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Remote Embedded Machine Learning Jobs in Ohio (NOW HIRING)

Location Remote in Europe. Albatross At Albatross, we're building the second pillar of AI: a ... Design and implement machine learning models for ranking, recommendation, and personalization ...

... remote management * Experience in low-power design and optimization * Understanding of cybersecurity best practices for embedded systems Nice-to-Have Skills * Experience with vending machine ...

Systems Engineer

Dayton, OH ยท On-site +1

This position will support development of a data architecture and machine learning experimentation ... This role is based in Dayton, Ohio with the possibility of remote work. Requirements U.S.

Remote Job Summary Join our client's team as a Data Scientist and play a pivotal role in ... Background in developing and deploying machine learning solutions in production settings. #J-18808 ...

Senior AI/ML Engineer

Columbus, OH ยท Remote

$90 - $100/hr

Remote Our client seeks a Senior AI/ML Engineer to design and deliver cloud-native machine learning solutions on AWS. The role includes LLM orchestration, RAG pipelines, vector database integration ...

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Remote Embedded Machine Learning information

What are the key skills and qualifications needed to thrive as a Remote Embedded Machine Learning Engineer, and why are they important?

To thrive as a Remote Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer science, electrical engineering, or related fields. Familiarity with microcontrollers, edge AI frameworks (such as TensorFlow Lite or Edge Impulse), and version control systems is typically required. Strong problem-solving skills, effective communication, and self-motivation are essential soft skills for collaborating remotely and troubleshooting complex issues. These skills ensure successful deployment of intelligent solutions on resource-constrained devices and effective teamwork in distributed environments.

What are some common challenges faced by Remote Embedded Machine Learning Engineers, and how can they be addressed?

Remote Embedded Machine Learning Engineers often encounter challenges related to hardware access, debugging embedded devices remotely, and collaborating with cross-functional teams across time zones. To address these, it's important to set up robust remote development environments, use simulation tools when physical hardware isn't available, and establish clear communication channels for effective teamwork. Regular virtual meetings and detailed documentation also help ensure alignment and smooth progress, despite the remote nature of the work.

What is a Remote Embedded Machine Learning Engineer?

A Remote Embedded Machine Learning Engineer is a professional who develops and deploys machine learning models on embedded systems like microcontrollers, IoT devices, and edge hardware, all while working remotely. Their work involves optimizing algorithms to run efficiently on devices with limited computing power, memory, and battery life. These engineers typically use frameworks such as TensorFlow Lite or TinyML to design intelligent features that operate directly on hardware, enabling real-time decision-making without relying heavily on cloud connectivity. They collaborate with cross-functional teams and often troubleshoot both software and hardware issues from a remote location.

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

AspectRemote Embedded Machine LearningRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Electrical Engineering, or related fields; experience with embedded systems and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in data analysis and ML algorithms
Work EnvironmentEmbedded hardware devices, IoT systems, real-time processing environmentsCloud platforms, data analysis labs, remote offices
Employer & Industry UsageTech companies, IoT device manufacturers, automotive, roboticsFinance, healthcare, marketing, tech firms

Remote Embedded Machine Learning specialists focus on integrating ML models into embedded hardware for real-time applications, often working with IoT and robotics. In contrast, Remote Data Scientists analyze large datasets to extract insights, primarily working in cloud or office environments. Both roles require strong analytical skills but differ in technical focus and work settings.

What are popular job titles related to Remote Embedded Machine Learning jobs in Ohio? For Remote Embedded Machine Learning jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Remote Embedded Machine Learning jobs in Ohio look for? The top searched job categories for Remote Embedded Machine Learning jobs in Ohio are:
What cities in Ohio are hiring for Remote Embedded Machine Learning jobs? Cities in Ohio with the most Remote Embedded Machine Learning job openings:
Lead Data Scientist - US Remote

Lead Data Scientist - US Remote

Hexion, Inc.

Columbus, OH โ€ข On-site, Remote

Other

Posted 9 days ago


Job description

Company Overview
ย 

Imagine Everything. Build the Future with Hexion.

At Hexion, we push boundaries, rethink possibilities, and create real impact. We activate science to deliver progress-developing breakthrough solutions that strengthen industries, protect communities, and drive a more sustainable future.

This is where bold thinkers, problem-solvers, and innovators come together to shape what's next. Whether you're engineering advanced materials, transforming manufacturing technologies, or leading strategic innovation, your ideas and actions leave a lasting mark. We cultivate an inclusive culture of growth, collaboration, and accountability, ensuring every contribution propels us forward.

We don't follow the status quo-we challenge it, disrupt it, and improve it.ย Every role at Hexion is part of something bigger.

We invest in innovation, sustainability, and continuous development-equipping you with the tools, training, and opportunities to excel. With an unwavering commitment to safety, partnership, belonging, and impact, we empower you to lead change and strengthen industries worldwide.

Your Future Starts Here. ย 

If you're ready to push limits, reimagine what's possible, and create the extraordinary, Hexion is where you belong.ย 

Anything is possible when you imagine everything.ย 

Job Responsibilities
  • Lead complex data science and machine learning initiatives supporting supply chain, manufacturing operations, capacity planning, demand forecasting, and operational decision-making.ย 
  • Design, develop, and own advanced ML solutions - including predictive models, time-series forecasting, optimization, and decision-support systems - scoped to supply chain and manufacturing use cases.ย 
  • Build, train, evaluate, and interpret machine learning models (regression, classification, clustering, forecasting) to quantify supply chain drivers, surface optimization opportunities, and improve operational outcomes.ย 
  • Develop and operationalize analytics and ML solutions using Databricks (Python / SQL / PySpark) for large-scale data processing, model development, and experimentation.ย 
  • Design and build multi-agent AI systems - including orchestrator-executor architectures, tool-calling agents, and RAG-based decision support - using frameworks such as Azure AI Foundry, AutoGen, Semantic Kernel, or LangChain/LangGraph.ย 
  • Implement and extend solutions using the MCP to enable AI agents to access and act on enterprise data systems in supply chain and manufacturing contexts.ย 
  • Apply data science best practices including feature engineering, model validation, performance monitoring, reproducibility, and documentation.ย 
  • Partner with Supply Chain & Procurement leadership, Manufacturing Ops, Process Engineering, Demand Planning, and IT to translate ambiguous business problems into structured ML and AI approaches.ย 
  • Develop and maintain self-service, automated, and AI-enabled analytics workflows that reduce manual effort and improve decision latency.ย 
  • Leverage Azure AI Foundry, Microsoft Copilot Studio, and Microsoft 365 Copilot extensibility to prototype and deploy AI-powered analytics and agent-based decision-support tools.ย 
  • Produce executive-ready insights through clear storytelling, visualizations, and recommendations using Power BI or embedded analytics.ย 
  • Set technical direction, establish reusable ML and AI frameworks, and mentor junior and mid-level data scientists across the team.ย 
  • Ensure high standards of data quality, governance, model validation, and explainability.ย 
Minimum Qualifications

Education & Experience (one of the following):ย 

  • Master's degree in Statistics, Mathematics, Industrial Engineering, Data Science, Computer Science, Engineering, or a related quantitative field with 5+ years of relevant data science/analytics experience, ORย 
  • Bachelor's degree in the same or related fields with 8+ years of relevant data science / analytics experience.ย 


Technical:ย 

  • Demonstrated track record delivering advanced ML and data science solutions in supply chain, manufacturing, or industrial domains.ย 
  • Strong hands-on experience with machine learning and statistical modeling - development, interpretation, and operational business application.ย 
  • Strong proficiency in Databricks (Python, SQL, PySpark, Delta Lake).ย 
  • Hands-on experience with the MCP - building or consuming MCP servers/clients to connect AI agents to enterprise data systems, APIs, or ERP modules.ย 
  • Hands-on experience with multi-agent system design - architecting multi-agent systems using AutoGen, Semantic Kernel, LangChain/LangGraph, or Azure AI Agent Service; orchestrator-executor patterns, tool calling, memory management, and agent coordination.ย 
  • Compulsory - must have hands-on experience with one or more of the following:ย 
    • Azure AI Foundryย 
    • Microsoft Copilot Studioย 
    • Microsoft 365 Copilot extensibilityย 
    • Microsoft Power Platform (Power Automate, Power BI)ย 
  • Ability to translate complex business problems into ML / AI solutions and communicate findings to both technical and executive audiences.ย 
  • Strong stakeholder management and cross-functional collaboration skills.ย 
Preferred Qualifications
  • Experience operationalizing ML models into production in supply chain or manufacturing environments.ย 
  • Familiarity with SAP ECC / S/4HANA supply chain and manufacturing modules (MM, PP, PM, SD).ย 
  • Strong Power BI experience - semantic modeling, performance optimization, executive dashboard design.ย 
  • Exposure to MLOps on Azure (Azure ML, MLflow, Databricks Asset Bundles, CI/CD for analytics artifacts).ย 
  • Experience designing operational KPI frameworks (MAPE, OTIF, service level, OEE, downtime).ย 
  • Experience with statistical / simulation methods (Monte Carlo, scenario analysis, sensitivity analysis) applied to operations and supply chain.ย 
  • Familiarity with Palantir Foundry (pipelines, ontology, Workshop, AIP).ย 
  • Proven experience mentoring data scientists or leading end-to-end analytics initiatives.ย 
  • Familiarity with cloud-native data architectures and governed data platforms.ย 
Other
ย 

We are an Equal Opportunity, Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to gender, pregnancy, race, national origin, religion, age, sexual orientation, gender identity, veteran or military status, status as a qualified individual with a disability or any other characteristic protected by law.

To be considered for this position candidates are required to submit an application for employment through our career site and, be at least 18 years of age. ย Any offer of employment will be conditioned upon successful completion of a drug test and background investigation, as well as authorization for the Company to conduct additional periodic background checks as required by the Chemical Facility Anti-Terrorism Standards (CFATS) or regulations adopted by the department of Homeland Security or other regulatory agencies. A prior criminal record is not an automatic bar to employment, and the Company will conduct an individualized assessment and reassessment, consistent with applicable law, prior to making any final employment decision.