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Remote Full Stack Machine Learning Engineer Jobs in Ohio

.Net Full Stack Web Developer

Blacklick, OH ยท Remote

$8K - $120K/yr

Net Full Stack Developer. Remote job but applicants in Columbus, OH or Arlington, VA preferred ... learning) . . . demonstrate strong verbal and written communication skills and excellent ...

Machine Learning Engineer, Perception

Columbus, OH ยท On-site +1

$100.90K - $138.60K/yr

... learning, and Python programming to tackle challenges in our field alongside our talented teams. What You'll Do Experienced: * Implement, validate, and iterate on machine learning algorithms for weld ...

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Remote Full Stack Machine Learning Engineer information

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

To thrive as a Remote Full Stack Machine Learning Engineer, you need proficiency in programming languages (such as Python or JavaScript), a solid understanding of machine learning algorithms, experience with web development frameworks, and typically a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, Docker, cloud computing platforms (AWS, GCP), and version control systems (Git) is essential. Strong problem-solving skills, self-motivation, and clear communication are crucial soft skills, especially in remote and cross-functional team environments. These combined skills ensure effective design, deployment, and integration of machine learning solutions in scalable web applications while maintaining productivity in a remote setting.

What are some common challenges faced by remote Full Stack Machine Learning Engineers, and how can they be addressed?

Remote Full Stack Machine Learning Engineers often encounter challenges such as managing effective collaboration with cross-functional teams and ensuring smooth deployment of machine learning models into production environments. To address these, it's important to establish clear communication channels, regularly participate in virtual stand-ups, and use collaborative platforms such as GitHub and Slack. Additionally, staying organized with version control and thorough documentation helps maintain project transparency and ensures seamless handoffs between backend and frontend development. Proactively seeking feedback and scheduling regular check-ins with team members can further enhance productivity and integration within the team.

What is a Remote Full Stack Machine Learning Engineer?

A Remote Full Stack Machine Learning Engineer is a professional who designs, develops, and deploys machine learning solutions while working remotely. They handle both the front-end and back-end aspects of machine learning projects, including data preprocessing, model building, API development, and integration with user interfaces or cloud platforms. This role requires expertise in programming, machine learning frameworks, cloud services, and web technologies, allowing them to build end-to-end AI-driven applications from anywhere in the world.

What is the difference between Remote Full Stack Machine Learning Engineer vs Remote Data Scientist?

AspectRemote Full Stack Machine Learning EngineerRemote Data Scientist
Primary FocusDeveloping end-to-end machine learning applications, including backend, frontend, and model deploymentAnalyzing data, creating models, and generating insights without necessarily building full applications
Skills RequiredProgramming (Python, JavaScript), ML frameworks, web development, deployment toolsStatistics, data analysis, visualization, Python/R, SQL
Work EnvironmentCollaborates with developers, data engineers, and product teams in tech-driven companiesWorks with data teams, analysts, and business units in various industries

While both roles involve working with data and machine learning, a Remote Full Stack Machine Learning Engineer builds complete applications with integrated ML models, whereas a Remote Data Scientist focuses on data analysis and model creation without necessarily developing full applications.

What are the most commonly searched types of Full Stack Machine Learning Engineer jobs in Ohio? The most popular types of Full Stack Machine Learning Engineer jobs in Ohio are:
What job categories do people searching Remote Full Stack Machine Learning Engineer jobs in Ohio look for? The top searched job categories for Remote Full Stack Machine Learning Engineer jobs in Ohio are:
What cities in Ohio are hiring for Remote Full Stack Machine Learning Engineer jobs? Cities in Ohio with the most Remote Full Stack Machine Learning Engineer job openings:
Artificial Intelligence / Machine Learning Engineer

Artificial Intelligence / Machine Learning Engineer

Riverside Research

Fairborn, OH โ€ข Remote

$130K - $150K/yr

Full-time

Posted 3 days ago


Job description

Riverside Overview

Riverside Research is an independent National Security Nonprofit dedicated to research and development in the national interest. We provide high-end technical services, research and development, and prototype solutions to some of the countryโ€™s most challenging technical problems. All Riverside Research opportunities require U.S. Citizenship.

Position Overview

Riverside Research is seeking an Artificial Intelligence / Machine Learning Engineer to support existing contracts to prototype and develop automation solutions to NASICโ€™s most difficult Scientific & Technical Intelligence problems. As a highly valued and sought-after Riverside Research employee, you will be part of a highly skilled and integrated team that analyzes intelligence data to discover opportunities for automated solutions.

Must live in or relocate to a commutable distance to Wright Patterson Airforce Base and surrounding areas.

Responsibilities

AI/ML algorithm development for prototype applications in remote sensing:

  • Develop prototype AI/ML algorithms and associated software tools using Python and the Python/TensorFlow API
  • Train AI/ML models and tune their hyperparameters for a given dataset and algorithm objectives
  • Visualize hyperparameter optimization spaces with Tensor board for selection of optimal parameters for a given parametric (functional) TensorFlow model

AI/ML dataset generation, curation, and management:

  • Provide customized solutions to data quality control that ensure accurate functional mappings for AI/ML algorithms on complex remote sensing datasets
  • Develop databases / data lakes / data warehouses for organizing both structured and unstructured datasets

AI/ML algorithm R&D:

  • Apply machine learning and general computer vision best practices and methods to analyze and exploit large, complex remote sensing datasets from a variety of remote sensing phenomenology
  • Keep up with the SoTA practices for AI/ML, perform relevant R&D, and implement new and innovative ideas in machine learning and high-performance computing to solve long-standing remote sensing โ€œbig-dataโ€ exploitation problems

Software development, documentation, and coding best practices:

  • Contribute and adhere to the AI teamโ€™s standards for reviewing and unit-testing code, lead or participate in team-wide code reviews, and adhere to standardized documentation practices
  • Utilize Python PEP8 standards

Qualifications

  • Must have minimum of Secret with able to obtain and maintain a TS/SCI clearance.
  • 5 years and a Bachelorโ€™s Degree in either Electrical Engineering, Mathematics, Statistics, Physics, Computer Science, or related field of study
  • Must demonstrate proficiency in Python-based end-to-end AI/ML model development lifecycle using a recent deep learning platform (TensorFlow preferred)
  • Awareness of version control, branches, merge conflict resolution, and git in general
  • Proficient in collaborative Office 365 tools such as MS Word, Excel, and PowerPoint
  • Ability to work closely with subject-matter experts to develop tools, algorithms, and datasets needed for developing relevant and useful AI/ML prototype algorithms
  • Self-driven, strong analytic, inferencing, critical thinking, and creative problem-solving skills
  • Communicates highly technical results and methods clearly and succinctly

Desired Qualifications:

  • Advanced degree (MS/PhD) in Data Science, Mathematics, Statistics, Computer Science, a Physical Science or Engineering with 10 years of experience is strongly desired
  • Active TS/SCI Security Clearance
  • Experience with DoD intelligence production processes and workflows
  • 3+ years operational experience in radar signal processing analysis, overhead imagery analysis, orbital mechanics, and/or electronic warfare data analysis
  • 2+ years experience using data visualization tools and libraries in Python
  • Visualizations/Web Development Skills (e.g., Tableau, MEAN stack - MongoDB, ExpressJS, AngularJS, NodeJS)
  • Experience with large (1 GB +) image data and formats such as HDF5, JSON, GEOTIFF, TFRecords, etc.
  • Experience in development of distributed, web-based systems, service-oriented architectures, front-end user interfaces, and back-end databases are a plus
  • Experience with interpretability of deep learning computer vision models including visualization and reasoning about model latent spaces and activation maps to assess model effectiveness / weaknesses
  • Familiarity in differences of supervised learning vs. unsupervised learning techniques

Global Comp

$130,000 - $150,000 This represents the typical compensation range for this position based on experience, location and other factors.

Closing Statement

Riverside Research Institute is a not-for-profit, technology-oriented defense company, where service to our customers and support of our staff is our overall mission. Riverside is an affirmative action-equal opportunity employer and complies with all applicable federal, state, and local laws regarding recruitment and hiring. Riverside offers comprehensive compensation and benefit packages to our employees. Riverside bases its employment decisions solely on technical experience, qualifications and other job-related criteria related to our organizational purpose as a not-for-profit company, and without regard to race, color, religion, age, sex marital status, sexual orientation, national origin, physical or mental disability, veteranโ€™s status or any other status legally protected by applicable federal, state, and local law.