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Remote Aws Machine Learning Jobs in Santa Clara, CA

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site +1

Company Description PatternAI is an automated machine learning platform that reveals critical ... Experience with Linux, Docker and AWS, and basic development operations. * Advanced degree in ...

Capital One

Lead Machine Learning Engineer

San Jose, CA · On-site +1

$120K - $158K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

Omnissa

Staff Machine Learning Engineer

Mountain View, CA · On-site +1

$162K - $342K/yr

Experience building and operating data processing workflows (batch or streaming) and working with cloud platforms (AWS, Azure, or GCP). * Solid understanding of machine learning algorithms ...

Capital One

Sr. Lead Machine Learning Engineer

San Jose, CA · On-site +1

$120K - $158K/yr

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE) , you'll be ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

YO AI Labs

Machine Learning Engineer - Remote

San Jose, CA · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training project by creating reinforcement learning environments that evaluate AI models on complex software ...

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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 the most commonly searched types of Aws Machine Learning jobs in Santa Clara, CA?

The most popular types of Aws Machine Learning jobs in Santa Clara, CA are:

What are popular job titles related to Remote Aws Machine Learning jobs in Santa Clara, CA?

For Remote Aws Machine Learning jobs in Santa Clara, CA, the most frequently searched job titles are:

What job categories do people searching Remote Aws Machine Learning jobs in Santa Clara, CA look for?

The top searched job categories for Remote Aws Machine Learning jobs in Santa Clara, CA are:

What cities near Santa Clara, CA are hiring for Remote Aws Machine Learning jobs?

Cities near Santa Clara, CA with the most Remote Aws Machine Learning job openings:

Remote Aws Machine Learning jobs near you

Machine Learning Engineer

Pattern AI

San Mateo, CA • On-site, Remote

Full-time

Re-posted 2 days ago

Job description

Company Description
PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems.
Job Description
We're seeking an outstanding ML Engineer to join our data team and help build out best-in-class machine learning solutions on our platform, powering innovative solutions in marketing & sales and commercial analytics.
Responsibilities:
  • Build and deploy the ML pipelines that power PatternAI's machine learning platform.
  • Manage MLOps infrastructure to monitor and optimize models.

Qualifications
Experience:
  • 3+ years of professional experience as a Machine Learning Engineer or production-focused Data Scientist.
  • Proficiency across topics in machine learning and statistics.
  • Fluency in Python coding as well as data manipulation (SQL, Spark, Pandas)
  • Broad familiarity with the Python ecosystem and common libraries including Scikit-Learn, XGBoost, PyTorch, Keras, Tensorflow, Pandas, and common ML cloud services.
  • Familiarity with CNNs, RNN, LSTMs, and the latest research trends.
  • Experience implementing, deploying, and maintaining production machine learning systems.
  • Experience monitoring and optimizing model performance.
  • Experience with Linux, Docker and AWS, and basic development operations.
  • Advanced degree in computer science, mathematics, statistics or related area of study strongly preferred.

Additional Information
About PatternAI
PatternAI is an early stage startup that is growing rapidly and recently closed a successful round of venture funding. We are emerging from stealth and with an exciting series of machine learning products and a rapidly growing number of enterprise customers.
All your information will be kept confidential according to EEO guidelines.

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