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Junior Machine Learning Engineer Jobs in Springfield, OH

Resonetics

AI Automation Engineering Co-Op

Dayton, OH

$22 - $24/hr

This role blends software engineering, machine learning, and process automation to solve real-world engineering challenges. Join Resonetics and be part of a team that's redefining medical device ...

New

Aptima, Inc

AI Engineer 2

Dayton, OH · On-site

$115K - $130K/yr

... machine learning models to solve complex, mission-critical problems. Whether fine-tuning large ... Collaborate with software engineers, within an agile development environment, to implement, test ...

Aptima Inc

AI Engineer

Dayton, OH · On-site

$115K - $130K/yr

... machine learning models to solve complex, mission-critical problems. Whether fine-tuning large ... Collaborate with software engineers, within an agile development environment, to implement, test ...

Resonetics

AI Automation Engineering Co-Op

Dayton, OH · On-site

$22 - $24/hr

This role blends software engineering, machine learning, and process automation to solve real-world engineering challenges. Join Resonetics and be part of a team that's redefining medical device ...

Aptima Inc. (All Jobs)

AI Engineer

Dayton, OH · On-site

$115K - $130K/yr

... machine learning models to solve complex, mission-critical problems. Whether fine-tuning large ... Collaborate with software engineers, within an agile development environment, to implement, test ...

Parallax

Senior Software Engineer

Beavercreek, OH · On-site

$113K - $149K/yr

... machine learning and artificial intelligence • Handle large-scale datasets, ensuring data ... junior engineers and contribute to technical roadmaps • Partner with cross-functional teams to ...

STR

Lead Algorithm & Signal Processing Engineer

Dayton, OH · On-site

$157K - $220K/yr

Design and apply cutting-edge signal processing and machine learning techniques to solve complex ... Government * BS, MS, or PhD in Electrical Engineering, Applied Mathematics, Physics, or related ...

STR

Lead Algorithm & Signal Processing Engineer

Dayton, OH · On-site

$157K - $220K/yr

Design and apply cutting-edge signal processing and machine learning techniques to solve complex ... Government * BS, MS, or PhD in Electrical Engineering, Applied Mathematics, Physics, or related ...

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All JobsMachine Learning Engineer JobsJunior Machine Learning Engineer JobsJunior Machine Learning Engineer Jobs in Springfield, OH

Junior Machine Learning Engineer information

See Springfield, OH salary details

$30.2K

$64.7K

$98.6K

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

As of Sep 4, 2026, the average yearly pay for junior machine learning engineer in Springfield, OH is $64,673.00, according to ZipRecruiter salary data. Most workers in this role earn between $43,700.00 and $72,100.00 per year, depending on experience, location, and employer.

What does a junior machine learning engineer do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

What kinds of projects and responsibilities can a junior machine learning engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

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

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

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

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

How much do junior machine learning engineers make?

Junior machine learning engineers typically earn between $70,000 and $100,000 annually, depending on location, education, and industry. Entry-level roles often require knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.
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What job categories do people searching Junior Machine Learning Engineer jobs in Springfield, OH look for?

The top searched job categories for Junior Machine Learning Engineer jobs in Springfield, OH are:

What cities near Springfield, OH are hiring for Junior Machine Learning Engineer jobs?

Cities near Springfield, OH with the most Junior Machine Learning Engineer job openings:

Junior Machine Learning Engineer jobs near you
Infographic showing various Junior Machine Learning Engineer job openings in Springfield, OH as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $64,673 per year, or $31.1 per hour.

Director, Model Engineering & Operations

CareSource

Dayton, OH • On-site, Remote

Full-time

Re-posted 6 hours ago

CareSource rating

7.7

Company rating: 7.7 out of 10

Based on 28 frontline employees who took The Breakroom Quiz

211th of 315 rated insurance

Job description

Job Summary:
The Director, Model Engineering & Operations is responsible for leading the strategy, development, implementation, and optimization of enterprise AI and machine learning solutions that support core health plan operations and business objectives. This role provides leadership for the design and delivery of scalable, secure, and compliant AI/ML platforms and production systems, while overseeing the end-to-end machine learning lifecycle. The Director leads a team of machine learning engineers and applied scientists and collaborates across business and technology functions to translate advanced analytics and artificial intelligence capabilities into reliable, cost-effective, and operationalized solutions that drive organizational performance and innovation.
Essential Functions:
  • Lead the design, development, and productionization of ML and AI models across risk adjustment (HCC/RAF), HEDIS/Stars quality measures, care management, utilization management, fraud/waste/abuse, and member/provider experience use cases.
  • Own the end-to-end MLOps lifecycle on Databricks: feature engineering and feature store design, model training and versioning (MLflow), CI/CD for ML pipelines, deployment patterns (batch, real-time, and streaming inference), and automated retraining.
  • Establish and enforce model monitoring practices - drift detection, performance degradation alerts, bias/fairness checks, and champion-challenger frameworks - to ensure production models remain accurate and compliant over time.
  • Guide the evaluation and responsible adoption of generative AI and LLM-based capabilities (e.g., Mosaic AI, Genie, retrieval-augmented generation) for internal analytics, member/provider-facing tools, and operational automation.
  • Define engineering standards, design patterns, and reusable components (feature libraries, model templates, deployment scaffolding) to accelerate delivery across the data science and ML engineering teams.
  • Partner with data governance and security teams to ensure all ML/AI systems comply with HIPAA, CMS, and NCQA requirements, including PHI handling, access controls, and audit trails within Unity Catalog.
  • Manage model risk documentation and validation processes suitable for regulatory review (e.g., RADV audits, Stars/HEDIS submissions) in partnership with compliance and quality teams.
  • Own the cost, performance, and reliability of the ML platform footprint on Databricks, including compute optimization, cluster/job design, and vendor/tooling evaluation (e.g., build vs. buy decisions for platform capabilities).
  • Collaborate with BI, data engineering, and data science teams to ensure ML features and pipelines align with the broader canonical data model and lakehouse architecture.
  • Translate business problems from clinical, quality, finance, and operations stakeholders into well-scoped ML engineering initiatives with clear success metrics and delivery timelines.
  • Communicate technical strategy, risk, and progress to senior leadership and non-technical stakeholders in clear, business-relevant terms.
  • Perform any other job related duties as requested.

Education and Experience:
  • Bachelor's degree in Computer Science, Data Science, Engineering, or a related field required
  • Master's degree in Computer Science, Data Science, Engineering preferred
  • Equivalent years of relevant work experience may be accepted in lieu of required education
  • Eight (8) years in software/ML engineering required
  • Five (5) years of leadership experience required
  • Experience productionizing ML models at scale, including MLOps practices (CI/CD, model versioning, monitoring, retraining pipelines) required
  • Experience operating within regulated, PHI-governed environments; working knowledge of HIPAA and healthcare data standards required
Competencies, Knowledge and Skills:
  • Familiarity in a health plan, payer, or healthcare provider environment, with exposure to HEDIS/Stars, HCC risk adjustment, claims (837/835), and clinical data standards (HL7, FHIR, CCDA)
  • Knowledgeable in cloud infrastructure (Azure preferred, given Databricks-on-Azure deployment) and Infrastructure-as-Code practices
  • Hands-on proficiency with Databricks (or comparable lakehouse platform), Delta Lake, MLflow, and Spark; strong Python and SQL skills
  • Solid understanding of ML fundamentals (supervised/unsupervised learning, model evaluation, feature engineering) and modern AI/LLM concepts (RAG, embeddings, prompt engineering, model evaluation for generative systems)
  • Ability to evaluate or implement knowledge graph, entity resolution, or Member 360-style initiatives
  • Strong communication skills with the ability to influence both technical teams and executive stakeholders
  • Ability to present model risk or AI governance documentation to regulators, auditors, or compliance committees
  • Strong service orientation and consulting skills
  • Ability to work collaboratively with all levels of management
  • Ability to juggle multiple complex priorities within a changing environment
  • Strong leadership and management skills with the ability to motivate in a team-orientated, collaborative environment
  • Strong knowledge of outsourcing and staff augmentation strategies supporting testing processes
  • Knowledge of the managed care industry is preferred
  • Exceptionally self-motivated and directed
Licensure and Certification:
  • None
Working Conditions:
  • General office environment; may be required to sit or stand for extended periods of time
  • Ability to travel as required by the needs of the business.

Compensation Range:
$135,600.00 - $237,400.00
CareSource takes into consideration a combination of a candidate's education, training, and experience as well as the position's scope and complexity, the discretion and latitude required for the role, and other external and internal data when establishing a salary level. In addition to base compensation, you may qualify for a bonus tied to company and individual performance. We are highly invested in every employee's total well-being and offer a substantial and comprehensive total rewards package.
Compensation Type (hourly/salary):
Salary
Organization Level Competencies
  • Fostering a Collaborative Workplace Culture
  • Cultivate Partnerships
  • Develop Self and Others
  • Drive Execution
  • Influence Others
  • Pursue Personal Excellence
  • Understand the Business

This job description is not all inclusive. CareSource reserves the right to amend this job description at any time. CareSource is an Equal Opportunity Employer. We are dedicated to fostering an environment of belonging that welcomes and supports individuals of all backgrounds.
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