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Remote Aws Machine Learning Jobs in Oregon (NOW HIRING)

U.S. Financial Technology

DevOps Engineer

$52.75 - $72.25/hr

... of machine learning concepts and AI tooling integration Preferred Qualifications: * AWS ... Remote work environment with emphasis on team collaboration and hands-on problem solving Pay Range ...

SentinelOne

Senior Backend Software Engineer, ObservoAI

OR · Remote

$122K - $161K/yr

... using advanced machine learning and LLMs. * Design cloud-native microservices and APIs that ... Extensive experience with cloud platforms (AWS, GCP, Azure), container orchestration (Kubernetes ...

phData

Territory Director - Chicago

OR · Remote

... Machine Learning, and Analytics) * Co-Sell with Snowflake, AWS, and other ecosystem partners to ... Remote-First Work Environment * A casual, award-winning small-business work environment * A culture ...

Upstart

Principal Software Engineer, Unsecured Installments

OR · On-site +1

$134K - $180K/yr

Partner closely with machine learning engineers and data teams to productionize models and ... Remote, Burlingame, Columbus, Austin, New York Time Zone Requirements - This team operates across ...

Upstart

Senior Software Engineer, Home Lending

OR · On-site +1

$122K - $161K/yr

... and Machine Learning, Servicing, and Operations. How you'll make an impact Build and improve ... Remote Travel requirements As a digital first company, the majority of your work can be ...

Upstart

Principal Product Manager, Pricing Platform

OR · On-site +1

Partner with engineering, machine learning, and product teams across unsecured, auto, and home ... Remote Time zone requirements The team operates on the East/West coast time zones. Travel ...

BECU

Sr. Software Engineer - AI Innovation Team

OR · On-site +1

$110K - $204K/yr

From integrating machine learning models and generative AI services to guiding best practices and ... Remote or onsite, we are committed to ensuring you are fully engaged and included in our ...

Upstart

Senior Engineering Manager, Marketplace

OR · On-site +1

You'll partner closely with Product, Machine Learning, and Capital Markets to deliver scalable ... Hands-on familiarity with cloud platforms (AWS/GCP/Azure), containerization and orchestration ...

phData

Territory Director - Northeast

OR · Remote

... Machine Learning, and Analytics) * Co-Sell with Snowflake, AWS, Anthropic and other ecosystem ... Remote-First Work Environment * 401k plan with company match * Dental and Vision insurance * Home ...

Upstart

Credit Risk Manager

OR · On-site +1

Partner with Machine Learning, Product, Risk, and Bank leadership teams to evaluate portfolio ... Remote (United States) Time zone requirements The team operates on the East/West coast time zones.

NewRocket

AI Data Intelligence Lead

OR · Remote

Remote (Occasional travel as needed) Reports to: Global AI Center of Excellence Lead Why Us ... This role focuses on applying machine learning, generative AI, and advanced data engineering ...

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

DevOps Engineer

U.S. Financial Technology

Remote

$52.75 - $72.25/hr

Full-time

Medical, Retirement, PTO

Posted 18 days ago

Job description

OVERVIEW

The Company

U.S. Financial Technology (U.S. FinTech) is seeking an experienced DevOps Engineer to join our team of talented professionals. This is a full-time remote opportunity. 

U.S. FinTech built and operates the largest and most advanced mortgage securitization platform in the world, supporting the Uniform Mortgage-Backed Security (UMBS) of Fannie Mae and Freddie Mac.

Supporting 70% of the mortgage-backed securities in the market, U.S. FinTech provides best-in-class single-family issuance, bond administration, disclosure, and tax services. We support a broad portfolio of products for our clients with full lifecycle management.

Our market-leading, cloud-based, end-to-end platform executes transactions on an extraordinary scale which has bolstered liquidity in the secondary mortgage market, one of the largest and most important financial markets in the world. Our unique approach to securitization combines the best minds in financial services with the know-how, flexibility, and innovation of leading technologists.

RESPONSIBILITIES

Job InformationAre you a hands-on engineer who thrives on building robust, scalable systems? Join our dynamic Cloud Monitoring SRE team where you'll architect and maintain mission-critical cloud infrastructure while working with cutting-edge technologies. This role is perfect for a strong coder who wants to drive operational excellence through automation, intelligent monitoring, and modern DevOps practices. You'll work closely with development teams in a fast-paced environment where your technical skills directly impact system reliability and customer experience.

Key Job Functions

Infrastructure & Automation:

  • Design and implement scalable infrastructure solutions using AWS services and Infrastructure as Code
  • Build robust CI/CD pipelines with comprehensive testing and automated deployment capabilities
  • Develop monitoring and alerting systems using CloudWatch, Splunk, and modern observability tools
  • Automate operational processes to eliminate manual work and reduce human error

System Reliability & Performance:

  • Maintain high availability and performance of large-scale cloud platforms
  • Implement proactive monitoring solutions for system health, performance metrics, and capacity planning
  • Execute strategic patching cycles and infrastructure maintenance with minimal downtime using AWS suite of services
  • Design disaster recovery and business continuity solutions

Security & Compliance:

  • Collaborate with InfoSec teams to implement automated vulnerability remediation workflows
  • Build security-first infrastructure with proper access controls and audit trails
  • Develop compliance monitoring and reporting automation

Development & Innovation:

  • Write clean, maintainable code in Python and other modern languages
  • Create comprehensive unit and integration tests for infrastructure code
  • Build internal tools and dashboards to improve team productivity
  • Evaluate and implement emerging technologies including AI/ML tools where they add operational value
  • Contribute to architecture decisions and technical roadmap planning
QUALIFICATIONS

Education   

  • Bachelor's degree in Computer Science, MIS or related technical field required.

Minimum Experience  

  • 3+ years professional experience managing large-scale, highly available cloud platforms
  • 3+ years hands-on Python development with focus on automation and infrastructure
  • 2+ years deep experience with AWS core services (EC2, Lambda, S3, CloudWatch, Systems Manager, API Gateway)
  • Proven experience with Infrastructure as Code (CloudFormation, CDK, or Terraform)
  • Applicants must be authorized to work in the US without requiring employer sponsorship currently or in the future. U.S. FinTech does not offer H-1B sponsorship for this position.

Specialized Knowledge & Skills     

Technical Skills - Core:

  • Strong Programming: Advanced Python skills plus proficiency in at least one other language (Go, JavaScript, Java, or similar)
  • Cloud Architecture: Deep understanding of AWS services, networking, security, and cost optimization
  • Automation: Expert-level experience with CI/CD tools (Jenkins, CodePipeline, GitHub Actions)
  • Monitoring & Observability: Hands-on experience with logging, metrics, and tracing solutions
  • Containerization: Working knowledge of Docker and container orchestration

Technical Skills - Modern Stack:

  • Experience with modern web frameworks and APIs (React.js, RESTful services)
  • Database management (both relational and NoSQL)
  • Version control and collaborative development practices (Git, code reviews)
  • Testing frameworks and quality assurance automation
  • Basic understanding of machine learning concepts and AI tooling integration

Preferred Qualifications:

  • AWS certifications (Solutions Architect Associate or DevOps Engineer)
  • Experience with Kubernetes or ECS for container orchestration
  • Knowledge of chaos engineering and resilience testing
  • Exposure to AI/ML services (SageMaker, Bedrock) and their operational integration
  • Experience building internal developer tools and platforms

Professional Qualities:

  • Hands-On Mindset: Prefers to build and fix things directly rather than just manage processes
  • Problem Solver: Strong analytical skills with ability to troubleshoot complex distributed systems
  • Code Quality Focus: Writes maintainable, well-tested code with proper documentation
  • Collaborative: Works effectively with development, security, and business stakeholder teams
  • Continuous Learner: Stays current with industry trends and emerging technologies
  • Ownership Mentality: Takes accountability for system reliability and customer impact

Work Environment:

  • Availability for occasional off-hours work during critical releases and maintenance windows
  • Participation in on-call rotation with proper tooling and escalation procedures
  • Remote work environment with emphasis on team collaboration and hands-on problem solving

Pay Range $81,000 to $107,500

U.S. FinTech's pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) a candidate's qualifications, skills, competencies, and experience, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law. U.S. FinTech offers a competitive total compensation package, which includes a performance bonus, 401k match, healthcare coverage, PTO, and a broad range of other benefits.

Employment

As a condition of employment with U.S. Financial Technology, any successful job applicant will be required to  successfully complete a background investigation, which may also include a credit check for positions in some areas of our business.   

U.S. Financial Technology is an Equal Opportunity Employer.

##LI-Remote

Employment Type: FULL_TIME

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