2

Remote Aws Machine Learning Jobs in Riverside, CA

Data Scientist II

Irvine, CA · On-site +1

$82K - $127K/yr

Support deployment and lifecycle management of models within Azure Machine Learning, AWS, or ... Remote Equal Opportunity Employer This employer is required to notify all applicants of their ...

... machine learning within a cloud environment such as Azure, AWS, or similar platforms. This role ... This position is open to remote or hybrid. ESSENTIAL FUNCTIONS & RESPONSIBILITIES: * Design, build ...

Senior Software Engineer, MLOps

Irvine, CA · On-site +1

$131K - $173K/yr

... machine learning pipelines. * Hands-on experience with cloud and cloud-native tools such as AWS ... Also, while we enjoy being together on-site, we are open to exploring a hybrid or remote option.

Senior Software Engineer, MLOps

Irvine, CA · On-site +1

$131K - $173K/yr

... machine learning pipelines. * Hands-on experience with cloud and cloud-native tools such as AWS ... Also, while we enjoy being together on-site, we are open to exploring a hybrid or remote option.

AI SOFTWARE ENGINEER

Anaheim, CA · Remote

$80K - $100K/yr

Build, ship, and iterate on AI-powered features end to end Design and deploy machine learning ... Remote Pay: $80,000 - $100,000 Benefits: * PTO * Health / Dental / Vision Employment Type ...

next page

Showing results 1-20

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

Data Scientist II

Corvel

Irvine, CA • On-site, Remote

$82K - $127K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 21 days ago


CorVel rating

7.9

Company rating: 7.9 out of 10

Based on 51 frontline employees who took The Breakroom Quiz

81st of 139 rated financial services


Job description

We have an exciting opportunity for a Data Scientist within our data product space. This individual will be focused on designing, building, and deploying machine learning models and data products that support our enterprise initiatives. This role focuses on developing scalable, production ready solutions by translating complex business problems into data-driven approaches and model-based outputs.
Working closely with product managers, engineering teams, and business stakeholders, this position contributes to the development of data products from concept through deployment, ensuring solutions are reliable, performant, and aligned with real world use cases. The role includes hands on model development, feature engineering, and integration into production systems within cloud environments.
The ideal candidate has experience building and operationalizing machine learning models and is comfortable working with modern AI techniques, including large language models (LLMs) and retrieval-augmented generation (RAG), where applicable. Experience with platforms such as Azure, AWS, or similar ecosystems is strongly preferred.
Success in this role requires strong technical expertise, problem-solving skills, and the ability to deliver high-quality solutions within a structured development environment. This role focuses on building and deployment of production data products and is not limited to exploratory analysis or reporting.
This position is open to remote or hybrid.
ESSENTIAL FUNCTIONS & RESPONSIBILITIES:
  • Mine and analyze data from internal databases to drive optimization and improvement of product development and business strategies
  • Creating new, experimental frameworks to collect data
  • Building tools to automate data collection
  • Develop custom data models and algorithms to apply to data sets
  • Design, build, train, and deploy machine learning models and data products for enterprise use
  • Translate business and operational needs into scalable data science solutions and modeling approaches
  • Perform feature engineering, data preparation, and exploratory analysis to support model development
  • Develop and evaluate models using appropriate techniques (e.g., classification, regression, NLP, optimization)
  • Contribute to the design of data products, including model outputs, APIs, and integration into downstream systems
  • Support advanced AI use cases, including LLM-based solutions, retrieval-augmented generation (RAG), and hybrid modeling approaches where appropriate
  • Collaborate with engineering teams to integrate models into production environments using APIs, pipelines, and cloud services
  • Support deployment and lifecycle management of models within Azure Machine Learning, AWS, or similar platforms
  • Perform model validation, testing, and documentation to ensure quality and reproducibility
  • Contribute to technical design discussions and provide input on architecture and implementation strategies
  • Work within the full software development lifecycle (SDLC), including version control, testing, and release processes
  • Communicate model behavior, assumptions, and results clearly to technical and non-technical stakeholders
  • Develop A/B testing framework and test model quality
  • Passion for technology and emerging AI/ML trends
  • Additional duties as assigned

KNOWLEDGE & SKILLS:
  • Strong problem-solving skills with an emphasis on product development.
  • Strong foundation in machine learning, statistical modeling, and data science techniques
  • Experience building and deploying machine learning models in production environments
  • Familiarity with modern AI approaches, including:
    • Natural language processing (NLP)
    • Large language models (LLMs)
    • Retrieval-Augmented Generation (RAG)
    • Feature engineering and model evaluation techniques
  • Experience working with cloud platforms such as Azure, AWS, or similar ecosystems
  • Familiarity with data pipelines, APIs, and integration patterns
  • Proficiency in programming languages such as Python and database management including SQL
  • Strong problem-solving skills with the ability to structure complex problems into analytical solutions
  • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.), their real-world advantages/drawbacks and experience with applications
  • Excellent presentation and written/verbal communication skills

EDUCATION & EXPERIENCE:
  • Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical field; Master's preferred
  • 2-5+ years of experience in data science, machine learning, or related roles
  • Experience developing and deploying machine learning models in production environments
  • Experience with cloud-based ML platforms such as Azure Machine Learning, AWS SageMaker, or similar
  • Exposure to AI platforms such as Azure OpenAI, AWS Bedrock, or similar technologies preferred
  • Experience working within enterprise software environments and SDLC practices preferred

PAY RANGE:
CorVel uses a market based approach to pay and our salary ranges may vary depending on your location. Pay rates are established taking into account the following factors: federal, state, and local minimum wage requirements, the geographic location differential, job-related skills, experience, qualifications, internal employee equity, and market conditions. Our ranges may be modified at any time.
For leveled roles (I, II, III, Senior, Lead, etc.) new hires may be slotted into a different level, either up or down, based on assessment during interview process taking into consideration experience, qualifications, and overall fit for the role. The level may impact the salary range and these adjustments would be clarified during the offer process.
Pay Range: $82,574 - $127,490
A list of our benefit offerings can be found on our CorVel website: CorVel Careers | Opportunities in Risk Management
In general, our opportunities will be posted for up to 1 year from date of posting, or until we have selected candidate(s) to fulfill the opening, whichever comes first.
About CorVel
CorVel, a certified Great Place to Work® Company, is a national provider of industry-leading risk management solutions for the workers' compensation, auto, health and disability management industries. CorVel was founded in 1987 and has been publicly traded on the NASDAQ stock exchange since 1991. Our continual investment in human capital and technology enable us to deliver the most innovative and integrated solutions to our clients. We are a stable and growing company with a strong, supportive culture and plenty of career advancement opportunities. Over 4,000 people working across the United States embrace our core values of Accountability, Commitment, Excellence, Integrity and Teamwork (ACE-IT!).
A comprehensive benefits package is available for full-time regular employees and includes Medical (HDHP) w/Pharmacy, Dental, Vision, Long Term Disability, Health Savings Account, Flexible Spending Account Options, Life Insurance, Accident Insurance, Critical Illness Insurance, Pre-paid Legal Insurance, Parking and Transit FSA accounts, 401K, ROTH 401K, and paid time off.
CorVel is an Equal Opportunity Employer, drug free workplace, and complies with ADA regulations as applicable.
#LI-Remote
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.

What CorVel employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom