2

Remote Aws Machine Learning Jobs in Renton, WA (NOW HIRING)

Senior Machine Learning Engineer II

Seattle, WA · On-site +1

$118K - $163K/yr

Your Impact We are seeking a seasoned Machine Learning Engineer to join a new team building agentic ... Hands-on experience operating cloud infrastructure at scale (AWS, GCP, or Azure), including ...

Lead AI Engineer - AWS Platform

Seattle, WA · On-site +1

$130K - $190K/yr

Build machine learning models that automate their training, validation, monitoring, and retraining ... Flexible work schedules and hybrid/remote options for eligible positions * Educational assistance ...

AWS Data Engineer (Associate)

Seattle, WA · On-site +1

$130K - $156K/yr

You'll spend it writing code that reaches production and learning judgment from engineers who own ... Certifications AWS Certified Big Data - Specialty OR Cloudera Certified Big Data Engineer OR ...

next page

Showing results 1-20

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 popular job titles related to Remote Aws Machine Learning jobs in Renton, WA? For Remote Aws Machine Learning jobs in Renton, WA, the most frequently searched job titles are:
What job categories do people searching Remote Aws Machine Learning jobs in Renton, WA look for? The top searched job categories for Remote Aws Machine Learning jobs in Renton, WA are:
What cities near Renton, WA are hiring for Remote Aws Machine Learning jobs? Cities near Renton, WA with the most Remote Aws Machine Learning job openings:
Senior Machine Learning Engineer II

Senior Machine Learning Engineer II

Axon

Seattle, WA • On-site, Remote

$118K - $163K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 20 days ago


Axon rating

8.8

Company rating: 8.8 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

11th of 144 rated electronics manufacturers


Job description

Your Impact

We are seeking a seasoned Machine Learning Engineer to join a new team building agentic video and multimodal reasoning systems. As a senior engineer on this team you will own the systems and infrastructure that turn cutting-edge research into safe, reliable, and scalable AI capabilities - supporting our company's mission to accelerate justice, protect truth, and save lives.

Working shoulder to shoulder with research scientists, you will build everything that stands between a promising model and a production system operating on video and multimodal data at scale: the data and ingest pipelines, the training and evaluation infrastructure, the inference and serving stack, the retrieval and orchestration layers behind agentic reasoning, and the reliability, security, and privacy guarantees that Axon's customers depend on. Scientists define the models and the metrics; you build the platform that lets them move fast and lets those models ship.

At Axon, we Aim Far. We think big with a long-term view because we want to reinvent the world to be a safer, better place. If you're excited about this role and our mission to Protect Life but your experience doesn't align perfectly with every qualification listed here, we encourage you to apply anyway. You may be just the right candidate for this or other roles.

What You'll Do

Location: Hybrid from Seattle, WA or London, UK
Reports to: Director of Software Engineering, AI

  • Own end to end the systems and infrastructure that take multimodal and video models from research prototype to reliable, scalable production.
  • Design and operate data and ingest pipelines for large-scale video and multimodal corpora - storage, processing, labeling, and retrieval.
  • Build and scale training and evaluation infrastructure, and turn scientists' evaluation methodology into automated, reproducible measurement systems.
  • Build inference and serving systems for real-time and batch multimodal workloads, optimizing latency, throughput, and cost.
  • Build the retrieval, indexing, and embedding infrastructure (vector search at scale) and the orchestration and tool-use plumbing behind agentic reasoning over video and multimodal data.
  • Ensure the platform is secure, privacy-preserving, and responsible by design.
  • Set technical direction for the team's systems, raise the engineering bar, and mentor other engineers.
What You Bring
  • Bachelor's Degree in Computer Science, Engineering, Physics, Mathematics or an equivalent highly technical field.
  • 10+ years of software engineering experience and a proven track record of architecting, operating, and maintaining large-scale distributed platforms in production.
  • Deep experience building systems across the ML lifecycle: data pipelines, training and evaluation infrastructure, model serving and inference at scale, and production monitoring.
  • Experience with large-scale data systems handling video or other high-volume, high-dimensional multimodal data.
  • Strong software engineering fundamentals and proficiency in Python, along with familiarity with ML frameworks such as PyTorch or TensorFlow.
  • Hands-on experience operating cloud infrastructure at scale (AWS, GCP, or Azure), including distributed systems and container orchestration.
  • Excellent problem-solving skills and the ability to dive into system architecture, design, performance metrics, code, test plans, project plans, deployments, and operations.
  • Strong communication skills and comfort partnering closely with scientists, engineers, and product managers.

Preferred

  • Master's or PhD in Computer Science, Engineering, or an equivalent highly technical field.
  • Experience building video processing or video understanding pipelines at scale.
  • Experience with retrieval systems, vector search, and RAG infrastructure.
  • Experience serving foundation models, or building agentic systems and LLM tool-use orchestration.
  • Familiarity with responsible AI, de-identification, and privacy-preserving techniques.
Benefits that Benefit You
  • Competitive salary and 401k with employer match
  • Discretionary paid time off
  • Paid parental leave for all
  • Medical, Dental, Vision plans
  • Fitness Programs
  • Emotional & Mental Wellness support
  • Learning & Development programs
  • Employee Resource Groups (ERGs)
  • And yes, we have snacks in our offices

Benefits listed herein may vary depending on the nature of your employment and the location where you work.

Location: This role is based out of our Seattle, WA office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesdays through Fridays, with the flexibility to work remotely on Mondays, unless there is an approved workplace accommodation. We believe that connection fuels innovation, and our in-office culture is designed to foster meaningful teamwork, mentorship, and shared success.

#LI-Hybrid


What Axon employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom