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Machine Learning Engineer Opt Jobs in Springfield, IL

Crowe LLP

Cyber AI Security Manager

Springfield, IL · On-site +1

$110K - $148K/yr

You'll work with developers, product stakeholders, and project managers as a trusted leader and ... Act as the security expert in designing, developing, and deploying secure AI and machine learning ...

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All JobsMachine Learning Engineer Opt JobsMachine Learning Engineer Opt Jobs in Springfield, IL

Machine Learning Engineer Opt information

See Springfield, IL salary details

$31.2K

$127.6K

$191.8K

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

As of Sep 8, 2026, the average yearly pay for machine learning engineer opt in Springfield, IL is $127,624.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,600.00 and $153,600.00 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 into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

What are some common challenges machine learning engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

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 a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

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

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

What are popular job titles related to Machine Learning Engineer Opt jobs in Springfield, IL?

For Machine Learning Engineer Opt jobs in Springfield, IL, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer Opt jobs in Springfield, IL look for?

The top searched job categories for Machine Learning Engineer Opt jobs in Springfield, IL are:

What cities near Springfield, IL are hiring for Machine Learning Engineer Opt jobs?

Cities near Springfield, IL with the most Machine Learning Engineer Opt job openings:

Machine Learning Engineer Opt jobs near you
Infographic showing various Machine Learning Engineer Opt job openings in Springfield, IL as of August 2026, with employment types broken down into 17% Internship, and 83% Full Time. Highlights an 83% In-person, and 17% Remote job distribution, with an average salary of $127,624 per year, or $61.4 per hour.

Lead AI Quality Assurance Engineer

Envestnet

Springfield, IL • Hybrid

$127K/yr

Full-time

Medical, Retirement, PTO

Posted 25 days ago

Job description

Description

Job Location   

The primary work location for this role is Berwyn, Raleigh, Boston, Chicago, or Seattle with a hybrid work model.   

  

About Envestnet  

Envestnet is an adaptive WealthTech company that is redefining the future of wealth management by helping advisors meet the moment with its comprehensive technology, actionable insights, and industry leading support. Backed by over 25 years of experience and approximately $7.0 trillion in platform assets, Envestnet is trusted by over one third of financial advisors across leading banks, wealth managers, brokerages, and RIAs.   

   

For a deeper look at how Envestnet is shaping the future of financial advice, visit www.envestnet.com.   

   

The Team You’ll Join  

The Quality Assurance Engineering team plays a critical role in ensuring the reliability, security, and effectiveness of Envestnet’s technology solutions, with a growing focus on AI-enabled products and platforms. Working at the intersection of engineering, data science, product, cybersecurity, and business operations, the team develops and executes innovative testing and validation strategies that help deliver trusted experiences for clients and internal stakeholders alike. By championing quality, governance, automation, and continuous improvement, the team helps accelerate the adoption of emerging technologies while ensuring solutions are scalable, compliant, and built to meet the highest standards of performance and customer confidence.

How You’ll Contribute   

Ensures that artificial intelligence solutions are accurate, reliable, secure, compliant and aligned with business and client expectations. Combines traditional QA practices with AI / ML validation techniques to test data integrity, model performance, automation workflows and user outcomes. Works with engineering, data science, product management, cybersecurity, legal and risk teams to validate AI-enabled products and operational processes. Continuously improves testing frameworks, monitoring methodologies, governance standards and automation capabilities to support scalable and trustworthy AI adoption.

  • Leads testing efforts for moderately complex AI products, features and platform enhancements.
     
  • Designs advanced test plans covering model accuracy, bias detection, explainability and operational resilience.
     
  • Develops automated testing frameworks and monitoring approaches for AI systems.
     
  • Performs detailed analysis of defects, model drift and production quality issues.
     
  • Partners with cross-functional stakeholders to define acceptance criteria and quality standards.
     
  • Mentors junior analysts and reviews testing deliverables for quality and consistency.
     
  • Supports implementation of enterprise AI governance and risk management controls.
     
  • Recommends improvements to testing methodologies, tooling and operational processes.
     
  • Facilitates quality reviews, stakeholder workshops, model validation discussions, and testing strategy sessions.
     
  • Identifies operational, technical, compliance, and model-related risks and recommends mitigation strategies.
     
  • Leads validation activities for AI models, data pipelines, automation workflows, user-facing AI capabilities, vendors, tools, and third-party technologies.
     
  • Evaluates quality, reliability, security, governance, and compliance considerations associated with AI products and services.

What You’ll Need to Bring  

  • Candidates should demonstrate the relevant experience, skills, and capabilities needed to successfully perform in the role. Relevant experience may be gained through current responsibilities, prior roles, project work, leadership opportunities, or other comparable experiences.
     
  • Ability to evaluate complex problems, identify root causes, assess alternatives, and implement practical, scalable, data-driven solutions.
     
  • Demonstrated ability to establish and maintain productive relationships across business, technology, product, engineering, data science, and risk organizations.
     
  • Knowledge of process improvement techniques, operational workflows, dependency management, quality optimization, and governance practices.
     
  • Ability to communicate technical and non-technical concepts clearly to diverse audiences, including leadership stakeholders.
     
  • Experience coordinating cross-functional initiatives, managing dependencies, tracking progress, and delivering measurable outcomes.
     
  • Strong understanding of AI concepts, machine learning fundamentals, AI system capabilities, limitations, risks, and practical applications, with experience validating AI/ML models, Generative AI applications, LLM-enabled systems, or data science solutions.
     
  • Experience with automated testing frameworks, API testing, model evaluation, prompt testing, hallucination testing, data quality validation, AI governance controls, and regulatory, security, privacy, or responsible AI requirements. 

Why You’ll Enjoy Working at Envestnet  

Help shape the future of WealthTech. At Envestnet you’ll gain hands-on experience and collaborate with some of the industry’s brightest minds to deliver meaningful, innovative solutions that make a real difference. 

We value flexibility in how and where work gets done, and we recognize strong performance with meaningful rewards—because your contributions should drive both business success and your own personal growth. If you’re looking for a place where your work has impact, your development is supported, and your contributions are truly valued, Envestnet is where you can build your future.  

The opportunity is now!  

  

Sponsorship  

This position is not open to candidates requiring visa sponsorship  

  

Our Investment in You 

This role offers a base salary range of  $152,300 to $190,400. The range listed represents a good-faith estimate of base salary compensation for this position and does not include incentive compensation, equity or benefits. Individual pay will be determined based on factors including, but not limited to, relevant experience, skills, education, certifications, and geographic location, in accordance with applicable pay transparency laws.  This role is eligible for an additional incentive component as part of the total rewards package.   

 

We provide a comprehensive suite of benefits - subject to Envestnet’s plan eligibility rules - that support your overall well-being including, medical insurance, paid time off (PTO), 401k company match, paid parental leave, education reimbursement, disability coverage and mental health & wellness support. Our investment in you means supporting you professionally, financially, and personally at every stage of your journey with us.  Please visit our benefits page on our career site to learn more.  

   

Our Commitment to Inclusion & Belonging  

Envestnet is an Equal Opportunity Employer and is committed to creating an inclusive environment for all employees and applicants. We welcome and value individuals of all backgrounds and do not discriminate based on race, color, religion, creed, sex (including pregnancy or related medical conditions), gender identity or expression, sexual orientation, national origin, ancestry, age, disability, genetic information, military or veteran status, citizenship status, or any other status protected by applicable law. We encourage individuals from all backgrounds to apply.  

 

We strive to provide an inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation, please contact us at  careers@envestnet.com. Please include your full name, the title of the role you are applying for, and the accommodation necessary to assist you with the recruiting process.      

Recruitment Fraud 

At Envestnet, safeguarding the trust and safety of job seekers is a top priority. We are aware that scammers may impersonate Envestnet recruiters or create fake job opportunities to deceive candidates. Review the information on our recruitment fraud awareness page to help you recognize and avoid recruitment fraud. 

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