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Senior Machine Learning Engineer Jobs in Sikeston, MO

... machine learning, generative AI, agentic AI, and natural language processing required. * Strong understanding of large language models (LLMs), prompt engineering, retrieval-augmented generation (RAG ...

Custodian

Cape Girardeau, MO · On-site

$13.75 - $17.50/hr

Junior/Senior High SchoolDescription: The MNW JH/HS is currently accepting applications for a ... Maintain an environment in the workplace safe and conducive to student learning according to ...

... Central Engineering, Scheduling, Shipping/Warehouse, and Sales & Marketing. Duties and ... Continuous Learning o Understands individual strengths and opportunity areas and seeks development ...

Chief Nursing Officer (CNO)

Cape Girardeau, MO · On-site

$124K - $170K/yr

Total Rewards for our Senior Leaders include: * Annual incentive plan * Relocation Support ... Diverse programming to expand your experience * HealthStream online learning catalogue with plenty ...

Chief Nursing Officer (CNO)

Cape Girardeau, MO · On-site

$124K - $170K/yr

Total Rewards for our Senior Leaders include: * Annual incentive plan * Relocation Support ... Diverse programming to expand your experience * HealthStream online learning catalogue with plenty ...

Total Rewards for our Senior Leaders include: * Annual incentive plan * Relocation Support ... Diverse programming to expand your experience * HealthStream online learning catalogue with plenty ...

Senior Machine Learning Engineer information

See Sikeston, MO salary details

$54.8K

$116.6K

$169K

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

As of Aug 23, 2026, the average yearly pay for senior machine learning engineer in Sikeston, MO is $116,562.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,200.00 and $132,200.00 per year, depending on experience, location, and employer.

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 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 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 Sikeston, MO are hiring for Senior Machine Learning Engineer jobs?

Cities near Sikeston, MO with the most Senior Machine Learning Engineer job openings:

Lead Data Scientist

Vizient

Cape Girardeau, MO • On-site

Full-time

Re-posted 12 days ago


Job description

When you're the best, we're the best. We instill an environment where employees feel engaged, satisfied and able to contribute their unique skills and talents while living and working as their authentic selves. We provide extensive opportunities for personal and professional development, building both employee competence and organizational capability to fuel exceptional performance through an inclusive environment both now and in the future.

Summary:

In this role, you willdevelop and deploy advanced analytics, machine learning, generative AI, and agentic AI solutions that address complex business and client challenges. You will design scalable data science products, translate sophisticated analytical findings into actionable insights, and guide data scientists in delivering high-quality solutions that improve clinical, operational, and economic outcomes. You will influence technical strategy, drive innovation, and ensure analytical solutions align with organizational objectives.

Responsibilities:

  • Lead the design, development, and implementation of advanced machine learning, generative AI solutions across structured and unstructured data.
  • Build and deploy scalable, automated data science products and reusable analytic assets that support business and client objectives.
  • Analyze large-scale, high-dimensional datasets using modern analytics tools and distributed computing platforms to identify trends, opportunities, and actionable insights.
  • Design and prototype agentic AI workflows leveraging large language models (LLMs), retrieval systems, structured data, APIs, tools, and business rules to automate complex business processes.
  • Translate business requirements into AI agent architectures, including task decomposition, tool orchestration, routing logic, escalation paths, and human approval checkpoints.
  • Optimize retrieval-augmented generation (RAG) solutions through embedding evaluation, metadata design, reranking approaches, citation quality assessment, and knowledge freshness validation.
  • Develop evaluation frameworks for machine learning and AI solutions, including performance, accuracy, reliability, hallucination risk, latency, cost, safety, and consistency measures.
  • Make key analytical and architectural decisions, establish technical standards, and provide leadership on methodology, model selection, solution design, and AI implementation best practices.
  • Lead code reviews, mentor data scientists, and promote best practices in software development, responsible AI, model governance, and analytics delivery.
  • Partner with engineering, platform, and business teams to deploy, monitor, and maintain production-ready analytics and AI solutions.
  • Translate complex analytical findings into clear reports, visualizations, and presentations for technical and non-technical audiences.
  • Collaborate with stakeholders and clients to define analytical approaches that address strategic, operational, and clinical objectives.
  • Evaluate emerging technologies and industry trends to advance organizational analytics and AI capabilities.

Qualifications:

  • Relevant degree preferred. Advanced degree in applied mathematics, statistics, computer science, econometrics, or a related field is a plus.
  • 7 or more years of relevant experience required.
  • Demonstrated expertise in data science methodologies, statistical modeling, machine learning, generative AI, agentic AI, and natural language processing required.
  • Strong understanding of large language models (LLMs), prompt engineering, retrieval-augmented generation (RAG), and autonomous decision-making frameworks within enterprise AI environments highly preferred.
  • Expertise in programming languages such as Python, R, SQL, SAS, or similar analytical tools.
  • Experience with vector databases, semantic search technologies, knowledge graphs, metadata management, or enterprise search platforms.
  • Experience deploying, monitoring, and maintaining machine learning and AI solutions in production environments.
  • Knowledge of responsible AI principles, model governance, explainability, bias detection, validation methodologies, and ethical use of data.
  • Experience designing and implementing human-in-the-loop workflows that balance automation, governance, risk management, and user oversight.
  • Experience working with cloud-based and distributed data platforms and modern analytics frameworks such as Databricks.
  • Strong analytical, problem-solving, communication, and presentation skills with the ability to convey complex concepts to diverse audiences.
  • Experience leading complex analytics initiatives, providing technical guidance, and mentoring data scientists.
  • Experience working with healthcare data, including clinical, claims, operational, or financial datasets preferred.

#LI-JB1

Estimated Hiring Range:

At Vizient, we consider skills, experience, and organizational needs in our compensation approach. Geographic factors may adjust the range estimate and hires typically fall below the top range. Compensation decisions are tailored to individual circumstances. The current salary range for this role is $117,600.00 to $206,000.00.

This position is also incentive eligible.

Vizient has a comprehensive benefits plan! Please view our benefits here:

http://www.vizientinc.com/about-us/careers

Equal Opportunity Employer: Females/Minorities/Veterans/Individuals with Disabilities

The Company is committed to equal employment opportunity to all employees and applicants without regard to race, religion, color, gender identity, ethnicity, age, national origin, sexual orientation, disability status, veteran status or any other category protected by applicable law.