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Remote Tesla Machine Learning Engineer Jobs in Arizona

Lead Data & AI Engineer

Phoenix, AZ ยท On-site +1

$50 - $60/hr

Phoenix, AZ (hybrid remote) Type: 6-month contract to hire Pay: $50-60/hr We're looking for a ... machine learning models that improve cost, quality, and patient outcomes. Your role ยท Design ...

... remote workers in cities across the U.S., Ascend Learning was recognized by Newsweek and Plant-A ... Advanced understanding and practical experience in machine learning and natural language processing ...

You will have the flexibility to work fully remote from anywhere across Arizona. Insight at a ... At least 5 years specifically focused on Data Engineering, Analytics, or Machine Learning. * Cloud ...

PhD Engineer (Electrical, Mechanical, Chemical) Role Type: Contractor Location: Remote micro1 is ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

Lead Engineer, Data Platforms

Tempe, AZ ยท On-site +1

$111K - $133K/yr

... machine learning, and AI-driven workflows and will be responsible for designing and implementing ... Location Requirement: This position is eligible for remote work within any state Dutch Bros ...

Data Solutions Engineer

Tempe, AZ ยท On-site +1

$91K - $156K/yr

Stay abreast of the latest trends in cloud computing, machine learning, AI, and data engineering. Explore new technologies and methodologies to continuously improve systems, tools, and data processes.

Senior Data & AI Engineer

Phoenix, AZ ยท Remote

$100K - $136K/yr

Position Profile The Senior Data & AI Engineer will need to have deep handsa'on experience in ... Analytics & Machine Learning * Build ML pipelines for risk stratification, cost/utilization ...

Senior DevOps Engineer (US REMOTE)

Phoenix, AZ ยท Remote

$140K - $170K/yr

... s Full-Stack Engineer with expertise in IaC (Terraform), Helm, MySQL, Kubernetes, and CI/CD ... Experience with AI/machine learning technologies is strongly preferred. * Familiarity with TCP/IP ...

Domain Expert - (STEM PhD)

Phoenix, AZ ยท Remote

$80 - $90/hr

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

Domain Expert - (STEM PhD)

Mesa, AZ ยท Remote

$80 - $90/hr

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

Domain Expert - (STEM PhD)

Tucson, AZ ยท Remote

$80 - $90/hr

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

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Remote Tesla Machine Learning Engineer information

What does a Remote Tesla Machine Learning Engineer do?

A Remote Tesla Machine Learning Engineer is responsible for designing, developing, and deploying machine learning models to improve Tesla's products and services. Working from a remote location, they collaborate with teams to analyze large datasets, build predictive models, and optimize algorithms for applications such as autonomous driving, energy management, and manufacturing. They also ensure that machine learning solutions are scalable and meet Tesla's high standards for performance and safety.

What are some common challenges faced by Remote Tesla Machine Learning Engineers, and how can they be overcome?

Remote Tesla Machine Learning Engineers often face challenges such as collaborating across different time zones, ensuring effective communication with cross-functional teams, and maintaining access to high-performance computing resources. To overcome these, engineers typically use collaborative tools for code sharing and project management, participate in regular virtual meetings, and leverage Tesla's robust cloud infrastructure for experimentation and model training. Proactively seeking feedback and staying aligned with team goals are also key practices for success in this remote, fast-paced environment.

What are the key skills and qualifications needed to thrive as a Remote Tesla Machine Learning Engineer, and why are they important?

To thrive as a Remote Tesla Machine Learning Engineer, you need a strong background in computer science, mathematics, and machine learning principles, typically demonstrated through a relevant degree or equivalent experience. Proficiency with Python, TensorFlow or PyTorch, cloud platforms, and version control systems is crucial, and certifications in AI/ML can be advantageous. Exceptional problem-solving, communication, and self-motivation are important soft skills for collaborating remotely and tackling complex projects. These skills enable engineers to design, implement, and scale innovative AI solutions that drive Tesla's technology forward.

What is the difference between Remote Tesla Machine Learning Engineer vs Remote Data Scientist?

AspectRemote Tesla Machine Learning EngineerRemote Data Scientist
Required CredentialsDegree in Computer Science, Engineering, or related field; experience with ML frameworksDegree in Statistics, Mathematics, or related field; strong programming skills
Work EnvironmentCollaborates with engineering teams on autonomous systems and vehicle dataAnalyzes large datasets to extract insights for business or product decisions
Employer & Industry UsagePrimarily in automotive, tech, and autonomous vehicle sectorsAcross tech, finance, healthcare, and various industries

While both roles involve data analysis and machine learning, the Remote Tesla Machine Learning Engineer focuses on developing algorithms for autonomous vehicles, whereas the Remote Data Scientist analyzes data to inform business strategies. The roles share similar credentials but differ in application and industry focus.

What cities in Arizona are hiring for Remote Tesla Machine Learning Engineer jobs? Cities in Arizona with the most Remote Tesla Machine Learning Engineer job openings:
AI Safety Engineer (Red Teaming) - Remote

AI Safety Engineer (Red Teaming) - Remote

micro1 AI

Phoenix, AZ โ€ข Remote

$50 - $90/hr

Part-time

Posted 9 days ago


Job description

Role Title: AI Jailbreak & Prompt-Injection Security Expert


Role Type: Contractor


Location: Remote


micro1 is engaging AI Jailbreak & Prompt-Injection Security Experts to contribute to a cutting-edge customer initiative focused on AI safety and robustness. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required โ€” your domain knowledge is what matters.


Scope of Work

  1. Design and implement advanced methodologies for evaluating AI system safety, focusing on ethical jailbreaks, LLM red teaming, prompt injection, and tool-use abuse scenarios.
  2. Create comprehensive cross-domain elicitation strategies to uncover multi-turn and complex adversarial bypass patterns in AI models.
  3. Develop, maintain, and update regression test suites that systematically test for jailbreak susceptibility and prompt-injection vulnerabilities.
  4. Construct robust evaluation frameworks that stress-test AI models against real-world adversarial threats, aiming to enhance overall system robustness.
  5. Collaborate with technical stakeholders to translate security findings into actionable improvements for model safety and risk mitigation.
  6. Document methodologies, findings, and best practices in clear, well-structured written reports and presentations for both technical and non-technical audiences.


Preferred Qualifications

  1. 2+ years of expertise in adversarial machine learning, LLM red teaming, AI safety evaluation, or a closely related security domain
  2. Proven experience researching, testing, or uncovering vulnerabilities related to ethical jailbreaks, prompt injection, tool-use abuse, or adversarial AI attacks.
  3. Advanced degree (PhD, MS) in computer science, cybersecurity, machine learning, or a relevant discipline, or equivalent operational/professional background.
  4. High credibility and recognition within the AI security or adversarial ML communityโ€”such as published research, open-source tools, or conference presentations.
  5. Exceptional written and verbal communication skills, with a strong focus on clear documentation and collaborative problem-solving.
  6. Prior participation in multi-disciplinary projects or cross-functional AI safety initiatives is a plus.
  7. Familiarity with current LLM architectures, prompt engineering techniques, and security assessment tools is highly desirable.