

Position Summary
We are seeking a skilled Machine Learning Engineer with approximately three years of hands-on experience designing, deploying, and maintaining production-grade machine learning systems. In this role, you will collaborate closely with data scientists, software engineers, and product teams to translate research models into reliable, scalable, and high-impact applications. You will be deeply involved in the end-to-end ML lifecycle-from data ingestion and feature engineering to deployment, monitoring, and continuous improvement-playing a critical part in shaping our machine learning platform and capabilities.
Primary Responsibilities
  • Develop, deploy, and optimize machine learning models for real-world business use cases and client-facing applications.
  • Partner with data scientists to operationalize predictive models and ensure scalable, maintainable, and performant production deployments.
  • Design and implement data pipelines and workflows that support training, inference, and model lifecycle management.
  • Work with large, complex datasets to ensure data quality, reproducibility, and reliable version control across ML workflows.
  • Implement model monitoring, logging, and alerting strategies to track performance, detect drift, and support retraining cycles.
  • Leverage cloud platforms (AWS, Azure, GCP) to build scalable ML solutions using managed services and infrastructure-as-code practices.
  • Write clean, modular, and well-documented code aligned with MLOps and software engineering best practices.
  • Stay current on emerging ML tooling, frameworks, and industry best practices to continuously enhance our platform and capabilities.
Qualifications
  • Master's degree in Computer Science, Data Science, Engineering, or a related technical field.
  • 6+ years of experience in machine learning engineering, applied ML, or related software engineering roles.
  • Strong proficiency in Python and experience with modern ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
  • Experience with distributed data processing and compute frameworks (e.g., Pandas, Spark, Dask).
  • Hands-on experience with containerization and orchestration technologies such as Docker and Kubernetes.
  • Familiarity with CI/CD pipelines, testing automation, and version control using Git.
  • Experience working with cloud-based ML platforms or services (e.g., SageMaker, Vertex AI, Databricks, or Snowflake ML) is preferred.
  • Strong understanding of model evaluation, feature engineering, and performance optimization in production contexts.
  • Excellent analytical, communication, and collaboration skills, with the ability to work effectively in cross-functional teams.

This is an exempt position. The annualized base pay range for this role is expected to be between $140,000-$180,000. Actual base pay could vary based on factors including but not limited to experience, subject matter expertise, geographic location where work will be performed, and the applicant's skill set. The base pay is just one component of the total compensation package for employees. Other rewards may include an annual cash bonus and a comprehensive benefits package, including but not limited to medical, dental, vision, life and 401(k). Please note that the job title is subject to change based on the selected candidate's experience and education.
About Focus Financial Partners
Focus is a leading financial services firm comprised of integrated wealth management, family office, and business management services. Blending deep expertise and expansive resources with a boutique, client-first fiduciary philosophy, Focus helps individuals, families, and institutions navigate complex financial situations with highly personalized solutions tailored to their unique needs. To learn more about Focus, visit www.focusfinancialpartners.com or follow the company on LinkedIn.
Focus is an equal opportunity employer and bases its employment decisions on the employee or candidate's skillset, and without regard to an employee or candidate's race, color, religion, sex (including pregnancy), gender identity, sexual orientation, national origin, age, disability, genetic information, veteran status, or any other characteristic protected by local, state and/or federal law.
Focus complies with federal and state disability laws and makes reasonable accommodations for applicants and employees with disabilities. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact careers@focuspartners.com.
The following language is for US based roles only
For California Applicants: Information on your California privacy rights can be found here
For Indiana Applicants: It is unlawful for an employer to discriminate against a prospective employee on the basis of status as a veteran by refusing to employ an applicant on the basis that they are a veteran of the armed forces of the United States, a member of the Indiana National Guard or a member of a reserve component.
For Maryland Applicants: I UNDERSTAND THAT UNDER MARYLAND LAW, AN EMPLOYER MAY NOT REQUIRE OR DEMAND, AS A CONDITION OF EMPLOYMENT, PROSPECTIVE EMPLOYMENT OR CONTINUED EMPLOYMENT, THAT ANY INDIVIDUAL SUBMIT TO OR TAKE A POLYGRAP OR SIMILAR TEST. AN EMPLOYER WHO VIOLATES THIS LAW IS GUILTY OF A MISDEMEANOR AND SUBJECT TO A FINE NOT EXCEEDING $100.
For Massachusetts Applicants: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this shall be subject to criminal penalties and civil liability.
For Montana Applicants: If hired, the employment relationship is governed by the Wrongful Discharge from Employment Act. Mont. Code Ann. Section 39-2-901.
For Rhode Island Applicants: Focus is subject to Chapters 29-38 of Title 28 of the General Laws of Rhode Island and is therefore covered by the state's workers' compensation law. If you willfully provide false information about your ability to perform the essential functions of the job, with or without reasonable accommodations, you may be barred from filing a claim under the provisions of the Workers' Compensation Act of the State of Rhode Island if the false information is directly related to the personal injury that is the basis for the new claim for compensation. The Company complies fully with the Americans with Disabilities Act.