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Remote Aws Machine Learning Jobs in Philadelphia, PA

Soni Resources

Data Scientist

Conshohocken, PA · On-site +1

$175K/yr

Remote (Preference for Northeast/Mid-Atlantic; monthly travel to Plymouth Meeting, PA as needed ... Develop predictive models, scoring frameworks, and machine learning solutions that enhance business ...

Gnostech

Software Engineer (US-Remote)

Marlton, NJ · On-site +1

Build and integrate AI-enabled capabilities into applications, including machine learning models ... Experience with cloud platforms such as AWS, Azure, or Google Cloud. * Experience with relational ...

GATE 1 LTD

A.I. Manager

Fort Washington, PA · On-site +1

Build and lead a remote AI team, including recruiting, mentoring, and performance management ... Guide model development, including machine learning, deep learning, NLP, and generative AI ...

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Remote Aws Machine Learning information

What is a remote AWS Machine Learning job?

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 are the key skills and qualifications needed to thrive as a remote AWS Machine Learning engineer?

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 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 popular job titles related to Remote Aws Machine Learning jobs in Philadelphia, PA?

For Remote Aws Machine Learning jobs in Philadelphia, PA, the most frequently searched job titles are:

What job categories do people searching Remote Aws Machine Learning jobs in Philadelphia, PA look for?

The top searched job categories for Remote Aws Machine Learning jobs in Philadelphia, PA are:

What cities near Philadelphia, PA are hiring for Remote Aws Machine Learning jobs?

Cities near Philadelphia, PA with the most Remote Aws Machine Learning job openings:

Remote Aws Machine Learning jobs near you

AWS Technical Labs Developers (Remote)

Philadelphia, PA • Remote

LearnQuest
IT Services • 51 - 200 employees
Learn more about LearnQuestexternal

Full-time

Re-posted 24 days ago

Job description

We are looking for freelance Technical Lab Developers for a full time project work (lasting cca 4 months) to help us build AWS hands-on labs.

The qualified candidate will have experience developing and deploying solutions using cloud-based services, a deep technical knowledge of multiple IT domains, and excellent writing skills. Additionally, the ideal candidate will have training delivery, or training development experience and be able to provide analysis of learning materials from a technical perspective. Software development experience is highly desirable.

Key job responsibilities: 
  • Dive deep into AWS technologies, such as Big Data, Web Applications, Security, Networking, High Performance Computing, Storage, Databases, Enterprise Applications, Migration Strategies or other solutions areas to understand the services and develop effective training for our customers.
  • Develop and maintain a cohesive set of real-world, scenario-based labs to reinforce the learning objectives.
  • Coordinate with the Technical Curriculum Architect to ensure that hands on labs are built for scalability and long-term support.
  • Utilize automated lab and courseware publishing process to manage and deploy content.
  • Work with the Technical Curriculum Architects to provide support and maintenance for the deployed hands-on labs.
  • Determine services and features to be included in course lab exercises, based on intended audience profile, learning objectives, best practices and strategic initiatives.
  • Collaborate with Subject Matter Experts (including Curriculum Developers, Technical Trainers, Support Engineers, Professional Services, and Solutions Architects) to build technically accurate training that meets the learning objectives.
  • A day in the life Every day is a new adventure! You are assigned to work on a specific course or set of courses. The technology you’ll work with will vary based on the course subject matter. Labs often need to have a few resources created before students can begin a lab. You will create templates and scripts to automate the deployment of these resources. You will document the steps required to complete the lab, including explanations. As you build labs for a course, you will collaborate with Technical Architects, Instructional Designers, and Curriculum Developers to ensure the instructional content and the labs are aligned.
Basic qualifications:
  • 1+ years prior experience designing, deploying, and operating internet-scale applications
  • 2+ years domain expertise in one or more of the following: data analytics, machine learning, data platforms, or general cloud technology
  • Demonstrated ability to work cross-functionally with multiple teams and stakeholders
  • Technical degree (e.g. Computer Science) or 2 years' relevant work experience required Current AWS Certification (Associate or Professional level)
  • Knowledge and/or hands-on experience with AWS infrastructure services. Experience designing, developing, and delivering instructional materials for technical content. Domain expertise in one or more of the following: big data, DevOps, security, systems administration, software development, cloud technology
  • Professional experience building systems on Amazon Web Services
  • Excellent command of English (speaking & writing)
  • Willingness to work across time zones.  Many colleagues are based in the USA

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