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Junior Aws Machine Learning Jobs in Florida (NOW HIRING)

Machine learning

Eglin Air Force Base, FL · On-site

$51 - $68/hr

A deep understanding of cloud computing concepts, especially related to Amazon Web Services (AWS ... Understand business requirements and align technical solutions accordingly. o Continuous Learning:

New

Sr Machine Learning Engineer

Jacksonville, FL · On-site +1

$113K - $149K/yr

Senior Machine Learning Engineer What you will do Let's do this. Let's change the world. In this ... Leverage cloud platforms (AWS, GCP, Azure) for ML model development, training, and deployment.

... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ... HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets ...

... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ... HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets ...

... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ... HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets ...

... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ... HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets ...

... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ... HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets ...

... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ... HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets ...

... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ... HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets ...

... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ... HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets ...

... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ... HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets ...

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Junior Aws Machine Learning information

What are Junior AWS Machine Learning engineers?

Junior AWS Machine Learning engineers are entry-level professionals who work with Amazon Web Services (AWS) to develop, deploy, and maintain machine learning models. They assist in data preparation, model training, and integration of AI solutions using AWS tools such as SageMaker, Lambda, and S3. These engineers often collaborate with data scientists and software teams to implement predictive analytics and automation solutions on the AWS cloud platform. Their role typically involves learning best practices for cloud security, data handling, and scalable machine learning deployment.

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

To thrive as a Junior AWS Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of machine learning concepts, and a relevant degree in computer science or a related field. Familiarity with AWS services like SageMaker, Lambda, and S3, as well as certifications such as AWS Certified Machine Learning – Specialty, are highly valuable. Strong problem-solving skills, attention to detail, and the ability to communicate technical ideas clearly help you stand out in this role. These skills and qualities are crucial for efficiently developing, deploying, and maintaining machine learning solutions on AWS in collaborative, fast-paced environments.

What are some common challenges faced by Junior AWS Machine Learning Engineers when deploying models to production environments?

Junior AWS Machine Learning Engineers often encounter challenges such as managing the scalability of their models, ensuring data security and compliance in the cloud, and integrating machine learning pipelines with existing AWS services. Since production environments require high reliability, newcomers may also need to learn how to monitor model performance and troubleshoot issues using AWS tools like SageMaker and CloudWatch. Collaborating closely with data engineers and DevOps teams is essential to streamline deployment and maintain model accuracy over time.

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

AspectJunior Aws Machine LearningData Scientist
Required CredentialsBasic AWS certifications, entry-level ML knowledgeAdvanced degrees, certifications like AWS, data analysis skills
Work EnvironmentCloud platforms, machine learning projects, collaborative teamsData analysis, modeling, research, cross-functional teams
Employer & Industry UsageTech companies, startups, cloud service providersFinance, healthcare, tech, research institutions

Junior AWS Machine Learning roles focus on implementing ML models using AWS tools with foundational knowledge, while Data Scientists typically handle broader data analysis, modeling, and research tasks. The roles overlap in cloud-based ML work but differ in scope and experience level.

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 Junior Aws Machine Learning jobs in Florida look for? The top searched job categories for Junior Aws Machine Learning jobs in Florida are:
What cities in Florida are hiring for Junior Aws Machine Learning jobs? Cities in Florida with the most Junior Aws Machine Learning job openings:

Machine Learning Engineer

ENSCO, Inc.

Melbourne, FL

Other

Re-posted 8 days ago


Job description

ENSCO, Inc. is seeking a Machine Learning Engineer with direct experience and applications with using Machine Learning (ML) and Deep Learning (DL) models, frameworks, architectures, pipelines, and advanced data analytics, to address difficult problem sets.  Work closely with other senior scientist to understand problem sets, physical data feature sets and parameters.  The successful candidate must have demonstrated understanding of signal processing, data fusion, feature extraction, and be able to apply it towards ML and DL solutions.  Assess algorithm performance of features by building datasets and designing and executing well-controlled experiments.
ENSCO's Mission Systems Group (MSG) provides innovative customized products and services vital to national safety and security.  A primary focus area is the development of advanced algorithm development and integration for multipurpose data sets.
 

Qualifications Required:
        Bachelors degree in Machine Learning, Data Science, Mathematics, or equivalent in a related discipline.  Direct relevant military experience will also be considered.
        Minimum of 3 years related industry experience in machine learning, data science, and analytics.
        Proven track record of successful data science and algorithm implementation.
        Provide mentorship to junior ML engineers.
        A self-starter with excellent oral and written communication skills.
        Experience navigating and programming within the Linux environment.
        Experience working with structured and unstructured databases.
        Advanced proficiency with data science languages (e.g. Python, Matlab,)
        Demonstrated experience with Deep Learning frameworks (e.g. PyTorch, TensorFlow/Keras, scikit-learn, MXNet).
        Experience working with large data sets and ability to extract relevant information from data sets.
         The ability to obtain and maintain a US security clearance is required for this position, for which you must be a U.S. Citizen

Qualifications Desired:
        Masters or PhD degree in Machine Learning, Data Science, or Mathematics, or equivalent.
        Experience with ML/DL algorithms extracting signal from noise.
        Past experience being able to develop solutions using disparate data sets through ML techniques.
        DevOps experience involving CI/CD pipelines to build and deploy.
        Experience working with container orchestration technologies (e.g. Docker/Kubernetes).
        An Active TS/SCI clearance.
 

Work Location Type: Hybrid
Required Certifications: None
U.S. Citizenship Required: Yes
Security Clearance Required: Ability to obtain
Employment Type: Regular Full-time
Background Check Type:  7 Year Pre-Employment
Drug Screen Required: None
Position Contingent Upon Contract Award: Yes