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Remote Aws Machine Learning Jobs in Phoenix, AZ (NOW HIRING)

Data Scientist

Phoenix, AZ · Remote

$65 - $75/hr

Remote (Candidate must reside in Pacific, Mountain, or Central time zone. Eastern time zone and ... Build and scale machine learning and AI models on cloud platforms, primarily AWS or Azure * Develop ...

Experience designing and deploying solutions to cloud environments (AWS) * Experience with IaC ... Experience with AI/machine learning technologies is strongly preferred. * Familiarity with TCP/IP ...

Lead Engineer, Data Platforms

Tempe, AZ · On-site +1

$111K - $133K/yr

... machine learning, and AI-driven workflows and will be responsible for designing and implementing ... Mastery of AWS services (IAM, VPC, Glue, S3, SFTP, Lambda, CloudWatch, SNS) , Gitlab CI/CD, DataDog ...

Lead Data & AI Engineer

Phoenix, AZ · On-site +1

$50 - $60/hr

Phoenix, AZ (hybrid remote) Type: 6-month contract to hire Pay: $50-60/hr We're looking for a Lead ... machine learning models that improve cost, quality, and patient outcomes. Your role · Design ...

Were looking for a pragmatic, startup-minded Senior Machine Learning Engineer or Applied Data ... Snowflake for data warehousing, AWS for cloud infrastructure, and Datadog for monitoring and ...

This role reports to the Security Ops Lead and is Remote-US (open to most states, with a few exceptions listed on the role page). You fit if you have shipped machine learning to production and you ...

Cloud Solutions Architect

Phoenix, AZ · Remote

$110K - $120K/yr

... remote work opportunities. With career paths for seasoned professionals in a variety of fields ... Develop and organize cloud systems, with a focus on enabling machine learning and artificial ...

... remote-first education and technology company on a mission to transform learning for students ... Collaborate with IT teammates to support Azure and AWS cloud environments, maintain technical ...

Fraud Specialist

Phoenix, AZ · On-site +1

$22.50/hr

Monitor and utilize AI fraud detection tools, machine learning model scores, and alert systems to ... Whether you are working from our San Francisco or Phoenix offices or joining us as a fully remote ...

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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 the most commonly searched types of Aws Machine Learning jobs in Phoenix, AZ? The most popular types of Aws Machine Learning jobs in Phoenix, AZ are:
What job categories do people searching Remote Aws Machine Learning jobs in Phoenix, AZ look for? The top searched job categories for Remote Aws Machine Learning jobs in Phoenix, AZ are:
What cities near Phoenix, AZ are hiring for Remote Aws Machine Learning jobs? Cities near Phoenix, AZ with the most Remote Aws Machine Learning job openings:

Senior / Staff Machine Learning Infrastructure Engineer

Waabi

Phoenix, AZ • On-site, Remote

$157K - $234K/yr

Full-time

Medical, Dental, Vision, PTO

Posted 14 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.
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