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Remote Aws Machine Learning Jobs in Newark, CA (NOW HIRING)

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 ...

Tapestry

Senior Staff Machine Learning Engineer

Mountain View, CA · On-site +1

$144K - $190K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Own the technical roadmap and system architecture for Tapestry's multimodal intelligence engines, scaling models across multimodal machine learning, graph neural networks, geospatial and remote ...

Tailored Brands

Data Scientist - Machine Learning

Dublin, CA · On-site +1

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

About the Job We currently have an exciting opportunity for Data Scientist - Machine Learning, to ... remote office location with the ability for occasional travel for team meetings and events.

EvenUp

Staff Machine Learning Engineer

San Francisco, CA · Remote

$212K - $301K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Join EvenUp as a Staff Machine Learning Engineer and help set the technical direction for how ... Open to remote candidates or 3 days a week hybrid from our Toronto or San Francisco hubs. Benefits ...

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All JobsAws Machine Learning JobsRemote Aws Machine Learning JobsRemote Aws Machine Learning Jobs in Newark, CA

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

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

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

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

Remote Aws Machine Learning jobs near you
Infographic showing various Remote Aws Machine Learning job openings in Newark, CA as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Machine Learning Infrastructure Engineer

Bright Vision Technologies

Santa Clara, CA • Remote

$143K/yr

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Machine Learning Infrastructure Engineer – Remote
Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.
This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.
Job Title: Machine Learning Infrastructure Engineer
Location: 100% Remote (U.S.)
Position Type: Full-time, Direct W2
Salary Range: $105,000–$143,000 Annually
Experience Required: 6+ years
Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.
Job Summary
We are seeking a Machine Learning Infrastructure Engineer to design, build, and operate high-performance, highly reliable inference platforms for serving large machine learning models in production. The role focuses on the systems engineering side of AI deployment, including request routing, batching, caching, autoscaling, GPU utilization, and end-to-end observability across diverse model workloads. The ideal candidate brings strong distributed systems and performance engineering expertise, has shipped serving systems at scale, and understands the trade-offs between latency, throughput, cost, and quality in ML serving.
Required Qualifications
  • Bachelor’s or Master’s degree in Computer Science or a related field.
  • Six or more years of experience in distributed systems, infrastructure, or ML platform engineering.
  • Strong proficiency in Python and a systems language such as Go, Rust, or C++.
  • Deep experience operating high-throughput, low-latency services in production.
  • Hands-on experience with LLM or large model inference frameworks such as vLLM or TensorRT-LLM.
  • Strong understanding of GPU architecture, memory hierarchies, and accelerator utilization.
  • Familiarity with Kubernetes, autoscaling, and modern cloud platforms.
  • Experience with observability stacks including metrics, tracing, and structured logging.
  • Solid grounding in performance engineering and capacity planning.
  • Strong communication and incident response skills.
Preferred Qualifications
  • Open-source contributions to model serving infrastructure.
  • Experience with multi-region or globally distributed AI serving.
  • Familiarity with model quantization, distillation, and compression techniques.
  • Exposure to FinOps for AI workloads and cost-efficient serving design.
  • Experience supporting external-facing AI APIs at scale.
How to Apply
Would you like to know more about this opportunity? For immediate consideration, please send your resume to hilda@bvteck.com.
Bright Vision Technologies is an Equal Opportunity Employer.

Equal Employment Opportunity (EEO) Statement

Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.

BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees\' ability to perform their job duties may result in disciplinary action up to and including termination of employment.

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