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Remote Spacex Machine Learning Jobs in Texas (NOW HIRING)

RealPage, Inc.

Data Scientist

Richardson, TX · Remote

$116K - $198K/yr

Machine Learning & Data Science * Develop, evaluate, and deploy predictive and generative models ... Experience building AI solutions that support customer facing products #LI-REMOTE #LI-JL1 Physical ...

RealPage, Inc.

Data Scientist

Richardson, TX · Remote

$116K - $198K/yr

Responsibilities Machine Learning & Data Science * Develop, evaluate, and deploy predictive and ... Experience building AI solutions that support customer facing products #LI-REMOTE #LI-JL1 Physical ...

Blue Cross of Idaho

AI Technical Lead

Meridian, TX · On-site +1

... remote within a mutually acceptable location. #LI-Hybrid Success Looks Like: * AI systems move ... Develop and deploy machine learning and generative AI solutions that support enterprise use cases.

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Remote Spacex Machine Learning information

What does a Remote SpaceX Machine Learning Engineer do?

A Remote SpaceX Machine Learning Engineer uses data-driven algorithms and models to solve complex problems for SpaceX, often focusing on areas such as rocket manufacturing, satellite communications, and mission planning. Working remotely, these engineers collaborate with cross-functional teams to design, develop, and implement machine learning solutions that improve efficiency, safety, and performance. They may analyze large datasets, build predictive models, and deploy AI systems to support SpaceX's ambitious goals in space exploration.

What are some unique challenges of working remotely as a Machine Learning Engineer at SpaceX, and how can candidates prepare for them?

Working remotely as a Machine Learning Engineer at SpaceX presents unique challenges such as collaborating across distributed teams, managing time zones, and maintaining effective communication with colleagues involved in hardware and aerospace projects. To succeed, candidates should be proactive in seeking regular updates, use collaborative tools efficiently, and be comfortable working independently while still aligning with team objectives. Familiarity with remote development environments and a strong ability to document and present complex models are also key to thriving in this role.

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

AspectRemote Spacex Machine LearningRemote Spacex Data Scientist
Required CredentialsAdvanced degree in Computer Science, AI, or related field; experience in ML frameworksDegree in Data Science, Statistics, or related; strong analytical skills
Work EnvironmentDeveloping ML models, algorithms, and AI systems for space applicationsAnalyzing data, creating insights, and supporting decision-making processes
Employer & Industry UsageUsed in AI-driven space missions, autonomous systems, and roboticsApplied in data analysis, reporting, and predictive modeling for space projects

Remote Spacex Machine Learning specialists focus on developing AI models for space technology, while Data Scientists analyze data to inform decisions. Both roles require strong technical skills and often collaborate but serve different core functions within the industry.

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

To excel as a Remote SpaceX Machine Learning Engineer, you need strong expertise in machine learning, data analysis, and programming languages like Python, along with a relevant degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, cloud computing platforms, and version control systems is typically necessary, and certifications in machine learning or data science can be advantageous. Excellent problem-solving skills, strong communication, and the ability to collaborate remotely are key soft skills that help you stand out. These skills ensure you can develop robust ML models that support SpaceX’s technical goals while effectively working within distributed teams.
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Remote Spacex Machine Learning jobs near you
Trust & Safety Engineer (GenAI) - Remote

Trust & Safety Engineer (GenAI) - Remote

micro1 AI

Houston, TX • Remote

$50 - $90/hr

Part-time

Posted 14 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 — 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 community—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.

Apply