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Remote Aws Machine Learning Jobs in Springfield, OH

CareSource

AI Developer (HealthCare Experience)

Dayton, OH · On-site +1

$94K - $164K/yr

Train, validate, and fine-tune machine learning and deep learning models for optimal performance ... Experience with cloud platforms (AWS, Azure, GCP) and MLOps tools Is required * Experience with ...

Booz Allen Hamilton, Inc.

DevOps Engineer

Beavercreek, OH · On-site +1

$61K - $141K/yr

You'll apply your skills within an AWS DevOps framework to establish or provision virtual machines ... Remote : If this position is listed as remote, there may still be occasions when you are required ...

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Remote Aws Machine Learning information

What are the key skills and qualifications needed to thrive as a remote AWS Machine Learning engineer?

To thrive as a Remote AWS Machine Learning Engineer, you need a strong background in machine learning algorithms, statistical analysis, and proficiency in programming languages such as Python, often supported by a relevant degree or certification. Familiarity with AWS services like SageMaker, Lambda, and EC2, as well as experience using cloud-based ML tools and AWS Certified Machine Learning credentials, is typically required. Excellent problem-solving skills, self-motivation, and clear written communication are valuable soft skills for remote collaboration and project management. These skills ensure effective model development, seamless deployment on cloud infrastructure, and successful remote teamwork in delivering scalable ML solutions.

What is a remote AWS Machine Learning job?

Remote AWS Machine Learning jobs involve working with Amazon Web Services' suite of machine learning tools and services, such as SageMaker, to build, train, and deploy machine learning models. These positions allow professionals to work from anywhere, collaborating with teams virtually while leveraging AWS infrastructure to solve data-driven problems. Responsibilities often include data preprocessing, model development, and deploying scalable solutions in the cloud. Typical job titles may include Machine Learning Engineer, Data Scientist, or AI Developer, all with a focus on AWS technologies. These roles require strong programming skills, experience with cloud computing, and a background in machine learning or data science.

What is the difference between Remote Aws Machine Learning vs Remote Data Scientist?

AspectRemote Aws Machine LearningRemote Data Scientist
Required CredentialsAWS certifications, machine learning coursesStatistics, data analysis, programming skills
Work EnvironmentCloud platforms, AWS services, remote teamsData analysis, modeling, research in remote settings
Industry UsageTech, finance, healthcare using AWS ML toolsResearch, consulting, analytics across industries

Remote AWS Machine Learning specialists focus on deploying machine learning models using AWS cloud services, requiring AWS certifications and cloud expertise. Remote Data Scientists analyze data, build models, and interpret results, often with a stronger emphasis on statistics and programming. While both roles work remotely and involve data, AWS Machine Learning roles are more cloud and deployment-oriented, whereas Data Scientists focus on data analysis and research.

What are some common challenges faced by remote AWS Machine Learning engineers, and how can they be addressed?

Remote AWS Machine Learning engineers often face challenges related to communication and collaboration, especially when working across different time zones and with cross-functional teams. Ensuring secure access to data and cloud resources is another key concern, given the sensitive nature of many machine learning projects. To overcome these challenges, engineers should leverage AWS collaboration tools, maintain clear documentation, and participate in regular virtual meetings. Additionally, setting up robust security protocols and using AWS Identity and Access Management (IAM) helps safeguard project assets while enabling effective teamwork.
What are popular job titles related to Remote Aws Machine Learning jobs in Springfield, OH? For Remote Aws Machine Learning jobs in Springfield, OH, the most frequently searched job titles are:
What job categories do people searching Remote Aws Machine Learning jobs in Springfield, OH look for? The top searched job categories for Remote Aws Machine Learning jobs in Springfield, OH are:
What cities near Springfield, OH are hiring for Remote Aws Machine Learning jobs? Cities near Springfield, OH with the most Remote Aws Machine Learning job openings:
Remote Aws Machine Learning jobs near you
Infographic showing various Remote Aws Machine Learning job openings in Springfield, OH as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

AI Developer (HealthCare Experience)

CareSource

Dayton, OH • On-site, Remote

$94K - $164K/yr

Full-time

Re-posted 14 days ago

CareSource rating

7.7

Company rating: 7.7 out of 10

Based on 28 frontline employees who took The Breakroom Quiz

200th of 304 rated insurance

Job description

Job Summary:
The AI Developer plays a key role in designing, developing, and deploying intelligent solutions. This role is focused on solving complex business challenges through innovative AI technologies and will collaborate closely with cross-functional teams to ensure timely and high-quality delivery of solutions aligned with defined objectives.
DS/Gen/Agentic AI resources with good hands-on skills on:
  • Current Advancements: Generative AI, Agentic AI, LLM fine-tuning, RAG, GraphRAG, Vector databases, Knowledge Graph, Langchain, Langgraph, etc
  • Model Deployment: MLOPs pipeline, CI/CD, Model Deployment, Docker, Kubernetes, Azure Cloud, Github, etc
  • Core Skills: Traditional AI / ML / Data Science skillsets (Predictive, Prescriptive, Descriptive, Statistical, Optimization, Simulation, Natural Language processing, Computer Vision, Image Processing, etc)
  • Domain: Healthcare, Facets, GuidingCare, etc

Note: Domain skills are nice to have and not mandatory.
Essential Functions:
  • Design and implement AI models and algorithms tailored to diverse business challenges
  • Define and lead the architecture of Generative AI platforms, including large language models (LLMs), vector databases, and inference pipelines
  • Maintain deep expertise in modern generative AI technologies such as Knowledge Graphs, OpenAI, LLaMA, Python, LangChain, vectorization, embeddings, semantic search, Retrieval-Augmented Generation (RAG), Infrastructure as Code (IaC), and Streamlit
  • Rapidly prototype proof-of-concept solutions to assess emerging technologies and innovative ideas
  • Foster innovation and collaboration in a fast-paced environment through a hands-on, imaginative approach and a self-driven, inquisitive mindset
  • Leverage AI-assisted development tools, including GitHub Copilot and internally developed solutions, to enhance productivity
  • Apply creative problem-solving techniques to identify and implement process improvements
  • Assess technical risks and develop effective mitigation strategies to ensure successful project delivery
  • Collaborate with data scientists, software engineers, and product teams to integrate AI capabilities into production-ready systems
  • Partner with leadership to evaluate existing services and develop strategies to optimize delivery and support
  • Perform data preprocessing and analysis on large datasets to uncover actionable insights
  • Train, validate, and fine-tune machine learning and deep learning models for optimal performance
  • Deploy models using cloud infrastructure and containerization technologies such as Docker and Kubernetes
  • Implement and manage MLOps pipelines to automate model training, deployment, monitoring, and lifecycle management
  • Apply AIOps practices to enhance operational efficiency, automate incident detection, and optimize system performance using AI-driven insights
  • Continuously monitor model performance and retrain as needed to maintain accuracy and relevance
  • Stay current with industry trends, tools, and frameworks, and assess their applicability to organizational goals
  • Document workflows, models, and codebases to support maintainability and knowledge sharing
  • Provide timely and transparent progress updates to stakeholders, highlighting key milestones, challenges, and proposed solutions
  • Perform any other job duties as requested

Education and Experience:
  • Bachelor's degree in Computer Science, Data Science, Artificial Intelligence or related field, or equivalent years of relevant work experience is required
  • Master's degree is preferred
  • Minimum of five (5) years of experience in developing and deploying AI/ML models is required
  • Experience with cloud platforms (AWS, Azure, GCP) and MLOps tools Is required
  • Experience with Agile methodologies is required

Competencies, Knowledge, and Skills:
  • Knowledge of model interpretability and ethical AI practices
  • Proficiency in Python and libraries such as TensorFlow, PyTorch, Scikit-learn, and OpenCV
  • Strong analytical, evaluative and problem-solving abilities
  • Strong understanding of data structures, algorithms, and software engineering principles
  • Excellent problem-solving skills and attention to detail
  • Strong communication and collaboration abilities
  • Knowledge of healthcare and managed care

Preferred Licensure and Certification:
  • AI / Data Science certifications or credentials are preferred

Working Conditions:
  • General office environment; may be required to sit or stand for extended periods of time
  • Occasional travel may be required to meet with stakeholders and development teams

Compensation Range:
$94,100.00 - $164,800.00
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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