Top 40 Machine learning engineer Jobs in San Luis Obispo, Ca

Platform Engineer II/III
Zone 5 Technologies —San Luis Obispo, CA
- $113,000 - $172,000 a year
- Remote
- Computer Science
- System design
- Analysis skills
- Paid holidays
- Health insurance
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Sensor Engineer
SORONA INC. —San Luis Obispo, CA
- Full-time
- Remote
- Azure
- Mid-level
- Analysis skills
- Health savings account
- Paid holidays
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Contract Software Engineer - AI Trainer
DataAnnotation —California
- $50 - $100 an hour
- Part-time
- Remote
- Writing skills
- English
- Mid-level
- Flexible schedule
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CI/CD Pipeline Engineer - AI Trainer
DataAnnotation —California
- $50 - $100 an hour
- Part-time
- Remote
- Writing skills
- English
- Mid-level
- Flexible schedule
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Application Developer - AI Trainer
DataAnnotation —California
- $50 - $100 an hour
- Part-time
- Remote
- Writing skills
- English
- Mid-level
- Flexible schedule
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Android Developer - AI Trainer
DataAnnotation —California
- $50 - $100 an hour
- Part-time
- Remote
- Writing skills
- English
- Mid-level
- Flexible schedule
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Speculative application for direct entry
SORONA INC. —San Luis Obispo, CA
- Full-time
- Linux
- Entry level
- Health savings account
- Paid holidays
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Flight Controls Engineer
Empirical Systems Aerospace, Inc. —San Luis Obispo, CA
- $90,000 - $120,000 a year
- Full-time
- Background check
- Mid-level
- Master's degree
- Health savings account
- Paid holidays
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Embedded Software Engineer (Aerospace)
Empirical Systems Aerospace, Inc. —San Luis Obispo, CA
- $100,000 - $170,000 a year
- Full-time
- Background check
- Computer science
- Computer Science
- Health savings account
- Paid holidays
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Sr Control Systems Engineer
Entegris, Inc. —San Luis Obispo, CA
Bachelors degree in electrical engineering, automation engineering, or mechatronics (Masters degree preferred). Control engineering: 5 years (Required).
$120,000 - $130,000 a year
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Sensor Engineer
SORONA INC. —San Luis Obispo, CA
Our engineering teams collaborate across the United States, working across software, hardware, data science, and machine learning to develop next-generation…
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Product Development Engineer - Onsite
RTP Company —Gahanna, OH
Field and respond to telephone calls and e-mails from customers, Sales Engineers, and Application Development Engineers. Evaluate and approve new raw materials.
Staff Software Engineer - AI Trainer
DataAnnotation —Dublin, OH
Flexible schedule: choose which projects you take on and when you work, on your own computer, from the comfort of your own home.
$50 - $100 an hour
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machine learning engineer jobs near san luis obispo, ca

Platform Engineer II/III

Zone 5 Technologies
San Luis Obispo, CA

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Job Details

$113,000 - $172,000 a year

Benefits

Paid holidays
Health insurance
Dental insurance
Paid time off
Vision insurance
401(k) matching
Opportunities for advancement

Qualifications

Continuous Delivery (CD) implementation
Linux support
Infrastructure as Code (IaC)
System design
Configuration management
System design for system development
Cloud Architecture Design (Architecture design skills)
DevOps automation
Linux administration

Full Job Description

At Zone 5 Technologies, we're redefining what's possible in unmanned aircraft systems. Our team of engineers and innovators is developing cutting-edge autonomous solutions that push the boundaries of UAS technology - solving complex challenges that matter.

We're building the future of UAS capabilities, and we're looking for exceptional talent to join us. If you're driven by hard problems, energized by rapid innovation, and ready to make an impact on next-generation flight systems, you belong here.

We are seeking a Platform Engineer to architect and operate scalable compute infrastructure that powers our autonomous vehicle simulation and testing framework. You will build elastic compute systems across AWS and on-premises clusters, enabling engineering teams to rapidly iterate on autonomy algorithms through massive parallel simulation workloads.

Responsibilities:

Elastic Compute Architecture

Design and implement auto-scaling compute infrastructure for simulation workloads using cloud platforms

Build and maintain on-premises GPU and CPU clusters for simulation and machine learning training

Architect hybrid cloud solutions that optimize cost and performance across cloud and local compute resources

Implement job scheduling and orchestration systems using Kubernetes for thousands of concurrent simulations

Design storage solutions for large-scale simulation data, logs, and artifacts using cloud and local storage systems

Simulation Platform Development

Deploy and maintain robotics simulation environments at scale

Build CI/CD pipelines for automated simulation testing of autonomy software

Create infrastructure for distributed parameter sweeps, Monte Carlo testing, and regression suites

Develop monitoring and observability systems for simulation fleet health and resource utilization

Implement data pipelines for simulation results ingestion, analysis, and visualization

Infrastructure as Code & Automation

Write and maintain infrastructure as code for reproducible infrastructure deployment

Build automation tools and CLI utilities to simplify developer access to compute resources

Implement GitOps workflows for infrastructure changes and configuration management

Create self-service interfaces for engineers to launch and manage simulation jobs

Develop cost monitoring and optimization strategies for cloud and on-prem resources

System Operations & Reliability

Monitor and optimize infrastructure performance, reliability, and cost efficiency

Troubleshoot complex distributed systems issues across networking, storage, and compute layers

Implement backup, disaster recovery, and business continuity strategies

Maintain security best practices including IAM, secrets management, and network isolation

Collaborate with autonomy, ML, and robotics teams to understand compute requirements and optimize workflows

Network Design & Infrastructure

Design and implement network architectures for distributed simulation workloads across AWS and on-premises environments

Configure VPCs, subnets, security groups, and routing for secure, high-performance compute clusters

Establish hybrid cloud connectivity (VPN, Direct Connect, site-to-site tunnels) between on-premises and cloud resources

Optimize network performance for large data transfers, multi-node communication, and distributed workloads

Support internal infrastructure network design and provide technical guidance to engineering programs

Troubleshoot network issues including latency, packet loss, and connectivity problems across distributed systems

Qualifications:

Bachelor's in Computer Science, Software Engineering, or related technical field – equivalent industry experience also welcome

2-5+ years of experience in platform engineering, DevOps, SRE, or cloud infrastructure roles

Strong hands-on experience with Kubernetes for container orchestration and workload management

Experience with cloud computing platforms and services (compute, storage, networking)

Deep understanding of Linux system administration and troubleshooting

Strong networking fundamentals including TCP/IP, routing, DNS, VPNs, and security

Understanding of infrastructure as code principles and configuration management

Proficiency in scripting and automation (Python, Bash, or similar)

Experience building and maintaining CI/CD pipelines

Solid grasp of distributed systems concepts, job scheduling, and resource management

Ability to design infrastructure from first principles and make architectural decisions

Preferred:

Experience building infrastructure for simulation, robotics, or autonomous systems workloads

Understanding of GPU computing and accelerated workload management

Knowledge of job scheduling systems for batch and parallel workloads

Experience managing on-premises clusters and hybrid cloud architectures

Familiarity with robotics middleware (ROS/ROS2) or simulation platforms

Understanding of cost optimization for compute-intensive workloads

Experience with monitoring, logging, and observability systems

Knowledge of containerization technologies and image management

Background in data engineering, MLOps, or machine learning infrastructure

Experience with network performance analysis and troubleshooting

Understanding of software-defined networking and network automation

Familiarity with security compliance requirements in aerospace/defense environments

Compensation:

Level II - $113,000 - $141,000

Level III - $142,000 - $172,000

What's in it for you:

Benefits:

Competitive total compensation package
Comprehensive benefit package options include medical, dental, vision, life, and more.
401k with company-match
4 weeks of paid time off each year
12 annual company holidays

Why Join Zone 5 Technologies?

Innovative Environment: Work on cutting-edge technology that is shaping the future of defense and aerospace.
Collaborative Culture: Join a team of passionate professionals dedicated to pushing the boundaries of what's possible.
Career Growth: Opportunities for professional development and career advancement.

If you are passionate about unmanned aircraft technology and want to be a part of a dynamic and growing company, we would love to hear from you. Apply today and join the Zone 5 Technologies team!

In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.

Zone 5 Technologies is a federal contractor and participates in E-Verify to confirm employment eligibility. As required by law, we will verify the identity and employment authorization of all new employees using the E-Verify system. Learn more about your rights and responsibilities under E-Verify: https://www.e-verify.gov.

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machine learning engineer jobs in san luis obispo, ca

Platform Engineer II/III

Sensor Engineer

Contract Software Engineer - AI Trainer

CI/CD Pipeline Engineer - AI Trainer

Application Developer - AI Trainer

Android Developer - AI Trainer

Speculative application for direct entry

Flight Controls Engineer

Embedded Software Engineer (Aerospace)

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