$76K - $96K/yr
... Bayesian reinforcement learning, and related areas to ensure reliable and secure AI agent ... Ability to collaborate effectively in a remote, international environment while demonstrating ...
New
$76K - $96K/yr
... Bayesian reinforcement learning, and related areas to ensure reliable and secure AI agent ... Ability to collaborate effectively in a remote, international environment while demonstrating ...
New
Remote Bayesian information
What are the key skills and qualifications needed to thrive as a Remote Bayesian, and why are they important?
To thrive as a Remote Bayesian, you need strong statistical knowledge, expertise in Bayesian inference, and a background in mathematics or data science, often supported by an advanced degree. Familiarity with programming languages like Python or R, Bayesian software such as Stan or PyMC, and experience with remote collaboration tools are typically required. Critical thinking, problem-solving, and clear communication are essential soft skills for interpreting results and working with distributed teams. These abilities are vital for delivering accurate, actionable insights in a remote environment where clear analysis and collaboration drive project success.
What is the difference between Remote Bayesian vs Remote Data Scientist?
| Aspect | Remote Bayesian | Remote Data Scientist |
|---|---|---|
| Required Credentials | Background in statistics, Bayesian methods, programming (Python/R) | Statistics, computer science, or related degree; programming skills |
| Work Environment | Research-focused, analytical tasks, often in tech or finance | Data analysis, modeling, business insights across industries |
| Industry Usage | Research institutions, AI, machine learning, finance | Tech companies, consulting, finance, healthcare |
Remote Bayesian specialists focus on Bayesian statistical methods and probabilistic modeling, often in research or AI contexts. Remote Data Scientists have broader roles in data analysis and modeling across various industries. While both roles require strong analytical skills and programming, Remote Bayesian roles emphasize Bayesian techniques, whereas Remote Data Scientist roles encompass a wider range of data analysis tasks.
What is a Remote Bayesian?
A Remote Bayesian is a professional who specializes in Bayesian statistics and probabilistic modeling while working remotely, often in fields like data science, machine learning, or research. They use Bayesian methods to update probabilities and make predictions based on data, collaborating with teams through digital communication tools. Remote Bayesians may work for tech companies, research institutions, or as independent consultants, applying their expertise to solve complex problems without being tied to a physical office location.
How do Remote Bayesian professionals typically collaborate with cross-functional teams given the virtual nature of their work?
Remote Bayesian professionals often work closely with data scientists, engineers, and decision-makers through virtual collaboration tools such as video conferencing, shared code repositories, and project management platforms. Clear communication is key, as they must explain complex probabilistic models and inferences to both technical and non-technical stakeholders. Regular check-ins and documentation help ensure alignment on project goals, data requirements, and model outcomes. This collaborative dynamic fosters an environment where insights from Bayesian analysis can directly inform business or research decisions, despite the physical distance.
What are popular job titles related to Remote Bayesian jobs in Missouri? For Remote Bayesian jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Remote Bayesian jobs in Missouri look for? The top searched job categories for Remote Bayesian jobs in Missouri are:
What cities in Missouri are hiring for Remote Bayesian jobs? Cities in Missouri with the most Remote Bayesian job openings:
$76K - $96K/yr
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 Senior AI Research Scientist (Model-based RL) based in Netherlands.
This role offers the opportunity to shape the future of intelligent industrial automation through advanced artificial intelligence research.
You will develop cutting-edge reinforcement learning systems that enable real-world machines and facilities to continuously learn and optimize performance.
Working at the intersection of AI research, control theory, and industrial applications, you will help transform complex operational environments.
The position combines deep technical exploration with practical deployment, turning innovative research into impactful solutions.
You will collaborate with multidisciplinary experts, contribute to ambitious research initiatives, and influence the direction of AI-driven control systems.
This is an ideal opportunity for a researcher passionate about applying advanced AI techniques to solve large-scale, real-world challenges.
Accountabilities:
- Design, implement, and evaluate model-based reinforcement learning agents, including planning-based controllers such as MPC and MPPI, as well as the software prototypes required for deployment in real industrial control systems.
- Develop learned dynamics models and world models capable of generalizing across different systems, including training approaches such as pretraining, curriculum learning, active learning, adversarial learning, and fine-tuning.
- Research and apply advanced methods in safe reinforcement learning, constrained control, scenario planning, Bayesian reinforcement learning, and related areas to ensure reliable and secure AI agent deployment.
- Translate research discoveries into practical outcomes by developing production-ready solutions and leading the rollout of research initiatives or large-scale projects.
- Communicate research findings, technical developments, and project results clearly through written documentation, presentations, and internal or external discussions.
- Collaborate with research teams, engineers, and external partners to transform innovative AI concepts into impactful industrial applications.
- Mentor and guide Research Engineers by helping them apply advanced AI research methodologies to complex industrial challenges.
- Independently define new research directions and contribute to the long-term evolution of intelligent control technologies.
- PhD in machine learning, control systems, computer science, or a related technical field, or equivalent practical experience with strong expertise in model-based reinforcement learning.
- At least 2 years of research experience in academia or industry after completing a PhD.
- Deep knowledge and hands-on experience in areas such as model-based reinforcement learning, model-free reinforcement learning, safe reinforcement learning, planning algorithms, world models, learned dynamics models, deep learning, or control theory.
- Proven experience building and evaluating AI agents using simulators, including experience addressing the challenges of simulation-to-real-world transfer.
- Strong programming skills in Python and experience with machine learning frameworks such as PyTorch and scientific computing libraries such as SciPy.
- Experience working with scalable experimentation environments and infrastructure such as distributed computing, Ray, Kubernetes, Docker, or cloud platforms like GCP.
- Strong research background demonstrated through publications or contributions in reinforcement learning, control systems, artificial intelligence, or related fields.
- Ability to collaborate effectively in a remote, international environment while demonstrating ownership, transparency, empathy, operational excellence, and strong teamwork.
- Passion for applying AI research to industrial systems and improving efficiency, sustainability, and resource utilization.
- Competitive base salary ranging from 87,681 to 165,379, depending on location tier, experience, qualifications, and other relevant factors.
- Eligibility for meaningful equity participation.
- Fully remote work environment with flexibility across multiple time zones.
- Medical, dental, and vision insurance, with benefits varying depending on location.
- Unlimited paid time off with a required minimum of 20 days per year.
- Paid parental leave, depending on regional policies.
- Flexible stipends supporting workspace setup, personal well-being, and professional development.
- Company-provided MacBook.
- Opportunities for significant ownership, career growth, and professional development in a fast-paced AI-focused environment.
- Access to training programs covering technical skills, product knowledge, customer immersion, and professional growth.
- Remote-first culture built around documentation, asynchronous collaboration, regular team communication, and virtual team-building activities.
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.
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