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Junior Aws Machine Learning Jobs in Utah (NOW HIRING)

Senior Machine Learning Engineer

Sandy, UT · Hybrid

$99K - $136K/yr

As Senior Machine Learning Engineer, you will own the evaluation and optimization of speech ... Experience with cloud-based infrastructure (AWS, Azure, or GCP). * Ability to develop and maintain ...

Design and develop AI-powered product features using Generative AI, machine learning, and Large ... Cloud platforms such as Microsoft Azure, AWS, or Google Cloud * Serverless and event-driven ...

New

... 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 ...

Senior Machine Learning Engineer

Sandy, UT · On-site

$113K - $150K/yr

As Senior Machine Learning Engineer, you will own the evaluation and optimization of speech ... Experience with cloud-based infrastructure (AWS, Azure, or GCP). * Ability to develop and maintain ...

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Junior Aws Machine Learning information

What is a junior AWS machine learning engineer?

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?

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.

Are there entry level AWS jobs?

Yes, there are entry-level AWS jobs such as Junior AWS Machine Learning roles that typically require foundational knowledge of cloud computing, basic understanding of machine learning concepts, and familiarity with AWS services like S3, EC2, and SageMaker. These roles often serve as starting points for careers in cloud and machine learning fields and may require certifications like AWS Certified Cloud Practitioner or AWS Certified Machine Learning – Specialty. Candidates should be prepared to learn on the job and develop skills through training and hands-on experience.

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 Utah? The most popular types of Aws Machine Learning jobs in Utah are:
What are popular job titles related to Junior Aws Machine Learning jobs in Utah? For Junior Aws Machine Learning jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Junior Aws Machine Learning jobs in Utah look for? The top searched job categories for Junior Aws Machine Learning jobs in Utah are:
What cities in Utah are hiring for Junior Aws Machine Learning jobs? Cities in Utah with the most Junior Aws Machine Learning job openings:

Senior Java Developer[Business Automation & AI]-[lOCAL TO UTAH]

SmartIPlace

Salt Lake City, UT • On-site

$55.50 - $70.75/hr

Contractor

Re-posted 3 days ago


Job description

Position: Senior Java Developer (Business Automation & AI)

Location:  Salt Lake City, Utah, 84111

Interview mode: Onsite interviews

Visa: ANY

 

Interviews will be held onsite.

Hybrid role

Required Technical Skills:

  • Java Mastery: 3-5 years of professional experience with Java (8/11/17+), including Spring Boot or Quarkus.
  • Rule Engines: Hands-on experience writing and debugging Drools rules and implementing DMN (Decision Model and Notation).
  • Cloud Native Automation: Proven experience with Kogito for building cloud-native business processes.
  • AWS AI/ML Stack: Experience configuring AWS Bedrock (Knowledge Bases, Agents, or Prompt Engineering).
  • **Proficiency in managing Amazon S3 for large-scale document storage and metadata tagging.
  • Documentation Transformation: Experience (or strong scripting ability) in converting Adobe RoboHelp (HTML/XML) into structured formats (Markdown/JSON) for AI consumption.
  • Modern DevOps: Experience with Git, CI/CD pipelines, and containerization (Docker/Kubernetes).

 

Preferred Qualifications:

  • Experience with Vector Databases (Amazon OpenSearch, Pinecone, or Milvus).
  • Understanding of Python (specifically for BeautifulSoup/Pandoc-based document parsing).
  • Knowledge of BPMN 2.0 standards.
  • AWS Certified Developer or AWS Machine Learning Specialty certification.

Smart-iPlace logo

About Smart-iPlace

Sourced by ZipRecruiter

SMART-iPLACE provides innovative staffing and consulting solutions that help our clients achieve their business objectives. We can understand and support all areas of your IT systems from back-end infrastructure to front-end personal productivity. Our goal is create innovative IT solutions that enable your business to be more agile and competitive.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Irving, TX, US

Year founded

2021

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