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Remote Aws Machine Learning Jobs in Florida (NOW HIRING)

Machine Learning & Operations Engineer

Miami, FL · Remote

$66.50K - $89.90K/yr

This is a fully remote position, working cross-functionally with research and engineering teams ... Experience with cloud platforms (AWS, GCP, or Azure) * Strong understanding of automation ...

Enterprise Cloud Architect

Fort Myers, FL · Remote

$54.15 - $70.39/hr

Remote - Florida Department: IS Information Technology Svcs Work Type: Full Time Shift: Shift 1/8 ... Azure AI Engineer Associate or AWS Machine Learning Specialty Why Join Lee Health * Be part of a ...

Enterprise Cloud Architect

Fort Myers, FL · On-site +1

$54.15 - $70.39/hr

Remote - Florida Department: IS Information Technology Svcs Work Type: Full Time Shift: Shift 1/8 ... Azure AI Engineer Associate or AWS Machine Learning Specialty Why Join Lee Health * Be part of a ...

Cloud Engineer

Fort Myers, FL · On-site +1

$78.46K - $101.98K/yr

Remote - Florida Department: IS Information Technology Svcs Work Type: Full Time Shift: Shift 1/8 ... AWS Certified Machine Learning Engineer * Microsoft Azure Security Certification Preferred ...

Cloud Engineer

Fort Myers, FL · On-site +1

$78.46K - $101.98K/yr

Remote - Florida Department: IS Information Technology Svcs Work Type: Full Time Shift: Shift 1/8 ... AWS Certified Machine Learning Engineer * Microsoft Azure Security Certification Preferred ...

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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, and why are they important?

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 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 remote AWS Machine Learning jobs?

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 the most commonly searched types of Aws Machine Learning jobs in Florida? The most popular types of Aws Machine Learning jobs in Florida are:
What job categories do people searching Remote Aws Machine Learning jobs in Florida look for? The top searched job categories for Remote Aws Machine Learning jobs in Florida are:
What cities in Florida are hiring for Remote Aws Machine Learning jobs? Cities in Florida with the most Remote Aws Machine Learning job openings:
Machine Learning Scientist - Remote

Machine Learning Scientist - Remote

Tower Hill Insurance Group LLC

Gainesville, FL • On-site, Remote

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 14 days ago


Job description

Description

Tower Hill Insurance Group has an exciting opportunity for a talented Machine Learning Scientist who enjoys intellectual challenges and is seeking a rewarding career with a company that is experiencing growth. Not only is Tower Hill Insurance one of Florida's most trusted names in homeowners insurance, but it offers great opportunities for career advancement and personal growth, along with very competitive benefits and rewards. We are growing at a consistent pace and seek professional individuals with drive, team mentality, who want to make an impact, and are committed to a long-term career in the insurance industry.       


The Machine Learning (ML) Scientist develops actionable insights and recommendations in support of business objectives using in-house and external data sources. This position utilizes problem-solving skills to collaborate with business and data engineering professionals for timely and reliable delivery of data solutions. This role leverages the team's deep expertise in data engineering, data science, advanced analytics, and insurance industry data to aid business partners in risk management, drive efficiencies, and improve customer experience.


ESSENTIAL DUTIES AND RESPONSIBILITIES

  • Partner with business stakeholders to scope, structure, and drive analytical projects from requirements through delivery. Present findings and recommendations clearly to both technical and non-technical audiences.
  • Source, validate, and integrate structured and unstructured data across platforms. Conduct exploratory data analysis to reveal data quality issues and identify opportunities.
  • Analyze business trends, time series patterns, model performance, and causal relationships using advanced statistical and machine learning / deep learning methods to inform strategic decisions.
  • Design, build, and deploy machine learning / deep learning models - including NLP, computer vision, and LLM-based solutions - from rapid prototyping through production deployment.
  • Create visualizations, dashboards, and reports that communicate analytical and model results to support decision-making across the organization.
  • Own and maintain recurring analytical, reporting, and model-monitoring processes.
  • Document data pipelines, model architecture, analytical frameworks, and deliverables for knowledge sharing across technical and non-technical teams.


ADDITIONAL DUTIES

This job description reflects the general duties considered necessary to describe the essential functions of the job and should not be considered a complete description of all the work requirements and expectations of the position. Tower Hill reserves the right to assign duties not listed herein as necessary to accomplish the goals of the organization.


Requirements

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.


EDUCATION

High School Diploma or GED required. Bachelor's Degree in Computer Science, Statistics, Mathematics, Engineering, or related field required. Master's Degree or higher preferred. 


EXPERIENCE

Minimum of five (5) years of relevant work experience in machine learning and/or deep learning required, including the following:

  • Advanced Proficiency in Python. 
  • Demonstrated ability to build and deploy ML models using frameworks such as scikit-learn, PyTorch, Hugging Face Transformers.
  • Experience working with cloud data platforms and warehouses (e.g., Snowflake, PostgreSQL) and cloud storage (e.g., S3).Strong written and verbal communication skills with the ability to present complex technical concepts and insights to non-technical stakeholders.
  • Proven ability to work independently, drive projects forward with minimal oversight, and execute in stakeholder-facing environments. 


The following work experience is highly preferred: 

  • Experience with deep learning, NLP, computer vision, or large language model development and deployment.
  • Hands-on experience with statistical methods (hypothesis testing, regression, causal inference), exploratory techniques (clustering, PCA), anomaly detection, forecasting, and time series analysis.
  • Experience with data processing at scale using PySpark, Pandas, or similar libraries to clean, transform, and integrate data from multiple sources.
  • Experience with visualization tools such as Power BI, matplotlib, seaborn, or plotly.
  • Familiarity with API development and deployment using frameworks such as FastAPI.
  • Experience with AWS services such as SageMaker, S3, Lambda, or Glue.
  • Property and casualty insurance or financial services industry work experience including regulatory standards and best practices is a plus. 


CERTIFICATIONS

AWS Certifications in AI or ML preferred.


LICENSES

N/A

*Tower Hill currently operates in a hybrid work environment and may consider candidates located outside of our established office locations. We are presently open to hiring in the following states CT, FL, GA, IA, IN, KY, MI, MS, NC, OH, SC, TN, TX, UT, VA, WV.   


Applicants must be legally authorized to work in the U.S. without the need for current or future visa sponsorship.  


Preferred work arrangement hybrid on-site, but remote candidates will be considered based on qualifications and experience. 


BENEFITS

  • Medical
  • Dental
  • Vision
  • Life & Disability Insurance
  • 401(k)
  • Health Savings Account
  • Accident, Critical Illness and Hospital Indemnity
  • Pet insurance
  • Paid time off & Holiday pay

We offer competitive pay and benefits, and well-being programs to support you and your family. For more information about our company, careers and Total Compensation visit:   Total Compensation - Tower Hill Insurance (thig.com) 


Tower Hill Insurance is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.


Tower Hill Insurance is committed to working with and providing reasonable accommodation for individuals with disabilities. If you need reasonable accommodation because of a disability for any part of the employment process, please send an e-mail to hrdepartment@thig.com and let us know the nature of your request and your contact information.


All applicants will receive an acknowledgement that their application has been received. Candidates will not receive status updates regarding their application; however, those candidates selected for further consideration will be contacted by Human Resources.