Deep expertise in MDPs, policy gradient methods (PPO, SAC), and temporal difference learning * Hands-on experience with Gymnasium-based environments and reward engineering (sparse vs. dense ...
Deep expertise in MDPs, policy gradient methods (PPO, SAC), and temporal difference learning * Hands-on experience with Gymnasium-based environments and reward engineering (sparse vs. dense ...
Senior Staff Machine Learning Engineer - Autonomous Driving Foundation Models
Santa Clara, CA · On-site
$122K - $168K/yr
As a Senior Staff Machine Learning Engineer, you will architect the transition from behavior ... Deep understanding of Sequential Decision Making , World Models, or Policy Gradient methods.
Senior Staff Machine Learning Engineer - Autonomous Driving Foundation Models
Santa Clara, CA · On-site
$122K - $168K/yr
As a Senior Staff Machine Learning Engineer, you will architect the transition from behavior ... Deep understanding of Sequential Decision Making , World Models, or Policy Gradient methods.
... gradient checkpointing • Solid understanding of deep learning architectures (transformers, attention mechanisms, diffusion/flow matching) and optimization techniques • Experience working with ...
... gradient checkpointing • Solid understanding of deep learning architectures (transformers, attention mechanisms, diffusion/flow matching) and optimization techniques • Experience working with ...
Senior Machine Learning Engineer - Engineering Intelligence Systems
Calabasas, CA · On-site
$110K - $151K/yr
Integrate Explainable AI (XAI) methods (e.g., SHAP, LIME, attention visualization, or gradient ... Expand machine learning models portfolio for engineering and simulation-driven applications.
Senior Machine Learning Engineer - Engineering Intelligence Systems
Calabasas, CA · On-site
$110K - $151K/yr
Integrate Explainable AI (XAI) methods (e.g., SHAP, LIME, attention visualization, or gradient ... Expand machine learning models portfolio for engineering and simulation-driven applications.
Experience with NN architectures such as CNNs, AEs, GANs and with ensemble learning methods including gradient boosting and random forests is preferred. Validation and Deployment * Apply model ...
Experience with NN architectures such as CNNs, AEs, GANs and with ensemble learning methods including gradient boosting and random forests is preferred. Validation and Deployment * Apply model ...
... learning algorithms (e.g. SVM, Random Forests, Gradient Boosting, Log-Log regression, XGBoost, Lasso, Ridge, Clustering techniques, Neural Networks and others) • Regression (e.g. ? Linear/Logistic ...
... learning algorithms (e.g. SVM, Random Forests, Gradient Boosting, Log-Log regression, XGBoost, Lasso, Ridge, Clustering techniques, Neural Networks and others) • Regression (e.g. ? Linear/Logistic ...
Deep expertise in MDPs, policy gradient methods (PPO, SAC), and temporal difference learning * Hands-on experience with Gymnasium-based environments and reward engineering (sparse vs. dense ...
Deep expertise in MDPs, policy gradient methods (PPO, SAC), and temporal difference learning * Hands-on experience with Gymnasium-based environments and reward engineering (sparse vs. dense ...
Experience with NN architectures such as CNNs, AEs, GANs and with ensemble learning methods including gradient boosting and random forests is preferred. Validation and Deployment * Apply model ...
Experience with NN architectures such as CNNs, AEs, GANs and with ensemble learning methods including gradient boosting and random forests is preferred. Validation and Deployment * Apply model ...
Staff, Data Scientist
Milpitas, CA · On-site
$143K - $286K/yr
Create robust machine learning models using structured and unstructured data sets and advanced algorithms, including Neural Networks, Regression Models, and Gradient Boosting Algorithms
Staff, Data Scientist
Milpitas, CA · On-site
$143K - $286K/yr
Create robust machine learning models using structured and unstructured data sets and advanced algorithms, including Neural Networks, Regression Models, and Gradient Boosting Algorithms
Staff, Data Scientist
San Mateo, CA · On-site
$143K - $286K/yr
Create robust machine learning models using structured and unstructured data sets and advanced algorithms, including Neural Networks, Regression Models, and Gradient Boosting Algorithms
Staff, Data Scientist
San Mateo, CA · On-site
$143K - $286K/yr
Create robust machine learning models using structured and unstructured data sets and advanced algorithms, including Neural Networks, Regression Models, and Gradient Boosting Algorithms
Senior Staff Machine Learning Engineer - Autonomous Driving Foundation Models
Santa Clara, CA · On-site
$122K - $168K/yr
As a Senior Staff Machine Learning Engineer, you will architect the transition from behavior ... Deep understanding of Sequential Decision Making , World Models, or Policy Gradient methods.
Senior Staff Machine Learning Engineer - Autonomous Driving Foundation Models
Santa Clara, CA · On-site
$122K - $168K/yr
As a Senior Staff Machine Learning Engineer, you will architect the transition from behavior ... Deep understanding of Sequential Decision Making , World Models, or Policy Gradient methods.
Staff, Data Scientist
San Jose, CA · On-site
$143K - $286K/yr
Create robust machine learning models using structured and unstructured data sets and advanced algorithms, including Neural Networks, Regression Models, and Gradient Boosting Algorithms
Staff, Data Scientist
San Jose, CA · On-site
$143K - $286K/yr
Create robust machine learning models using structured and unstructured data sets and advanced algorithms, including Neural Networks, Regression Models, and Gradient Boosting Algorithms
Experience with NN architectures such as CNNs, AEs, GANs and with ensemble learning methods including gradient boosting and random forests is preferred. Validation and Deployment * Apply model ...
Experience with NN architectures such as CNNs, AEs, GANs and with ensemble learning methods including gradient boosting and random forests is preferred. Validation and Deployment * Apply model ...
Experience with NN architectures such as CNNs, AEs, GANs and with ensemble learning methods including gradient boosting and random forests is preferred. Validation and Deployment * Apply model ...
Experience with NN architectures such as CNNs, AEs, GANs and with ensemble learning methods including gradient boosting and random forests is preferred. Validation and Deployment * Apply model ...
Senior Machine Learning Engineer, E-commerce Feed Recommendation
San Jose, CA · On-site
$212K - $387K/yr
... Gradient Boosting Trees, Deep Neural Networks, Wide and Deep etc. - Experience in Deep Learning Tools such as tensorflow/pytorch. - Experience with at least one programming language like C++/Python ...
Senior Machine Learning Engineer, E-commerce Feed Recommendation
San Jose, CA · On-site
$212K - $387K/yr
... Gradient Boosting Trees, Deep Neural Networks, Wide and Deep etc. - Experience in Deep Learning Tools such as tensorflow/pytorch. - Experience with at least one programming language like C++/Python ...
Staff Machine Learning Engineer (Infra), Driver Understanding and Evaluation
Mountain View, CA · On-site
The DUE Machine Learning team will build and operate scalable machine learning and data systems ... Strong expertise in distributed training techniques, including gradient sharding and optimization ...
Staff Machine Learning Engineer (Infra), Driver Understanding and Evaluation
Mountain View, CA · On-site
The DUE Machine Learning team will build and operate scalable machine learning and data systems ... Strong expertise in distributed training techniques, including gradient sharding and optimization ...
Data Science
San Francisco, CA · On-site
Understanding of various machine learning algorithms (e.g. SVM, Random Forests, Gradient Boosting, Log-Log regression, XGBoost, Lasso, Ridge, Clustering techniques, Neural Networks and others)
Data Science
San Francisco, CA · On-site
Understanding of various machine learning algorithms (e.g. SVM, Random Forests, Gradient Boosting, Log-Log regression, XGBoost, Lasso, Ridge, Clustering techniques, Neural Networks and others)
Data Science
San Francisco, CA · Remote
Understanding of various machine learning algorithms (e.g. SVM, Random Forests, Gradient Boosting, Log-Log regression, XGBoost, Lasso, Ridge, Clustering techniques, Neural Networks and others)
Data Science
San Francisco, CA · Remote
Understanding of various machine learning algorithms (e.g. SVM, Random Forests, Gradient Boosting, Log-Log regression, XGBoost, Lasso, Ridge, Clustering techniques, Neural Networks and others)
Deep expertise in modern recommendation and ranking techniques such as gradient boosted trees and deep learning based ranking models. * Experience building and operating ML systems at scale in ...
Deep expertise in modern recommendation and ranking techniques such as gradient boosted trees and deep learning based ranking models. * Experience building and operating ML systems at scale in ...
Staff, Data Scientist
Mountain View, CA · On-site
$143K - $286K/yr
Create robust machine learning models using structured and unstructured data sets and advanced algorithms, including Neural Networks, Regression Models, and Gradient Boosting Algorithms
Staff, Data Scientist
Mountain View, CA · On-site
$143K - $286K/yr
Create robust machine learning models using structured and unstructured data sets and advanced algorithms, including Neural Networks, Regression Models, and Gradient Boosting Algorithms
Gradient Learning information
See California salary details
$9.18 - $16.48
13% of jobs
$21.14 is the 25th percentile. Wages below this are outliers.
$16.48 - $23.77
19% of jobs
$23.77 - $31.07
16% of jobs
The median wage is $32.40 / hr.
$31.07 - $38.37
12% of jobs
$38.37 - $45.67
9% of jobs
$52.44 is the 75th percentile. Wages above this are outliers.
$45.67 - $52.96
7% of jobs
$52.96 - $60.26
6% of jobs
$60.26 - $67.56
5% of jobs
$67.56 - $74.86
5% of jobs
$74.86 - $82.15
4% of jobs
$82.15 - $89.45
3% of jobs
$9
$41
$89
How much do gradient learning jobs pay per hour?
As of Jul 3, 2026, the average hourly pay for gradient learning in California is $41.54, according to ZipRecruiter salary data. Most workers in this role earn between $21.42 and $57.44 per hour, depending on experience, location, and employer.
What are the key skills and qualifications needed to thrive as a Gradient Learning specialist, and why are they important?
To thrive as a Gradient Learning specialist, you need expertise in instructional design, educational technology integration, and a background in teaching or curriculum development, often supported by a relevant degree. Familiarity with learning management systems (LMS), digital assessment tools, and platforms like Google Classroom is common in this role. Strong communication, collaboration, and problem-solving skills are essential for engaging educators and supporting student-centered learning. These skills ensure the effective implementation of personalized learning strategies and foster successful educational outcomes.
How does a professional in Gradient Learning typically collaborate with educators and technology teams to implement personalized learning solutions?
Professionals working in Gradient Learning roles often serve as a bridge between educators and technology teams, ensuring that personalized learning platforms are effectively integrated into classroom environments. They collaborate with teachers to understand classroom needs, provide training, and gather feedback to refine digital tools. Simultaneously, they work closely with developers and product managers to relay user insights and help prioritize features that enhance student learning experiences. This cross-functional collaboration is essential for creating solutions that are both pedagogically sound and technically robust.
What is Gradient Learning?
Gradient Learning is an education-focused nonprofit organization that partners with schools and educators to develop innovative teaching tools and learning models. Their mission is to support student-centered education by providing resources such as curriculum content, professional development, and technology platforms. Gradient Learning is known for initiatives like the Summit Learning program, which emphasizes personalized learning, project-based instruction, and strong teacher-student relationships. They collaborate with schools to improve educational outcomes and empower teachers to tailor learning experiences to individual student needs.
What are popular job titles related to Gradient Learning jobs in California? For Gradient Learning jobs in California, the most frequently searched job titles are:
What job categories do people searching Gradient Learning jobs in California look for? The top searched job categories for Gradient Learning jobs in California are:
Full-time
Posted 11 days ago
Job description
About Centific
Centific is a frontier AI data foundry that curates diverse, high-quality data, using our purpose-built technology platforms to empower the Magnificent Seven and our enterprise clients with safe, scalable AI deployment. Our team includes more than 150 PhDs and data scientists, along with more than 4,000 AI practitioners and engineers. We harness the power of an integrated solution ecosystem-comprising industry-leading partnerships and 1.8 million vertical domain experts in more than 230 markets-to create contextual, multilingual, pre-trained datasets; fine-tuned, industry-specific LLMs; and RAG pipelines supported by vector databases. Our zero-distance innovation™ solutions for GenAI can reduce GenAI costs by up to 80% and bring solutions to market 50% faster.
Our mission is to bridge the gap between AI creators and industry leaders by bringing best practices in GenAI to unicorn innovators and enterprise customers. We aim to help these organizations unlock significant business value by deploying GenAI at scale, helping to ensure they stay at the forefront of technological advancement and maintain a competitive edge in their respective markets.
About Job
What You'll Do
Required Qualifications
Experience & Education
LLM Post-Training
Agent Engineering
RL Foundations
Preferred Qualifications
Why Join Centific
How to Apply
Send your CV, a description of a technically complex system you personally built or led, and (if applicable) your publication list or open-source contributions to:
diana.moeck@centific.com
Subject: Senior Staff Research Scientist - RL
$250k-$300k +
Centific is an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, citizenship status, age, mental or physical disability, medical condition, sex (including pregnancy), gender identity or expression, sexual orientation, marital status, familial status, veteran status, or any other characteristic protected by applicable law. We consider qualified applicants regardless of criminal histories, consistent with legal requirements.
Centific is a frontier AI data foundry that curates diverse, high-quality data, using our purpose-built technology platforms to empower the Magnificent Seven and our enterprise clients with safe, scalable AI deployment. Our team includes more than 150 PhDs and data scientists, along with more than 4,000 AI practitioners and engineers. We harness the power of an integrated solution ecosystem-comprising industry-leading partnerships and 1.8 million vertical domain experts in more than 230 markets-to create contextual, multilingual, pre-trained datasets; fine-tuned, industry-specific LLMs; and RAG pipelines supported by vector databases. Our zero-distance innovation™ solutions for GenAI can reduce GenAI costs by up to 80% and bring solutions to market 50% faster.
Our mission is to bridge the gap between AI creators and industry leaders by bringing best practices in GenAI to unicorn innovators and enterprise customers. We aim to help these organizations unlock significant business value by deploying GenAI at scale, helping to ensure they stay at the forefront of technological advancement and maintain a competitive edge in their respective markets.
About Job
What You'll Do
- Design simulation environments and digital twins for enterprise workflows
- Post-train LLM agents using RLHF, DPO, GRPO, PPO, and emerging methods
- Build pipelines that convert human-labeled traces and verifiable signals into training data
- Architect multi-turn, tool-using agents with closed learning loops
- Design reward functions and verifiers that resist reward hacking and reflect real task outcomes
- Set the technical bar across the team - architecture, code review, engineering standards
- Mentor researchers and engineers; drive technical direction through influence
- Translate research into production; contribute to publications
Required Qualifications
Experience & Education
- 7+ years in ML/AI research or engineering; 3+ years at senior/staff level
- MS or PhD in Computer Science, Machine Learning, or related field (or equivalent)
- 5+ years hands-on RL - environment design, reward engineering, policy optimization - with at least one production deployment
LLM Post-Training
- 3+ years fine-tuning LLMs with hands-on RL post-training (RLHF, DPO, GRPO, PPO)
- Expert-level implementation of RLHF pipelines, reward modeling (Bradley-Terry), DPO, and KTO
- Working knowledge of modern post-training and rollout-serving libraries (TRL, veRL, OpenRLHF, SkyRL)
Agent Engineering
- Experience building LLM-based agents: tool use, multi-turn reasoning, trajectory evaluation
- Strong Python and software engineering skills - comfortable building production pipelines, not just notebooks
RL Foundations
- Deep expertise in MDPs, policy gradient methods (PPO, SAC), and temporal difference learning
- Hands-on experience with Gymnasium-based environments and reward engineering (sparse vs. dense)
Preferred Qualifications
- Publications at NeurIPS, ICML, ICLR, ACL, COLM, or similar venues
- Open-source contributions to post-training or agent frameworks (TRL, veRL, OpenRLHF, SkyRL)
- Experience with Offline RL (CQL, IQL), Model-based RL / World Models, or Hierarchical RL
- Background in synthetic data generation, simulation, or world models
- Domain experience in healthcare, finance, logistics, or compliance
- Distributed training on GPU clusters
Why Join Centific
- Lead the frontier. Shape a new discipline at the intersection of post-training, simulation, and enterprise AI.
- Ship your science. See your research power real systems across healthcare, finance, and safety-critical operations.
- Collaborate with leaders. Work alongside NVIDIA, Microsoft, and the global AI community.
- Build what matters. Create governed, compliant AI systems enterprises can actually trust.
How to Apply
Send your CV, a description of a technically complex system you personally built or led, and (if applicable) your publication list or open-source contributions to:
diana.moeck@centific.com
Subject: Senior Staff Research Scientist - RL
$250k-$300k +
Centific is an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, citizenship status, age, mental or physical disability, medical condition, sex (including pregnancy), gender identity or expression, sexual orientation, marital status, familial status, veteran status, or any other characteristic protected by applicable law. We consider qualified applicants regardless of criminal histories, consistent with legal requirements.
About Centific
Sourced by ZipRecruiter
Industry
It services
Company size
5,001 - 10,000 Employees
Headquarters location
Redmond, WA, US
Year founded
2020