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Python Ml Developer Jobs in Dayton, OH (NOW HIRING)

Booz Allen Hamilton, Inc.

AI/ML Engineer, Mid

Dayton, OH · On-site

$77K - $176K/yr

Experience with Python-based ML frameworks such as PyTorch or TensorFlow * Experience demonstrating ... Experience with ML engineering and MLOps, including model versioning, CI/CD for ML, monitoring ...

Booz Allen Hamilton, Inc.

AI/ML Engineer, Mid

Dayton, OH · On-site

$77K - $176K/yr

Experience with Python-based ML frameworks such as PyTorch or TensorFlow * Experience demonstrating ... Experience with ML engineering and MLOps, including model versioning, CI/CD for ML, monitoring ...

Booz Allen Hamilton

Mid AI/ML Engineer

Dayton, OH · On-site

$77K - $176K/yr

R0242676 AI/ML Engineer, Mid The Opportunity: As an Artificial Intelligence and Machine Learning ... Experience with Python-based ML frameworks such as PyTorch or TensorFlow * Experience demonstrating ...

Booz Allen Hamilton

Mid AI/ML Engineer

Dayton, OH · On-site

$77K - $176K/yr

Experience with Python-based ML frameworks such as PyTorch or TensorFlow * Experience demonstrating ... Experience in GPU programming, including CUDA or RAPIDs * Experience with AWS and containerization ...

Altamira Technologies Corp.

AI/ML Engineer

Fairborn, OH · On-site

Position Overview Altamira is seeking an AI/ML Engineer to support the design, development, and ... Python * C/C++ * Rust Altamira is an Equal Opportunity/Affirmative Action employer. All qualified ...

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Python Ml Developer information

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How much do python ml developer jobs pay per hour?

As of Jul 13, 2026, the average hourly pay for python ml developer in Dayton, OH is $56.98, according to ZipRecruiter salary data. Most workers in this role earn between $46.97 and $64.71 per hour, depending on experience, location, and employer.

What does a Python ML Developer do?

A Python ML Developer designs, builds, and deploys machine learning models using the Python programming language. They work with large datasets, clean and process data, select appropriate algorithms, and use libraries like TensorFlow, PyTorch, or scikit-learn to implement solutions. Their work often involves collaborating with data scientists and engineers to integrate machine learning models into applications. Additionally, they may be responsible for testing, tuning, and optimizing models to achieve the best possible performance in real-world scenarios.

What are some common challenges Python ML Developers face when deploying machine learning models to production?

Python ML Developers often encounter challenges such as ensuring model scalability, managing dependencies, and maintaining reproducibility when deploying models into production environments. Integrating machine learning models with existing systems can require close collaboration with DevOps and software engineering teams to streamline workflows and automate deployment pipelines. Additionally, monitoring model performance over time and handling data drift are crucial responsibilities to ensure continued accuracy and reliability of deployed solutions.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and maintain AI and machine learning systems. While AI automation tools can handle certain tasks, MLEs are essential for creating, optimizing, and interpreting complex models, making complete replacement unlikely in the near term. MLEs need skills in programming, data analysis, and model deployment to adapt to evolving AI technologies.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as senior machine learning engineer or AI research director, often requiring advanced skills in deep learning, data science, and programming with tools like Python and TensorFlow. Such roles usually involve leadership, strategic planning, and extensive experience in the field.

Which 3 jobs will survive AI?

For a Python ML Developer, roles that require complex problem-solving, creativity, and human judgment are likely to persist, such as AI research scientist, data scientist, and software engineer. These jobs involve designing, interpreting, and improving AI models, which currently require advanced expertise, critical thinking, and domain knowledge that AI cannot fully replicate. Continuous learning and staying updated with new tools and techniques are essential for long-term career resilience.

What are the key skills and qualifications needed to thrive as a Python ML Developer, and why are they important?

To thrive as a Python ML Developer, you need strong programming skills in Python, a solid understanding of machine learning algorithms, and a background in mathematics or statistics, often supported by a degree in computer science, engineering, or a related field. Familiarity with tools and libraries such as TensorFlow, scikit-learn, PyTorch, and version control systems like Git is essential, along with experience using data visualization and cloud platforms. Critical soft skills include problem-solving, adaptability, and effective communication to collaborate with cross-functional teams and explain complex models to stakeholders. These skills ensure the successful development, deployment, and maintenance of machine learning solutions that drive business value.

What is the difference between Python Ml Developer vs Data Scientist?

AspectPython Ml DeveloperData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; Python, ML certificationsBachelor's/Master's in Data Science, Statistics, or related; Python, ML certifications
Work EnvironmentSoftware development teams, AI/ML projectsResearch, data analysis, modeling teams
Employer & Industry UsageTech companies, startups, AI firmsFinance, healthcare, tech, research institutions
Common Search & ComparisonYesYes

Python ML Developers focus on building and deploying machine learning models using Python, often working closely with software engineering teams. Data Scientists analyze data, create models, and generate insights, often using Python along with statistical tools. While both roles require Python and ML knowledge, Python ML Developers are more involved in implementation and deployment, whereas Data Scientists focus on data analysis and research.

Can you do ML in Python?

Yes, Python is widely used for machine learning (ML) development due to its extensive libraries such as TensorFlow, scikit-learn, and PyTorch. Python skills are essential for a Python ML developer to build, train, and deploy ML models efficiently in various environments.
What are popular job titles related to Python Ml Developer jobs in Dayton, OH? For Python Ml Developer jobs in Dayton, OH, the most frequently searched job titles are:
What job categories do people searching Python Ml Developer jobs in Dayton, OH look for? The top searched job categories for Python Ml Developer jobs in Dayton, OH are:
What cities near Dayton, OH are hiring for Python Ml Developer jobs? Cities near Dayton, OH with the most Python Ml Developer job openings:
Python Ml Developer jobs near you
Infographic showing various Python Ml Developer job openings in Dayton, OH as of July 2026, with employment types broken down into 84% Full Time, 4% Part Time, 1% Temporary, 10% Contract, and 1% Nights. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $118,514 per year, or $57 per hour.
Distinguished AI/ML Engineer

Distinguished AI/ML Engineer

Frontier Technology Inc.

Dayton, OH • On-site, Remote

Full-time

Posted 11 days ago

Job description

Overview
FTI Defense delivers mission-focused solutions to the Department of Defense and Intelligence Community through advanced engineering, digital transformation, and program execution expertise. We help our customers solve complex challenges and achieve mission success by integrating people, process, and technology.
FTI Defense is seeking a Distinguished AI/ML Engineer to serve as a technical leader, architect, and integrator - designing, building, deploying, and sustaining AI systems that transform complex mission data into trusted, explainable insights.
This is a hands-on builder role, not an analytics management position. The ideal candidate is equally comfortable writing model code, standing up ML pipelines, and integrating AI inference services into operational systems within secure environments. The right candidate blends deep AI/ML engineering expertise with system-level architecture leadership and an ability to unify data engineering, simulation modeling, and responsible AI principles into scalable, mission-ready capabilities.
Responsibilities
  • Architect and integrate hybrid AI systems that combine traditional machine learning, deep learning, large language models (LLMs), and retrieval-augmented generation (RAG) pipelines.
  • Design and deploy scalable AI architectures including APIs, microservices, and model-serving frameworks that integrate seamlessly with analytic, simulation, or operational systems.
  • Lead the full AI/ML lifecycle - from data ingestion and feature engineering through training, deployment, and sustainment within secure DoD environments (IL5/IL6, ATO, GovCloud).
  • Engineer event-driven data pipelines and feature stores for both structured and unstructured data, including text, imagery, and simulation outputs.
  • Ensure Responsible AI practices by embedding traceability, explainability, and confidence scoring into deployed systems.
  • Implement and maintain MLOps pipelines (MLflow, Kubeflow, Airflow, Docker/Kubernetes) to support continuous integration, retraining, and drift detection.
  • Transition R&D prototypes into production, optimizing for mission constraints such as limited compute, edge environments, or disconnected operations.
  • Provide technical leadership and mentorship, setting standards for model quality, architectural design, and ethical AI deployment across programs.
  • Collaborate across engineering, data, and modeling teams to unify FTI's AI portfolio, ensuring interoperability and reuse across mission systems.
  • Support proposal and solution development, providing technical inputs for AI/ML architectures, data strategies, and Responsible AI assurance frameworks.

Education/Qualifications
  • Active Secret clearance required; TS/SCI strongly preferred.
  • Bachelor's degree in Computer Science, Engineering, or a related technical field (Master's or Ph.D. preferred).
  • 10+ years of overall experience in AI/ML development, with 5+ years designing and deploying scalable AI/ML architectures, including at least two full lifecycle implementations (from prototype to operational system).
  • Proficiency in Python, PyTorch, TensorFlow, and modern ML frameworks.
  • Experience designing or deploying systems using vector databases (Milvus, Pinecone, Weaviate), knowledge graphs, and semantic search frameworks.
  • Proven ability to design event-driven data pipelines using Databricks, Spark, Flink, or Kafka.
  • Demonstrated experience deploying AI/ML systems in secure, classified, or edge environments.
  • Familiarity with Responsible AI and assurance principles, including bias detection, explainability, human-machine teaming, and hallucination prevention.
  • Experience integrating AI models into simulation, modeling, or operational planning systems is highly desirable.
  • Experience transitioning R&D systems into accredited production environments.
  • Strong communication and mentoring skills, with the ability to lead technically while remaining deeply hands-on.

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