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Machine Learning Assistant Jobs in Florida (NOW HIRING)

SkilzMatrix Digital

Machine learning

Eglin Air Force Base, FL · On-site

$51 - $68/hr

Ability to assist DevOps engineers to develop proper Terraform templates used to provision AWS ... Understand business requirements and align technical solutions accordingly. o Continuous Learning:

New

Acclaim

Principal Machine Learning Engineer

Miami, FL · On-site +1

Experienced team, Acclaim is formed by a team of enthusiastic professionals who have created award-winning devices, voice assistants, and other AI-driven products for BigTech corporations * Cutting ...

Barkera

A.I. Specialist (Intern)

Fort Lauderdale, FL · On-site

$14.25 - $19/hr

... machine learning models and algorithms to address specific business challenges and opportunities. - Assist in Implementing and optimizing AI solutions, ensuring scalability, reliability, and ...

Vultus Inc

AI/ML Engineer

Miami, FL · On-site +1

$120K - $150K/yr

Experience building AI-powered chatbots or intelligent assistants. * Relevant certifications in AI, Machine Learning, or Cloud technologies. Salary USD $120,000 - $150,000 per annum (Based on ...

SynthBee, Inc.

Cloud Engineer

Pembroke Pines, FL · On-site

$52.50 - $70.25/hr

... machine learning models, and collaborating with teams to enhance data-intensive applications. Responsibilities : • Assist in cloud system upgrades, security patches, and infrastructure management ...

Disys

Bigdata Engineer

Tampa, FL

$52.75 - $69.75/hr

Deploy the machine learning model and serve its outputs as RESTful API calls. Understand the ... Maintain and improve tools to assist Analytics in ETL, retrospective testing, efficiency ...

Disys - Oak Brook

Bigdata Engineer

Tampa, FL · On-site

$52.75 - $69.75/hr

... machine learning/Big Data • applications using open source tools such as Scala, Java, Python ... tools to assist Analytics in ETL, retrospective testing, efficiency, • repeatability, and R&D ...

The Voleon Group

Executive Assistant

Miami, FL · On-site

$80K - $90K/yr

Voleon is a technology company that applies state-of-the-art AI and machine learning techniques to ... As an Executive Assistant in our newly established Miami office, you will provide dedicated support ...

SynthBee, Inc.

ML Applied Scientist

Pembroke Pines, FL · On-site

Responsibilities : • Contribute as required to the development of SynthBee's machine learning ... Assist in the architectural design of systems, working closely with data engineers and software ...

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Machine Learning Assistant information

What are some common challenges a Machine Learning Assistant may face when supporting data preparation and model training?

Machine Learning Assistants often encounter challenges such as cleaning large, unstructured datasets, identifying and handling missing or inconsistent data, and ensuring data privacy compliance. They also need to communicate effectively with data scientists and engineers to understand project requirements and adapt to evolving priorities. Staying organized and managing multiple tasks simultaneously—such as data preprocessing, feature engineering, and running model experiments—is crucial for success in this role.

What is a Machine Learning Assistant?

A Machine Learning Assistant is a professional who supports the development, implementation, and maintenance of machine learning models and systems. They assist data scientists and engineers by preparing datasets, conducting preliminary data analysis, running experiments, and helping to optimize algorithms. This role often involves coding, testing models, and ensuring the quality and reliability of machine learning solutions. Machine Learning Assistants play a key role in streamlining workflows and enabling faster progress in AI projects.

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

To thrive as a Machine Learning Assistant, a solid background in mathematics, statistics, programming (often Python), and foundational knowledge of machine learning algorithms is essential, typically supported by a relevant degree or coursework. Familiarity with tools like TensorFlow, scikit-learn, Jupyter Notebooks, and version control systems such as Git is commonly required. Strong problem-solving abilities, attention to detail, and the capability to communicate findings effectively are standout soft skills in this role. These skills ensure accurate data analysis, effective model building, and successful collaboration within multidisciplinary teams.
What are the most commonly searched types of Machine Learning jobs in Florida? The most popular types of Machine Learning jobs in Florida are:
What are popular job titles related to Machine Learning Assistant jobs in Florida? For Machine Learning Assistant jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Machine Learning Assistant jobs in Florida look for? The top searched job categories for Machine Learning Assistant jobs in Florida are:
What cities in Florida are hiring for Machine Learning Assistant jobs? Cities in Florida with the most Machine Learning Assistant job openings:
Machine Learning Assistant jobs near you
Infographic showing various Machine Learning Assistant job openings in Florida as of July 2026, with employment types broken down into 91% Full Time, and 9% Contract. Highlights an 100% In-person job distribution.

Machine learning

SkilzMatrix Digital

Eglin Air Force Base, FL • On-site

$51 - $68/hr

Other

Posted yesterday

Job description

MLOPS
office locations (Pittsburgh, PA, Cleveland, OH, Dallas, TX, Birmingham, AL or Phoenix, AZ,). 
 
 
Technical Skills:
o Amazon SageMaker: In-depth knowledge of SageMaker, including domain setup, configuration, and infrastructure management.
o Cloud Knowledge: A deep understanding of cloud computing concepts, especially related to Amazon Web Services (AWS).
o Infrastructure Design: Ability to design and implement MLOPs cloud solutions, considering scalability, security, and performance.
o Experience: Practical firsthand experience with cloud MLOps and Data Analytics platforms, preferably AWS SageMaker, Glue, EMR, Athena.
o Best Practices: Familiarity with best practices for MLOps and Data Engineering.
o EC2 Instances: Understanding of EC2 instance types and their suitability for AWS SageMaker.
o S3: Proficiency in using Amazon S3 for data storage and SageMaker input/output.
o IAM: Ability to manage permissions and access control using Identity and Access Management.
o Lambda: Knowledge of serverless computing for automating tasks.
o ML & Data Pipelines: Experience with creating data pipelines using AWS SageMaker services integrated with Glue and EMR.
o Monitoring and Troubleshooting: Proficiency in monitoring SageMaker cluster health, identifying bottlenecks, and resolving issues.
o Cost Optimization: Strategies to tag SageMaker resources with an eye on optimizing costs and observability.
Security and Compliance:
o Encryption: Understanding of data encryption at rest and in transit to ensure secure data analytics cloud environment.
o Security Groups and VPC: Knowledge of network security and virtual private clouds.
o Compliance Controls: Ensuring compliance with industry standards and regulations.
Scripting and Automation:
o Language Proficiency: Python, R, Spark, SQL in scripting languages for automating tasks.
o MLOPs: Ability to collaborate with the business to optimize MLOps process, and model lifeycle using SageMaker
o Infrastructure as Code (IaC): Ability to assist DevOps engineers to develop proper Terraform templates used to provision AWS analytics infrastructure.
Backup and Disaster Recovery:
o Snapshotting: Familiarity with taking EMR cluster snapshots for backup and recovery.
o High Availability: Implementing strategies for fault tolerance and disaster recovery.
Soft Skills:
o Communication: Effective communication with stakeholders, developers, and data engineers.
o Problem-Solving: Analytical thinking to address complex issues.
o Adaptability: Keeping up with evolving technologies and best practices.
o Decisiveness: Make informed decisions, especially when dealing with complex architectural choices.
o Business Acumen: Understand business requirements and align technical solutions accordingly.
o Continuous Learning: A zeal for staying updated with evolving cloud technologies.
o
Experience and Certifications:
o Experience: Senior AWS Cloud Engineers must have 3 to 5 years of firsthand experience in designing and building cloud MLOps and Data Analytics applications.
o Certifications: AWS Professional Developer or Data certifications are desired for senior roles
 

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