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Remote Policy Research Jobs in Missouri (NOW HIRING)

Our partner is looking for a Research Engineer (Reinforcement Learning) based in Netherlands. Join ... Flexible vacation policy. * Remote-friendly working environment with flexibility and autonomy. How ...

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Remote Policy Research information

What is remote policy research?

Remote policy research involves analyzing, evaluating, and developing policy recommendations while working from a location outside of a traditional office setting. Professionals in this field gather and interpret data, review legislation, and prepare reports that inform decision-makers, all through virtual collaboration and digital tools. This role typically requires strong analytical skills, attention to detail, and effective communication abilities. Remote policy researchers may work for government agencies, think tanks, nonprofits, or private organizations.

How do remote policy researchers typically collaborate with team members and stakeholders despite working from different locations?

Remote policy researchers commonly use digital collaboration tools like video conferencing, project management platforms, and shared document editors to stay connected with their teams and stakeholders. Regular virtual meetings and clear communication protocols help ensure everyone is aligned on research objectives and deadlines. This setup allows for flexible scheduling but also requires strong self-management and proactive communication skills. Building relationships remotely can be a challenge, but many organizations foster a collaborative environment through virtual check-ins and team-building activities.

What are the key skills and qualifications needed to thrive as a remote policy researcher, and why are they important?

To thrive as a Remote Policy Researcher, you need a strong background in public policy, research methodologies, and data analysis, typically supported by a relevant degree such as political science or public administration. Familiarity with data analysis tools (like Excel, SPSS, or R), digital libraries, and citation management systems is common in the field. Excellent written communication, critical thinking, and self-motivation are essential soft skills for distilling complex information and working independently. These capabilities are crucial for producing high-quality, evidence-based policy recommendations in a remote and collaborative environment.

What is the difference between Remote Policy Research vs Remote Policy Analysis?

AspectRemote Policy ResearchRemote Policy Analysis
CredentialsMaster's degree in public policy, political science, or related fieldMaster's degree in public policy, political science, or related field
Work EnvironmentPrimarily remote, collaborative research teams, data collection, literature reviewPrimarily remote, data interpretation, report writing, policy evaluation
Industry UsageGovernment agencies, think tanks, NGOs, research institutionsGovernment agencies, think tanks, consulting firms, advocacy groups
Common Search IntentResearch methodologies, data collection, policy impact studiesPolicy evaluation, data analysis, report development

Remote Policy Research and Remote Policy Analysis share similar credentials and work environments, often overlapping in industry usage. However, research focuses on gathering and studying data, while analysis emphasizes interpreting data to inform policy decisions. Both roles are essential in shaping effective policies remotely.

What are popular job titles related to Remote Policy Research jobs in Missouri?

For Remote Policy Research jobs in Missouri, the most frequently searched job titles are:

Infographic showing various Remote Policy Research job openings in Missouri as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 17% Part Time, and 2% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution.

Research Engineer (Reinforcement Learning)

Jobgether

Remote

Full-time

Medical, Dental, Vision, PTO

Posted 3 days ago

New


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 Research Engineer (Reinforcement Learning) based in Netherlands.

Join a small, senior engineering team building the next generation of voice- and text-driven AI agents.
You'll focus on post-training models to make agents more capable, reliable, and effective over long-running interactions.
Your work will span environments, verifiers, synthetic data, training experiments, evaluations, and production deployment.
You'll tackle challenging problems such as persistent context, reliable tool use, and multi-turn agent behavior.
The role combines hands-on research and engineering, with a strong emphasis on measurable improvements in model performance.
You'll work closely with experienced engineers in a remote, collaborative environment where technical craft and creativity are highly valued.
Your contributions will directly shape AI systems operating at significant production scale.

Accountabilities
  • Build training environments, verifiers, and supporting infrastructure for post-training models.
  • Own the synthetic data pipeline from data generation through quality assurance and validation.
  • Run end-to-end training experiments, analyze results, and clearly identify the factors driving model improvements.
  • Design and maintain evaluations that models must pass before production releases.
  • Select and adapt suitable open-weight foundation models for specific agent and product requirements.
  • Develop trained behaviors that perform consistently across both voice and text-based agents.
  • Deploy trained models to production and continuously improve them based on real-world usage and feedback.
  • Develop robust approaches to long-horizon interactions, accumulated context, and reliable tool use during live conversations.
Requirements:
  • Strong Python engineering skills and the ability to build reliable, production-quality systems.
  • Demonstrated experience taking a machine learning model from raw data through experimentation and into production.
  • A strong data-centric mindset, with attention to coverage, diversity, quality, and data leakage.
  • The ability to anticipate reward exploitation and design robust rewards, verifiers, and evaluation mechanisms.
  • Practical experience working with GPUs and a realistic understanding of their capabilities and limitations.
  • Strong judgment around when model training is the right solution-and when a simpler approach is preferable.
  • Ability to collaborate effectively within a remote, distributed, and highly autonomous team.
  • Experience with post-training techniques such as fine-tuning, reward design, or reinforcement learning, including approaches such as GRPO, is highly desirable.
  • Familiarity with RL and fine-tuning frameworks such as TRL, verl, OpenRLHF, or custom training loops is a plus.
  • Experience with technologies such as vLLM or SGLang for fast rollouts and FSDP for multi-GPU training is advantageous.
  • Experience training tool-using or multi-turn agents, as well as building execution sandboxes, verifiers, evaluation harnesses, or developer tooling, is valuable.
  • Familiarity with open-weight model families such as Qwen or Llama and techniques such as LoRA is a plus.
Benefits:
  • Opportunity to make a significant impact on a fast-growing developer platform and help shape its future.
  • Collaboration with a small, highly experienced team that values technical excellence, creativity, and ownership.
  • Competitive salary and equity package.
  • Health, dental, and vision benefits.
  • Flexible vacation policy.
  • Remote-friendly working environment with flexibility and autonomy.
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 and identifying potential inconsistencies or verification signals in application materials based on available information. 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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