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Remote Python Llm Jobs in Missouri (NOW HIRING)

$240K - $290K/yr

... proficiency in Python and/or TypeScript. * Experience building and maintaining backend systems ... Remote-first flexibility across Europe and the US, with optional access to major tech hubs. * High ...

Strong programming skills in Python with expertise in PyTest and test automation frameworks * Solid ... Remote-first work environment * 20 paid time off days plus U.S. holidays * Access to a modern AI ...

$45.25 - $60.50/hr

Strong programming skills, particularly in Python and JavaScript. * Experience with cloud platforms ... Flexible, remote-friendly working model across Europe or selected hubs. * 25 days of annual leave ...

Remote, Europe Full Time Experienced Engineering Manager +6 Years of Experience Who We Are At Yuno ... Proficiency in Python and/or SQL; comfort navigating across modern data stacks. * Deep ...

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Remote Python Llm information

What is a Remote Python LLM job?

A Remote Python LLM job typically involves working with large language models (LLMs) like GPT or similar AI technologies using the Python programming language, while operating remotely. Professionals in this role develop, fine-tune, and deploy machine learning models, especially those focused on natural language processing (NLP) tasks. Responsibilities may include building Python applications that integrate with LLMs, data preprocessing, and collaborating with teams across different locations. The remote aspect allows for flexible work arrangements and access to global opportunities.

What are some common collaboration methods used by Remote Python LLM engineers when working with cross-functional teams?

Remote Python LLM engineers frequently collaborate with data scientists, product managers, and other developers through virtual meetings, code reviews, and shared documentation platforms. Tools like Slack, GitHub, and Jira are often used to ensure smooth communication and project tracking, despite working across different time zones. Regular stand-ups and sprint planning sessions help align objectives and keep everyone updated on progress. Proactive communication and clear documentation are key to overcoming the challenges of remote, distributed teamwork in this role.

What are the key skills and qualifications needed to thrive as a Remote Python LLM Engineer, and why are they important?

To thrive as a Remote Python LLM Engineer, you need strong proficiency in Python programming, experience with large language models (LLMs), and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), cloud platforms, and version control systems like Git is typically required. Excellent problem-solving abilities, self-motivation, and effective communication are crucial soft skills for remote collaboration and troubleshooting. These skills ensure you can develop, deploy, and maintain advanced language models efficiently while working independently in distributed teams.
What are the most commonly searched types of Python Llm jobs in Missouri? The most popular types of Python Llm jobs in Missouri are:
What are popular job titles related to Remote Python Llm jobs in Missouri? For Remote Python Llm jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Remote Python Llm jobs in Missouri look for? The top searched job categories for Remote Python Llm jobs in Missouri are:
What cities in Missouri are hiring for Remote Python Llm jobs? Cities in Missouri with the most Remote Python Llm job openings:

Member of Technical Staff, Trust & Safety Engineer

Jobgether

On-site, Remote

$240K - $290K/yr

Full-time

Posted 9 days ago


Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Member of Technical Staff, Trust & Safety Engineer based in Netherlands.

This is a high-impact engineering role focused on ensuring that advanced generative AI systems are safe, reliable, and aligned with responsible usage at scale. You will work at the intersection of machine learning, platform infrastructure, and policy enforcement, helping shape how next-generation AI models are deployed safely to millions of users. The role involves designing and implementing safety systems, building red-teaming frameworks, and translating ambiguous and evolving trust & safety challenges into robust technical solutions. You will collaborate closely with product, research, legal, and policy teams, contributing directly to both pre-launch safeguards and post-launch monitoring. Operating in a fast-moving environment, you will help define best practices where none yet exist, playing a critical role in shaping the safety foundation of cutting-edge AI technology.

Accountabilities
  • Act as a core Trust & Safety engineering partner embedded within product and research teams, supporting safe design and launch of AI systems from early development through production monitoring.
  • Design, build, and maintain safety infrastructure that ensures responsible deployment of generative AI models at large scale.
  • Develop and continuously improve red-teaming systems to identify harmful outputs, policy violations, and adversarial behavior before production release.
  • Translate ambiguous, evolving trust & safety requirements into concrete, scalable technical solutions and enforcement mechanisms.
  • Build internal tooling and systems for content moderation, policy enforcement, abuse detection, and safety evaluation.
  • Collaborate with legal, policy, and product teams to define safety rules, interpret guidelines, and implement technical controls.
  • Work closely with machine learning researchers to evaluate model behavior and improve safety performance across iterations.
  • Contribute to system reliability, performance optimization, logging, monitoring, and incident response for safety-critical infrastructure.
  • Support the development of data pipelines and analytical systems to detect abuse patterns and policy violations at scale.
  • Continuously improve engineering quality, robustness, and maintainability across safety-related codebases and systems.
Requirements
  • 3+ years of software engineering experience in production environments, with strong proficiency in Python and/or TypeScript.
  • Experience building and maintaining backend systems, infrastructure, or distributed systems in cloud environments (AWS or GCP).
  • Strong ownership mindset with the ability to design, build, and operate systems end-to-end, including monitoring and incident response.
  • Experience working across the stack, including backend services, internal tooling, data pipelines, and infrastructure debugging.
  • Familiarity with analytics systems or large-scale data infrastructure, ideally involving event data, abuse detection, or behavioral signals.
  • Ability to translate ambiguous policy, safety, or compliance requirements into clear technical implementations.
  • Strong collaboration and communication skills, especially when working with legal, policy, research, and product stakeholders.
  • Experience designing or supporting evaluation systems, red-teaming frameworks, or model safety testing is a plus.
  • Comfort working in high-ambiguity environments where processes and solutions are still being defined.
  • Strong written communication skills with the ability to document technical decisions and trade-offs clearly.
  • Open-minded, proactive, and highly collaborative approach to engineering work.
  • Interest in AI safety, generative models, or responsible AI deployment is strongly preferred.
Benefits
  • Competitive compensation package ranging from $240K - $290K (based on experience and location adjustments).
  • Opportunity to work at the forefront of generative AI and world-model simulation technology.
  • Remote-first flexibility across Europe and the US, with optional access to major tech hubs.
  • High-impact role shaping safety systems used by millions of users globally.
  • Collaborative environment working closely with leading researchers, engineers, and policy experts.
  • Strong ownership culture with autonomy to define systems and safety approaches from the ground up.
  • Exposure to cutting-edge AI infrastructure, including LLM-based safety systems and large-scale simulation models.
  • Inclusive and mission-driven engineering culture focused on responsible AI development.
  • Opportunity to work on foundational problems in AI safety, evaluation, and system reliability.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
 Why Apply Through Jobgether? 
 
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
 
 
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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