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Executive Aws Machine Learning Jobs in Ohio (NOW HIRING)

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range ... AWS (SageMaker, S3, EC2) * Microsoft Azure ML * Google Cloud AI Platform * Docker * Kubernetes

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range ... AWS (SageMaker, S3, EC2) * Microsoft Azure ML * Google Cloud AI Platform * Docker * Kubernetes

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range ... AWS (SageMaker, S3, EC2) * Microsoft Azure ML * Google Cloud AI Platform * Docker * Kubernetes

The Hartford

AI Machine Learning Engineer

Columbus, OH · Hybrid

$100K - $151K/yr

The Hartford is seeking AI Machine Learning Engineer to build Machine Learning Operations (MLOps ... Development experience developing solutions within AWS, GCP or both. Exposure to developing ...

New

The Hartford

Sr AI Machine Learning Engineer

Columbus, OH · Hybrid

$117K - $175K/yr

The Hartford is seeking Senior AI Machine Learning Engineer to build Machine Learning Operations ... Development experience developing solutions within AWS, GCP or both. * Experience developing ...

Hudson Manpower

DATA ENGINEER IV

Cincinnati, OH · On-site

$68 - $70/hr

Must Have Python SQL Nice To Have AWS Sagemaker DBT Snowflake What You'll Do Squad: Machine Learning Data Enablement squad in the Data Insights Tribe Required: In office 4 days a week minimum (Monday ...

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Executive Aws Machine Learning information

What does an Executive AWS Machine Learning professional do?

An Executive AWS Machine Learning professional leads the strategic planning and implementation of machine learning solutions using Amazon Web Services (AWS) within an organization. Their responsibilities often include overseeing teams, aligning machine learning initiatives with business goals, and ensuring that scalable, secure, and cost-effective AWS-based ML services are deployed. They also stay updated on the latest AWS technologies, foster innovation, and communicate with stakeholders to drive digital transformation. This role requires a blend of technical expertise, leadership skills, and business acumen.

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

AspectExecutive Aws Machine LearningData Scientist
Required CredentialsAdvanced AWS certifications, leadership experienceStatistics, programming, data analysis degrees
Work EnvironmentLeadership roles, strategic planning, cloud infrastructureData analysis, model development, research
Employer & Industry UsageTech companies, cloud service providers, enterprisesResearch institutions, tech firms, finance, healthcare
Common Search & ComparisonYesYes

Executive Aws Machine Learning professionals focus on strategic leadership, cloud infrastructure, and overseeing ML projects within organizations, often requiring AWS certifications and leadership skills. Data Scientists primarily analyze data, develop models, and perform research to extract insights. While both roles work with machine learning, the Executive Aws Machine Learning role emphasizes management and cloud expertise, whereas Data Scientists focus on technical data analysis and model building.

What are some common challenges faced by an Executive AWS Machine Learning professional when leading cross-functional teams?

As an Executive AWS Machine Learning professional, a frequent challenge is bridging the gap between data science teams, engineering, and business stakeholders. Ensuring all teams are aligned on project goals, timelines, and technical requirements can be complex, especially when translating machine learning concepts for non-technical audiences. Additionally, managing cloud resource allocation and cost efficiency on AWS while delivering scalable ML solutions requires strategic oversight. Strong communication, project management skills, and a deep understanding of AWS services are essential to successfully lead collaborative, multidisciplinary teams.

What are the key skills and qualifications needed to thrive as an Executive AWS Machine Learning specialist, and why are they important?

To thrive as an Executive AWS Machine Learning specialist, you need deep expertise in machine learning concepts, cloud architecture, and a strong background in computer science or related fields, often supported by advanced degrees or AWS certifications. Familiarity with AWS services like SageMaker, Lambda, and data management tools, along with certifications such as AWS Certified Machine Learning – Specialty, is highly valuable. Leadership, strategic thinking, and the ability to communicate complex technical ideas to both technical and non-technical stakeholders are crucial soft skills. These skills ensure effective development and deployment of scalable ML solutions that align with business goals and drive innovation.
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Executive Aws Machine Learning jobs near you

Machine Learning Engineer Intern

Aivra Health LLC

$28 - $45/hr

Other

Posted 27 days ago

Job description

Machine Learning Engineer Intern

United States
Internship | Full-Time (40 hours/week)
Pay Range: $28 – $45 per hour 
Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome

Position Overview

We are seeking a highly motivated Machine Learning Engineer Intern to join our AI/ML team. This role is ideal for students or entry level candidates in STEM fields who are passionate about building scalable machine learning models and deploying them into production environments.

The intern will work closely with Data Scientists and Software Engineers to develop, train, evaluate, and deploy machine learning models that solve real-world business problems.

Key Responsibilities

  • Assist in building and training machine learning and deep learning models

  • Perform data preprocessing, feature engineering, and exploratory data analysis (EDA)

  • Implement supervised and unsupervised learning algorithms

  • Optimize model performance using hyperparameter tuning

  • Deploy ML models using REST APIs or cloud services

  • Work on model monitoring, validation, and performance tracking

  • Collaborate with cross-functional teams in Agile/Scrum environment

  • Document experiments and maintain reproducible ML workflows

Required Qualifications

  • Currently pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, or related STEM field

  • Strong understanding of Machine Learning fundamentals

  • Knowledge of Probability, Statistics, and Linear Algebra

  • Basic understanding of Data Structures and Algorithms

Technical Skills (ATS Keywords)Programming Languages

  • Python

  • R (preferred)

  • Java (basic knowledge)

  • SQL

Machine Learning & AI Frameworks

  • Scikit-learn

  • TensorFlow

  • Keras

  • PyTorch

  • XGBoost

  • LightGBM

Data Processing & Big Data

  • Pandas

  • NumPy

  • Apache Spark

  • PySpark

  • Hadoop

NLP & Advanced Techniques (Preferred)

  • Natural Language Processing (NLP)

  • Computer Vision

  • Deep Learning

  • Transformers

  • LLM fundamentals

Cloud & MLOps

  • AWS (SageMaker, S3, EC2)

  • Microsoft Azure ML

  • Google Cloud AI Platform

  • Docker

  • Kubernetes

  • MLflow

  • CI/CD pipelines

  • Model Deployment & Monitoring

Tools & Concepts

  • Git

  • REST APIs

  • Feature Engineering

  • Model Evaluation Metrics

  • A/B Testing

  • Agile/Scrum

Preferred Qualifications

  • Prior ML internship or academic research experience

  • Experience deploying models into production

  • Knowledge of MLOps practices

  • Strong problem-solving and analytical skills

  • Good communication and teamwork abilities

Compensation & Benefits

  • Competitive hourly compensation ($28 – $45/hr)

  • Hands-on real-world AI/ML project experience

  • Mentorship from senior ML engineers

  • Opportunity for full-time conversion

  • H1B sponsorship support for eligible candidates

  • STEM OPT extension support

Equal Opportunity Employer

We are an Equal Opportunity Employer and encourage applications from diverse backgrounds, including international students and professionals requiring H1B sponsorship or STEM OPT support.

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