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Remote Aws Machine Learning Jobs in Oregon (NOW HIRING)

SOSi

Data Scientist

OR · On-site +1

... AWS SageMaker or Azure Machine Learning, and in implementing models into operational workflows ... Full remote flexibility. Working at SOSi All interested individuals will receive consideration and ...

Liftoff

Staff Product Manager, Conversion ML

OR · On-site +1

... machine learning at scale is a plus. * Loads of passion for building great products and growing a great company! Location: Liftoff follows a philosophy of "remote first, come together meaningfully ...

Upstart

Software Engineer, Distribution Platform

OR · On-site +1

You will work closely with cross-functional counterparts in Analytics, Marketing, Machine Learning ... Remote Travel requirements As a digital first company, the majority of your work can be ...

Upstart

Applied Scientist

OR · On-site +1

The team conducts machine learning research, evaluates model performance, and partners closely with ... Remote Travel requirements As a digital first company, the majority of your work can be ...

New

Upstart

DevOps Engineer, Cloud Platform

OR · On-site +1

$52.75 - $72.25/hr

... machine learning workloads. The team owns core platform components across Kubernetes (EKS), AWS ... Remote Travel requirements As a digital first company, the majority of your work can be ...

LMI

Artificial Intelligence Lead

This position is anticipated to be majority remote, but with the ability to travel and visit the ... Advanced knowledge of AI, machine learning, deep learning, and data science concepts (Master's or ...

Tebra

Data Engineer

OR · Remote

$114K - $137K/yr

You'll partner closely with Machine Learning Engineers, Data Scientists, and Software Engineers to ... Remote

Upstart

Software Engineer, Verifications Platform

OR · On-site +1

Partner with Machine Learning, Product, Risk, Fraud, and Compliance teams to integrate data ... Remote Travel requirements As a digital first company, the majority of your work can be ...

Origami Risk LLC

Senior Data Engineer

$117K - $146K/yr

NET code to a scalable, cloud-native architecture on AWS and expanding into our Databricks ... Exposure to machine learning pipelines and real-time data processing Benefits * Medical and Dental ...

Hitachi

Data Scientist I or II (MAD-BS-OR)

Hillsboro, OR · On-site +1

$121K - $167K/yr

Hybrid (+50% Remote) - Remote 60% / Onsite 40% EXPECTED PAY RANGE: Data Scientist I: $99,608 - $136 ... PRIMARY RESPONSIBILITIES * Hands-on development and write algorithms in machine learning ...

Lumen Technologies

Senior Lead Applied AI Scientist

OR · Remote

$176K - $220K/yr

You will combine deep expertise in AI and machine learning with strong software engineering ... Bonus Structure #LI-REMOTE #LI-SB1 Requisition #: 342925 Life at Lumen Life at Lumen is human and ...

Upstart

Senior Privacy Engineer

OR · On-site +1

$104K - $143K/yr

The team works across Engineering, Security, Legal, Compliance, Product, Data, and Machine Learning ... REMOTE #LI-MidSenior --> use for L5, L6

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All JobsAws Machine Learning JobsRemote Aws Machine Learning JobsRemote Aws Machine Learning Jobs in Oregon

Remote Aws Machine Learning information

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 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 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:
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Remote Aws Machine Learning jobs near you

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Salem, OR • Remote

Full-time

Re-posted 16 days ago

Job description

About Us

Our mission is to bring people together and connect them into a community to nurture each other. We aim to share a conducive environment, a joyous space to grow and excel; a world brimming with selfless love and enough kindness. We strive to enrich each of our lives with kaleidoscopic memories we make here - vibrant, lively, of all hues and colors.

Job Description

​

This is a remote position.

We are seeking a highly skilled and innovative Generative AI Automation Engineer to join our team. The ideal candidate will be responsible for designing, developing, and implementing automation solutions powered by Generative AI models. This role requires a combination of expertise in machine learning, natural language processing, software engineering, and automation frameworks to drive efficiency and innovation in business processes.

Key Responsibilities:

Generative AI Model Implementation:

  • Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.

  • Integrate pre-trained models or build custom models for specific use cases.

Automation Design and Development:

  • Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.

  • Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.

Data Management:

  • Collect, preprocess, and analyze large datasets for training and validating AI models.

  • Ensure data privacy and compliance with regulatory requirements during data handling.

System Integration:

  • Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.

  • Build and maintain pipelines for real-time AI inference and automation.

Monitoring and Optimization:

  • Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.

  • Optimize models and processes based on performance metrics and user feedback.

Research and Innovation:

  • Stay updated with the latest advancements in Generative AI and automation technologies.

  • Identify opportunities for implementing cutting-edge AI solutions to address business challenges.

Documentation and Collaboration:

  • Document technical designs, workflows, and implementation strategies.

  • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.

Requirements

Required Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

  • Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.

  • Proficiency in designing and deploying machine learning models, particularly in Generative AI.

  • Experience with automation tools (e.g., RPA, workflow orchestration tools).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).

  • Solid understanding of data structures, algorithms, and software design principles.

  • Strong analytical and problem-solving skills.

  • Excellent communication and teamwork abilities.

Preferred Qualifications:

  • Experience with NLP, image generation, or multimodal AI models.

  • Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.

  • Familiarity with prompt engineering and fine-tuning Generative AI models.

  • Knowledge of MLOps practices for deploying and maintaining AI solutions.

  • Previous experience in automation or workflow optimization projects.

Benefits

Why Join Us?

  • Work with cutting-edge Generative AI technologies.

  • Collaborate with a team of forward-thinking innovators.

  • Make a tangible impact on the future of automation and AI-driven processes.

If you are passionate about leveraging Generative AI to create innovative automation solutions, we invite you to apply and be a part of our dynamic and growing team.

Apply