Strong programming skills in Python, MATLAB, C++, or C * Hands-on work across multiple of the ... Bayesian inference (e.g., beta and gamma distributions) * Markov models and probabilistic system ...
Strong programming skills in Python, MATLAB, C++, or C * Hands-on work across multiple of the ... Bayesian inference (e.g., beta and gamma distributions) * Markov models and probabilistic system ...
Sr Machine Learning Engineer
Irvine, CA · On-site
$112K - $154K/yr
We are seeking a hands-on Senior Machine Learning Engineer to support and enhance machine learning ... Experience with Bayesian or probabilistic modeling frameworks such as PyMC or ArviZ. * Familiarity ...
Sr Machine Learning Engineer
Irvine, CA · On-site
$112K - $154K/yr
We are seeking a hands-on Senior Machine Learning Engineer to support and enhance machine learning ... Experience with Bayesian or probabilistic modeling frameworks such as PyMC or ArviZ. * Familiarity ...
Senior Data Scientist
Foster City, CA · On-site
$180K - $230K/yr
Statistical modeling & algorithms : optimization, Bayesian inference, probabilistic modeling ... AI-native developer : actively uses AI tools (Claude, Cursor, GitHub Copilot, or equivalent) in ...
Senior Data Scientist
Foster City, CA · On-site
$180K - $230K/yr
Statistical modeling & algorithms : optimization, Bayesian inference, probabilistic modeling ... AI-native developer : actively uses AI tools (Claude, Cursor, GitHub Copilot, or equivalent) in ...
Senior Data Scientist
Menlo Park, CA · On-site
$156K - $224K/yr
... probabilistic models (e.g., hierarchical models, state-space models, Bayesian approaches ... Engineering, Computer Science) or equivalent practical experience. * 8+ years of experience ...
Senior Data Scientist
Menlo Park, CA · On-site
$156K - $224K/yr
... probabilistic models (e.g., hierarchical models, state-space models, Bayesian approaches ... Engineering, Computer Science) or equivalent practical experience. * 8+ years of experience ...
... Engineering, or a related quantitative discipline. Experience with simulation systems, probabilistic modeling, Bayesian methods, survival analysis, causal impact modeling, reinforcement learning ...
... Engineering, or a related quantitative discipline. Experience with simulation systems, probabilistic modeling, Bayesian methods, survival analysis, causal impact modeling, reinforcement learning ...
(USA)Staff, Data Scientist
Cupertino, CA · On-site
$143K - $286K/yr
... engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting and uncertainty quantification (quantile regression, Bayesian ...
(USA)Staff, Data Scientist
Cupertino, CA · On-site
$143K - $286K/yr
... engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting and uncertainty quantification (quantile regression, Bayesian ...
(USA)Staff, Data Scientist
Hayward, CA · On-site
$143K - $286K/yr
... engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting and uncertainty quantification (quantile regression, Bayesian ...
(USA)Staff, Data Scientist
Hayward, CA · On-site
$143K - $286K/yr
... engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting and uncertainty quantification (quantile regression, Bayesian ...
... engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting and uncertainty quantification (quantile regression, Bayesian ...
... engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting and uncertainty quantification (quantile regression, Bayesian ...
(USA)Staff, Data Scientist
Sunnyvale, CA · On-site
$143K - $286K/yr
... engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting and uncertainty quantification (quantile regression, Bayesian ...
(USA)Staff, Data Scientist
Sunnyvale, CA · On-site
$143K - $286K/yr
... engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting and uncertainty quantification (quantile regression, Bayesian ...
(USA)Staff, Data Scientist
Mountain View, CA · On-site
$143K - $286K/yr
... engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting and uncertainty quantification (quantile regression, Bayesian ...
(USA)Staff, Data Scientist
Mountain View, CA · On-site
$143K - $286K/yr
... engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting and uncertainty quantification (quantile regression, Bayesian ...
(USA)Staff, Data Scientist
San Mateo, CA · On-site
$143K - $286K/yr
... engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting and uncertainty quantification (quantile regression, Bayesian ...
(USA)Staff, Data Scientist
San Mateo, CA · On-site
$143K - $286K/yr
... engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting and uncertainty quantification (quantile regression, Bayesian ...
Principal Data Scientist
South San Francisco, CA · On-site
$196K/yr
... engineering methods for high-dimensional glycoproteomic data * Bring a diverse modeling toolkit - classical statistical methods, tree-based ensembles, deep learning, probabilistic and Bayesian ...
Principal Data Scientist
South San Francisco, CA · On-site
$196K/yr
... engineering methods for high-dimensional glycoproteomic data * Bring a diverse modeling toolkit - classical statistical methods, tree-based ensembles, deep learning, probabilistic and Bayesian ...
(USA)Staff, Data Scientist
San Jose, CA · On-site
$143K - $286K/yr
... engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting and uncertainty quantification (quantile regression, Bayesian ...
(USA)Staff, Data Scientist
San Jose, CA · On-site
$143K - $286K/yr
... engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting and uncertainty quantification (quantile regression, Bayesian ...
(USA)Staff, Data Scientist
Milpitas, CA · On-site
$143K - $286K/yr
... engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting and uncertainty quantification (quantile regression, Bayesian ...
(USA)Staff, Data Scientist
Milpitas, CA · On-site
$143K - $286K/yr
... engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting and uncertainty quantification (quantile regression, Bayesian ...
(USA)Staff, Data Scientist
Fremont, CA · On-site
$143K - $286K/yr
... engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting and uncertainty quantification (quantile regression, Bayesian ...
(USA)Staff, Data Scientist
Fremont, CA · On-site
$143K - $286K/yr
... engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting and uncertainty quantification (quantile regression, Bayesian ...
... engineering methods for high-dimensional glycoproteomic data * Bring a diverse modeling toolkit - classical statistical methods, tree-based ensembles, deep learning, probabilistic and Bayesian ...
... engineering methods for high-dimensional glycoproteomic data * Bring a diverse modeling toolkit - classical statistical methods, tree-based ensembles, deep learning, probabilistic and Bayesian ...
... engineering methods for high-dimensional glycoproteomic data * Bring a diverse modeling toolkit classical statistical methods, tree-based ensembles, deep learning, probabilistic and Bayesian ...
Quick apply
... engineering methods for high-dimensional glycoproteomic data * Bring a diverse modeling toolkit classical statistical methods, tree-based ensembles, deep learning, probabilistic and Bayesian ...
Senior Data Scientist
Menlo Park, CA · On-site
... Engineering and peer Data Scientists on shared infrastructure, upstream dependencies, and ... as hierarchical, Bayesian, probabilistic, deep learning, or state-space models. • Strong ...
Senior Data Scientist
Menlo Park, CA · On-site
... Engineering and peer Data Scientists on shared infrastructure, upstream dependencies, and ... as hierarchical, Bayesian, probabilistic, deep learning, or state-space models. • Strong ...
Senior Autonomy Systems Software Engineer
$200K - $245K/yr
Strong programming skills in Python, MATLAB, C++, or C * Hands-on work across multiple of the ... Bayesian inference (e.g., beta and gamma distributions) * Markov models and probabilistic system ...
Quick apply
Senior Autonomy Systems Software Engineer
$200K - $245K/yr
Strong programming skills in Python, MATLAB, C++, or C * Hands-on work across multiple of the ... Bayesian inference (e.g., beta and gamma distributions) * Markov models and probabilistic system ...
Senior Autonomy Systems Software Engineer
Mountain View, CA · On-site
$200K - $245K/yr
Strong programming skills in Python, MATLAB, C++, or C * Hands-on work across multiple of the ... Bayesian inference (e.g., beta and gamma distributions) * Markov models and probabilistic system ...
Senior Autonomy Systems Software Engineer
Mountain View, CA · On-site
$200K - $245K/yr
Strong programming skills in Python, MATLAB, C++, or C * Hands-on work across multiple of the ... Bayesian inference (e.g., beta and gamma distributions) * Markov models and probabilistic system ...
Probabilistic Programming Bayesian information
What are the typical challenges faced by professionals working in Probabilistic Programming with a Bayesian focus, and how can they be addressed?
Professionals working in Probabilistic Programming with a Bayesian focus often encounter challenges related to model complexity, computational efficiency, and communicating results to non-technical stakeholders. Building accurate Bayesian models requires careful selection of priors and an understanding of underlying data distributions, which can be demanding without robust domain expertise. Additionally, computational demands can be high, especially for large datasets or complex hierarchical models, making efficient sampling and approximation methods essential. Collaborating closely with domain experts and leveraging modern probabilistic programming frameworks can help address these challenges and ensure practical, interpretable results.
What is probabilistic programming in the context of Bayesian statistics?
Probabilistic programming in the context of Bayesian statistics refers to writing computer programs that use probability distributions and Bayesian inference to model uncertainty and learn from data. These programs allow users to define complex probabilistic models using code, making it easier to specify, fit, and analyze Bayesian models. Probabilistic programming languages, such as Stan, PyMC, or Edward, provide tools to automate inference, enabling practitioners to focus on modeling rather than mathematical derivations. This approach is widely used in fields like machine learning, data science, and scientific research to handle uncertainty and make predictions.
What is the difference between Probabilistic Programming Bayesian vs Data Scientist?
| Aspect | Probabilistic Programming Bayesian | Data Scientist |
|---|---|---|
| Required credentials | Background in statistics, probability, programming | Statistics, computer science, or related degree |
| Work environment | Research, modeling, algorithm development | Data analysis, visualization, business insights |
| Industry usage | AI, machine learning, research projects | Business, finance, tech, healthcare |
Probabilistic Programming Bayesian focuses on developing models using Bayesian methods and probabilistic programming languages, often in research or AI development. Data Scientists analyze data to extract insights, build predictive models, and support decision-making. While both roles require statistical knowledge, Bayesian programmers specialize in probabilistic modeling, whereas Data Scientists apply a broader set of data analysis techniques.
What are the key skills and qualifications needed to thrive as a Probabilistic Programming Bayesian specialist, and why are they important?
To thrive as a Probabilistic Programming Bayesian specialist, you need a strong background in statistics, probability theory, and Bayesian inference, often supported by a degree in mathematics, statistics, computer science, or a related field. Expertise with probabilistic programming languages (such as Stan, PyMC, or TensorFlow Probability) and familiarity with statistical modeling software are also essential. Analytical thinking, problem-solving, and effective communication skills help translate complex models into actionable insights and collaborate with interdisciplinary teams. These skills and qualities are crucial for developing robust, interpretable models that inform decision-making in research and industry applications.
What are popular job titles related to Probabilistic Programming Bayesian jobs in California? For Probabilistic Programming Bayesian jobs in California, the most frequently searched job titles are:
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What cities in California are hiring for Probabilistic Programming Bayesian jobs? Cities in California with the most Probabilistic Programming Bayesian job openings:
Other
Medical, Dental, Vision, Life, Retirement, PTO
Re-posted 16 days ago
Job description
We are looking for a Senior Autonomy Software Systems Engineer who can derive requirements from first principles for safe and mission-critical autonomous behavior across both commercial and defense applications. An ideal candidate will have a background in developing algorithms for autonomy or robotics in aerospace, defense, or automotive domains. This will be used to support our safety claims about safe perception, motion planning, and control for autonomous robots deployed in both commercial freight and defense logistics environments.
In this role, you will:
- Collaborate closely with Autonomy Software teams by using first-principles analysis to develop requirements for safe perception, localization, prediction, motion planning, and/or control algorithms.
- Identify edge cases that could help us expose weaknesses in our system prior to encountering them in on-road environments.
- Provide analysis to support complex autonomy system design trade-offs to inform system design decisions affecting safety and performance.
- Support development of simulation scenarios, structured track testing, on-road road testing, and hardware-in-the-loop testing.
What you'll bring:
- Deep understanding of kinematics, dynamics, and system modeling
- Strong programming skills in Python, MATLAB, C++, or C
- Hands-on work across multiple of the following areas:
- Sensor fusion and object tracking (e.g., Kalman filtering, particle filters, least squares estimation)
- Machine learning methods (e.g., neural networks, SVMs, kNN, regression models, decision trees)
- Classical computer vision (e.g., edge/corner detection, camera calibration, optics)
- Motion planning (e.g., A*, RRT, potential fields)
- Control systems (e.g., PID, nonlinear control, model predictive control)
- Strong foundation in probability and statistics, including appropriate application of distributions (e.g., Gaussian, Poisson, binomial)
- Working knowledge of autonomy system architectures and system-level design
- Background in one or more of the following:
- Bayesian inference (e.g., beta and gamma distributions)
- Markov models and probabilistic system modeling
- Simulation development and validation environments
- System reliability analysis
- Exposure to safety-critical standards such as ISO 26262, DO-178, or IEC 61508 (e.g., ASIL-D, DAL A, SIL 4)
- Experience with safety analysis methodologies (e.g., FTA, FMEA, HARA)
- Understanding of redundancy strategies and fault-tolerant system design
- Familiarity with SOTIF, UL 4600, and safety case development (e.g., Goal Structuring Notation)
- Knowledge of real-time, safety-critical systems
- Experience contributing to verification and validation (V&V) efforts or full testing campaigns
What we offer:
- Competitive compensation package including equity and annual bonuses
- Excellent Medical, Dental, and Vision plans through Kaiser Permanente, Cigna, and MetLife (including a medical plan with infertility benefits)
- MetLife Legal Services, Identity & Fraud Protection, Hospital Indemnity Insurance, Accident Insurance, & Critical Illness Insurance
- Flexible PTO, 10 paid holidays, and generous parental leave policies
- Our office is centrally located in Mountain View, CA
- Office perks: dog-friendly, free catered lunch, a fully stocked kitchen, and free EV charging
- Long Term Disability, Short Term Disability, Life Insurance
- Wellbeing Benefits - Headspace through Cigna, Calm through Kaiser, One Medical, Gympass, Spring Health through Cigna, Rula (mental health navigation)
- Fidelity 401(k)
- Commuter, FSA, Dependent Care FSA, HSA
- Various incentive programs (referral bonuses, patent bonuses, etc.)
About Kodiak Labor Solutions
Sourced by ZipRecruiter
Industry
Construction
Company size
51 - 200 Employees
Headquarters location
Indianapolis, IN, US