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Work Based Learning Program Aws Jobs in Elizabeth, PA

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Machine Learning Engineer III

Pittsburgh, PA · On-site

$111K - $133K/yr

Ability to efficiently work with very large datasets and deal with non-standard machine learning ... based management and hosting, one or more of: AWS, Azure, GCS, CloudFormation, Terraform, or ...

Trying Together

Early Literacy Strategist

Pittsburgh, PA · On-site

$48K - $52K/yr

Trying Together is a Pittsburgh-based nonprofit that supports the work of early childhood by ... Build relationships with early learning programs and providers and work with the Trying Together ...

Bespoke Labs

Machine Learning Engineer

Pittsburgh, PA · On-site

What You'll Be Working On You will work directly with our research team on RL environment and task ... HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets ...

Trying Together

Early Literacy Strategist

Pittsburgh, PA · On-site

$48K - $52K/yr

Trying Together is a Pittsburgh-based nonprofit that supports the work of early childhood by ... Build relationships with early learning programs and providers and work with the Trying Together ...

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All JobsWork Based Learning Program Aws JobsWork Based Learning Program Aws Jobs in Elizabeth, PA

Work Based Learning Program Aws information

See Elizabeth, PA salary details

$44.4K

$76.9K

$173.4K

How much do work based learning program aws jobs pay per year?

As of Aug 15, 2026, the average yearly pay for work based learning program aws in Elizabeth, PA is $76,889.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,900.00 and $84,100.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in a work based learning program focused on AWS, and why are they important?

To thrive in a Work-Based Learning Program focused on AWS, you need foundational knowledge of cloud computing concepts, basic programming skills, and familiarity with networking, supported by relevant coursework or entry-level certifications like AWS Cloud Practitioner. Hands-on experience with AWS tools such as EC2, S3, Lambda, and the AWS Management Console is typically required, along with understanding of version control systems like Git. Strong problem-solving abilities, willingness to learn, and effective communication are important soft skills for adapting to real-world technical environments. These skills and qualities are crucial for successfully applying cloud concepts in practical settings and collaborating with teams to solve business challenges.

What is the difference between Work Based Learning Program Aws vs Cloud Support Associate?

AspectWork Based Learning Program AwsCloud Support Associate
CredentialsTypically no formal certifications required; focus on trainingOften requires AWS certifications or related cloud credentials
Work EnvironmentEducational or training setting, often part-time or internshipProfessional cloud support environment, full-time role
Employer & Industry UsageEducational institutions, training providers, AWS programsCloud service providers, IT companies, AWS partners

The Work Based Learning Program Aws is primarily a training or internship opportunity designed to develop skills in AWS cloud services, often without requiring prior certifications. In contrast, a Cloud Support Associate is a full-time professional role that typically requires AWS certifications and involves supporting cloud customers in a real-world environment. While the learning program focuses on education and skill development, the associate role emphasizes practical support and troubleshooting in the industry.

What is a work based learning program with AWS?

A Work Based Learning Program with AWS is an educational initiative that combines classroom instruction with real-world work experience using Amazon Web Services (AWS) technologies. These programs are designed to help students and professionals gain hands-on cloud computing skills by working on projects, internships, or apprenticeships in partnership with employers. Participants learn about cloud infrastructure, deployment, and AWS services, making them more competitive in the job market. Such programs often include mentorship, industry certifications, and exposure to real business challenges.

How does participating in an AWS work based learning program help prepare candidates for a cloud-focused career?

Participating in an AWS Work-Based Learning Program offers hands-on experience with key AWS cloud services, allowing candidates to apply classroom concepts to real-world projects. You'll typically collaborate with mentors and teammates in a structured environment, working on tasks such as cloud migration, automation, and security configuration. This immersion helps build both technical and professional skills, making you more competitive for roles such as cloud support associate or solutions architect. Additionally, exposure to industry best practices and networking opportunities within the program can significantly accelerate your career growth in cloud computing.

What cities near Elizabeth, PA are hiring for Work Based Learning Program Aws jobs?

Cities near Elizabeth, PA with the most Work Based Learning Program Aws job openings:

Work Based Learning Program Aws jobs near you
Infographic showing various Work Based Learning Program Aws job openings in Elizabeth, PA as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 18% Part Time, and 4% Contract. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution, with an average salary of $76,889 per year, or $37 per hour.

Senior / Staff Machine Learning Infrastructure Engineer

Waabi

Pittsburgh, PA • On-site, Remote

$157K - $234K/yr

Full-time

Re-posted 2 days ago

Job description

Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech.

With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: www.waabi.ai

You will..
- Design, develop, and implement the machine learning platform for the continuous deployment and integration of machine learning models.
- Collaborate with data scientists and engineers to understand model requirements and optimize pipeline processes.
- Automate the training, testing and deployment processes for machine learning models.
- Continuously monitor and maintain model pipelines, ensuring optimal performance, accuracy and reliability.
- Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness.
- Ensure compliance with security and data privacy standards in all MLOps activities.
 
Qualifications:
- 3-5 years of experience supporting machine learning training platforms.
- Bachelor’s degree in Computer Science, Data Science or a related field.
- Strong understanding of machine learning principles and model lifecycle management.
- Proficiency in programming languages such as Python, with hands-on experience in machine learning frameworks like TensorFlow or PyTorch.
- Experience with cloud platforms like AWS, Azure, or Google Cloud and their respective machine learning services.
- Experience managing technology such as JupyterHub and Kubeflow.
- Familiarity with containerization and orchestration tools such as Kubernetes and Docker.
- Strong problem-solving skills and ability to troubleshoot complex issues.
- Experience with monitoring tools and practices for model performance in production.
- Ability to work collaboratively in cross-functional teams.
 
Bonus/nice to have: 
- Experience with infrastructure-as-code (IaC) tools such as Terraform or Crossplane.
- Knowledge of big data technologies like Apache Spark or Hadoop.
- Familiarity with data engineering practices and tools.
- Experience with A/B testing and model validation in production environments.
- Relevant MLOps certifications (e.g., AWS Certified Machine Learning – Specialty, DataRobot MLOps Certification) are a plus.
The US yearly salary range for this role is: $157,000 - $234,000 USD in addition to competitive perks & benefits. Waabi (US) Inc.’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations.  Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus.

Perks/Benefits:
- Competitive compensation and equity awards.
- Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only).
- Unlimited Vacation.
- Flexible hours and Work from Home support.
- Daily drinks, snacks and catered meals (when in office).
- Regularly scheduled team building activities and social events both on-site, off-site & virtually.
- As we grow, this list continues to evolve! 

Waabi is a technology start-up building technologies to transform the way the world moves. Join our talented team to be a part of the future and to make an impact!

Waabi is an equal opportunity employer. We celebrate diversity and are committed to creating a supportive, inclusive, and accessible workplace for all our employees. We seek applicants of all backgrounds and identities, across race, color, ethnicity, national origin or ancestry, age, citizenship, religion, sex, sexual orientation, gender identity or expression, military or veteran status, marital status, pregnancy or parental status, caregiver status, disability, or any other characteristic protected by law. We make workplace accommodations for qualified individuals with disabilities as required by applicable law. If reasonable accommodation is needed to participate in the job application or interview process please let our recruiting team know.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.