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Remote Bayesian Jobs in California (NOW HIRING)

We continue to invest time, money and energy into making our onsite, hybrid and remote work ... Bayesian modeling, network-based and mechanistic approaches, and modern deep learning - with hands ...

San Francisco (hybrid) or fully remote from Boston / San Diego Travel: Regular travel to our ... Familiarity with active learning, iterative DMTL design loops, and Bayesian optimisation applied to ...

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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.

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 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.

What is the difference between Remote Bayesian vs Remote Data Scientist?

AspectRemote BayesianRemote Data Scientist
Required CredentialsBackground in statistics, Bayesian methods, programming (Python/R)Statistics, computer science, or related degree; programming skills
Work EnvironmentResearch-focused, analytical tasks, often in tech or financeData analysis, modeling, business insights across industries
Industry UsageResearch institutions, AI, machine learning, financeTech 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 are the most commonly searched types of Bayesian jobs in California? The most popular types of Bayesian jobs in California are:
What cities in California are hiring for Remote Bayesian jobs? Cities in California with the most Remote Bayesian job openings:
Infographic showing various Remote Bayesian job openings in California as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% Hybrid job distribution.
Senior Machine Learning Engineer - VLM/LLM Evaluation

Senior Machine Learning Engineer - VLM/LLM Evaluation

Waymo

Mountain View, CA • On-site, Remote

$204K - $259K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 4 days ago


Job description

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver-to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.

The mission of the Waymo AI Foundations team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate and foster collaborations with other research teams in Alphabet. AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.

This role follows a hybrid work schedule and you will report to a Senior Staff Software Engineer.

You will:

  • Work with a creative team of people who help to build the state-of-the-art Foundation Models that are used throughout Waymo's systems, both onboard autonomous vehicles and offboard in simulation
  • Drive the development or significantly contribute to end-to-end evaluation systems and benchmarks for Waymo Foundation models, encompassing the entire life-cycle from pre-training and supervised fine-tuning (SFT) to reinforcement learning (RL), for evaluating the quality, safety, and realism of embodied AI agents
  • Partner with cross-functional teams within the organization to land innovative tech in production
  • Implement and extend large large scale data and evaluation pipelines.

You have:

  • Bachelor or Master's degree in Computer Science, similar technical field of study, or equivalent practical experience
  • Experience in ML engineering and applied Deep Learning
  • Experience with large scale distributed system
  • Proficient programming skills (eg: Python, C/C++)

We prefer:

  • ML infra experience: training, evaluating and deploying ML models at scale
  • Deep learning experience, especially with generative models, e.g., LLMs/VLMs, and/or reinforcement learning
  • Proficiency and in-depth knowledge of the inner workings of an ML framework (e.g. Pytorch, JAX, Tensorflow)

In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:

  • Health, dental, vision, life, disability insurance
  • Retirement Benefits: 401(k) with company match
  • Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
  • Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary)
  • Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
  • Baby Bonding Leave: 18 weeks
  • Holidays: 13 paid days per year

The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.

Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.

Salary Range
$204,000—$259,000 USD