ML Infra Engineer

About Humble Robotics Working at Humble Robotics means taking on the biggest change in ground transportation in decades. We’re building an autonomous, zero-emissions hauler that dramatically lowers the cost of freight with groundbreaking vision-based AI, designed for today’s global logistics network.We’re a fast-moving, close-knit team of AV industry veterans and innovative thinkers. We don’t believe culture can be engineered - but when it falls into place, it’s a once-in-a-lifetime adventure.Progress has never felt so present.Position Overview We’re looking for an ML infrastructure engineer to help design, build, and scale the foundational systems we need to realize our ambitious vision. You’ll work on tooling and infrastructure that supports every stage of the ML training flywheel and be an important voice in the technical and organizational decisions that shape our work. From areas spanning vehicle compute to data collection to dataset curation to large-scale model training and deployment, help us build reliable, performant, and secure infrastructure that every team at Humble Robotics can rely on. It’s fun here. We are doing cool stuff.The ideal candidate is a first-principles thinker who is comfortable being a broad generalist. Work on every layer of the stack to help make the software iteration loop as fast and efficient as possible. We’re a small team, and your input, experience, and knowledge will play a critical role in shaping every system we build, operate, and depend on to achieve our mission.Key Responsibilities Work on data collection infrastructure that moves sensor data reliably and efficiently from our vehicles into our ML platformDevelop batch compute pipelines for cataloging, exploring, and curating raw data into high-quality training setsDesign and scale distributed ML training on our GPU clustersTake ownership of performance, observability, efficiency, and security across the full pipelinePartner with the ML team to understand their workflows and translate them into reliable infrastructure that accelerates their workMinimum QualificationsExperience building and operating high-availability web services on cloud infrastructureExperience with infrastructure-as-code and configuration management tools (we use Terraform and Ansible)Experience building and maintaining CI/CD pipelines and managing deploymentsFluent in security fundamentals including Linux hardening, network security, and cryptographic principlesHands-on experience with cluster scheduling systems for running large-scale batch computationComfortable reading, writing, and extending non-trivial code (not just scripting)Eligible to work in the United StatesPreferred Qualifications Hands-on experience managing large, high-performance ML training clustersWorking knowledge of distributed training frameworks and high-performance networking for ML workloadsPrior infrastructure experience at an early-stage autonomous vehicle or robotics companyComfort operating as an early team member-high ownership, low ego, fast iterationCompensationThis role is eligible for base salary + benefits + equity compensation. Salary ranges are determined by role, level, and location. Within the range, individual pay is determined by additional factors, including qualifications, skills, experience, and location.Additional Information As part of the interview process, we may use Artificial Intelligence (AI) tools to compare your qualifications and experience to the job description. A human reviews all AI output and makes a final hiring decision. Humble Robotics does not rely on the output to make any employment decisions. Some applicants may have a legal right to opt-out of the use of AI as part of our interview process. Contact [email protected] to exercise this right or if you have further questions on the use of AI tools in our hiring process.Humble Robotics is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, national origin, gender, age, religion, disability, sexual orientation, veteran status, marital status or any other characteristics protected by law. Humble Robotics will consider qualified applicants with arrest and conviction records in a manner consistent with local ordinances.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. About Humble Robotics Working at Humble Robotics means taking on the biggest change in ground transportation in decades. We’re building an autonomous, zero-emissions hauler that dramatically lowers the cost of freight with groundbreaking vision-based AI, designed for today’s global logistics network.We’re a fast-moving, close-knit team of AV industry veterans and innovative thinkers. We don’t believe culture can be engineered - but when it falls into place, it’s a once-in-a-lifetime adventure.Progress has never felt so present.Position Overview We’re looking for an ML infrastructure engineer to help design, build, and scale the foundational systems we need to realize our ambitious vision. You’ll work on tooling and infrastructure that supports every stage of the ML training flywheel and be an important voice in the technical and organizational decisions that shape our work. From areas spanning vehicle compute to data collection to dataset curation to large-scale model training and deployment, help us build reliable, performant, and secure infrastructure that every team at Humble Robotics can rely on. It’s fun here. We are doing cool stuff.The ideal candidate is a first-principles thinker who is comfortable being a broad generalist. Work on every layer of the stack to help make the software iteration loop as fast and efficient as possible. We’re a small team, and your input, experience, and knowledge will play a critical role in shaping every system we build, operate, and depend on to achieve our mission.Key Responsibilities Work on data collection infrastructure that moves sensor data reliably and efficiently from our vehicles into our ML platformDevelop batch compute pipelines for cataloging, exploring, and curating raw data into high-quality training setsDesign and scale distributed ML training on our GPU clustersTake ownership of performance, observability, efficiency, and security across the full pipelinePartner with the ML team to understand their workflows and translate them into reliable infrastructure that accelerates their workMinimum QualificationsExperience building and operating high-availability web services on cloud infrastructureExperience with infrastructure-as-code and configuration management tools (we use Terraform and Ansible)Experience building and maintaining CI/CD pipelines and managing deploymentsFluent in security fundamentals including Linux hardening, network security, and cryptographic principlesHands-on experience with cluster scheduling systems for running large-scale batch computationComfortable reading, writing, and extending non-trivial code (not just scripting)Eligible to work in the United StatesPreferred Qualifications Hands-on experience managing large, high-performance ML training clustersWorking knowledge of distributed training frameworks and high-performance networking for ML workloadsPrior infrastructure experience at an early-stage autonomous vehicle or robotics companyComfort operating as an early team member-high ownership, low ego, fast iterationCompensationThis role is eligible for base salary + benefits + equity compensation. Salary ranges are determined by role, level, and location. Within the range, individual pay is determined by additional factors, including qualifications, skills, experience, and location.Additional Information As part of the interview process, we may use Artificial Intelligence (AI) tools to compare your qualifications and experience to the job description. A human reviews all AI output and makes a final hiring decision. Humble Robotics does not rely on the output to make any employment decisions. Some applicants may have a legal right to opt-out of the use of AI as part of our interview process. Contact [email protected] to exercise this right or if you have further questions on the use of AI tools in our hiring process.Humble Robotics is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, national origin, gender, age, religion, disability, sexual orientation, veteran status, marital status or any other characteristics protected by law. Humble Robotics will consider qualified applicants with arrest and conviction records in a manner consistent with local ordinances.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. About Humble Robotics Working at Humble Robotics means taking on the biggest change in ground transportation in decades. We’re building an autonomous, zero-emissions hauler that dramatically lowers the cost of freight with groundbreaking vision-based AI, designed for today’s global logistics network.We’re a fast-moving, close-knit team of AV industry veterans and innovative thinkers. We don’t believe culture can be engineered - but when it falls into place, it’s a once-in-a-lifetime adventure.Progress has never felt so present.Position Overview We’re looking for an ML infrastructure engineer to help design, build, and scale the foundational systems we need to realize our ambitious vision. You’ll work on tooling and infrastructure that supports every stage of the ML training flywheel and be an important voice in the technical and organizational decisions that shape our work. From areas spanning vehicle compute to data collection to dataset curation to large-scale model training and deployment, help us build reliable, performant, and secure infrastructure that every team at Humble Robotics can rely on. It’s fun here. We are doing cool stuff.The ideal candidate is a first-principles thinker who is comfortable being a broad generalist. Work on every layer of the stack to help make the software iteration loop as fast and efficient as possible. We’re a small team, and your input, experience, and knowledge will play a critical role in shaping every system we build, operate, and depend on to achieve our mission.Key Responsibilities Work on data collection infrastructure that moves sensor data reliably and efficiently from our vehicles into our ML platformDevelop batch compute pipelines for cataloging, exploring, and curating raw data into high-quality training setsDesign and scale distributed ML training on our GPU clustersTake ownership of performance, observability, efficiency, and security across the full pipelinePartner with the ML team to understand their workflows and translate them into reliable infrastructure that accelerates their workMinimum QualificationsExperience building and operating high-availability web services on cloud infrastructureExperience with infrastructure-as-code and configuration management tools (we use Terraform and Ansible)Experience building and maintaining CI/CD pipelines and managing deploymentsFluent in security fundamentals including Linux hardening, network security, and cryptographic principlesHands-on experience with cluster scheduling systems for running large-scale batch computationComfortable reading, writing, and extending non-trivial code (not just scripting)Eligible to work in the United StatesPreferred Qualifications Hands-on experience managing large, high-performance ML training clustersWorking knowledge of distributed training frameworks and high-performance networking for ML workloadsPrior infrastructure experience at an early-stage autonomous vehicle or robotics companyComfort operating as an early team member-high ownership, low ego, fast iterationCompensationThis role is eligible for base salary + benefits + equity compensation. Salary ranges are determined by role, level, and location. Within the range, individual pay is determined by additional factors, including qualifications, skills, experience, and location.Additional Information As part of the interview process, we may use Artificial Intelligence (AI) tools to compare your qualifications and experience to the job description. A human reviews all AI output and makes a final hiring decision. Humble Robotics does not rely on the output to make any employment decisions. Some applicants may have a legal right to opt-out of the use of AI as part of our interview process. Contact [email protected] to exercise this right or if you have further questions on the use of AI tools in our hiring process.Humble Robotics is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, national origin, gender, age, religion, disability, sexual orientation, veteran status, marital status or any other characteristics protected by law. Humble Robotics will consider qualified applicants with arrest and conviction records in a manner consistent with local ordinances.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. About Humble Robotics Working at Humble Robotics means taking on the biggest change in ground transportation in decades. We’re building an autonomous, zero-emissions hauler that dramatically lowers the cost of freight with groundbreaking vision-based AI, designed for today’s global logistics network.We’re a fast-moving, close-knit team of AV industry veterans and innovative thinkers. We don’t believe culture can be engineered - but when it falls into place, it’s a once-in-a-lifetime adventure.Progress has never felt so present. Working at Humble Robotics means taking on the biggest change in ground transportation in decades. We’re building an autonomous, zero-emissions hauler that dramatically lowers the cost of freight with groundbreaking vision-based AI, designed for today’s global logistics network.We’re a fast-moving, close-knit team of AV industry veterans and innovative thinkers. We don’t believe culture can be engineered - but when it falls into place, it’s a once-in-a-lifetime adventure.Progress has never felt so present. Position Overview We’re looking for an ML infrastructure engineer to help design, build, and scale the foundational systems we need to realize our ambitious vision. You’ll work on tooling and infrastructure that supports every stage of the ML training flywheel and be an important voice in the technical and organizational decisions that shape our work. From areas spanning vehicle compute to data collection to dataset curation to large-scale model training and deployment, help us build reliable, performant, and secure infrastructure that every team at Humble Robotics can rely on. It’s fun here. We are doing cool stuff.The ideal candidate is a first-principles thinker who is comfortable being a broad generalist. Work on every layer of the stack to help make the software iteration loop as fast and efficient as possible. We’re a small team, and your input, experience, and knowledge will play a critical role in shaping every system we build, operate, and depend on to achieve our mission. Position Overview We’re looking for an ML infrastructure engineer to help design, build, and scale the foundational systems we need to realize our ambitious vision. You’ll work on tooling and infrastructure that supports every stage of the ML training flywheel and be an important voice in the technical and organizational decisions that shape our work. From areas spanning vehicle compute to data collection to dataset curation to large-scale model training and deployment, help us build reliable, performant, and secure infrastructure that every team at Humble Robotics can rely on. It’s fun here. We are doing cool stuff.The ideal candidate is a first-principles thinker who is comfortable being a broad generalist. Work on every layer of the stack to help make the software iteration loop as fast and efficient as possible. We’re a small team, and your input, experience, and knowledge will play a critical role in shaping every system we build, operate, and depend on to achieve our mission. We’re looking for an ML infrastructure engineer to help design, build, and scale the foundational systems we need to realize our ambitious vision. You’ll work on tooling and infrastructure that supports every stage of the ML training flywheel and be an important voice in the technical and organizational decisions that shape our work. From areas spanning vehicle compute to data collection to dataset curation to large-scale model training and deployment, help us build reliable, performant, and secure infrastructure that every team at Humble Robotics can rely on. It’s fun here. We are doing cool stuff.The ideal candidate is a first-principles thinker who is comfortable being a broad generalist. Work on every layer of the stack to help make the software iteration loop as fast and efficient as possible. We’re a small team, and your input, experience, and knowledge will play a critical role in shaping every system we build, operate, and depend on to achieve our mission. We’re looking for an ML infrastructure engineer to help design, build, and scale the foundational systems we need to realize our ambitious vision. You’ll work on tooling and infrastructure that supports every stage of the ML training flywheel and be an important voice in the technical and organizational decisions that shape our work. From areas spanning vehicle compute to data collection to dataset curation to large-scale model training and deployment, help us build reliable, performant, and secure infrastructure that every team at Humble Robotics can rely on. It’s fun here. We are doing cool stuff.The ideal candidate is a first-principles thinker who is comfortable being a broad generalist. Work on every layer of the stack to help make the software iteration loop as fast and efficient as possible. We’re a small team, and your input, experience, and knowledge will play a critical role in shaping every system we build, operate, and depend on to achieve our mission. We’re looking for an ML infrastructure engineer to help design, build, and scale the foundational systems we need to realize our ambitious vision. You’ll work on tooling and infrastructure that supports every stage of the ML training flywheel and be an important voice in the technical and organizational decisions that shape our work. From areas spanning vehicle compute to data collection to dataset curation to large-scale model training and deployment, help us build reliable, performant, and secure infrastructure that every team at Humble Robotics can rely on. It’s fun here. We are doing cool stuff.The ideal candidate is a first-principles thinker who is comfortable being a broad generalist. Work on every layer of the stack to help make the software iteration loop as fast and efficient as possible. We’re a small team, and your input, experience, and knowledge will play a critical role in shaping every system we build, operate, and depend on to achieve our mission. Key Responsibilities Work on data collection infrastructure that moves sensor data reliably and efficiently from our vehicles into our ML platformDevelop batch compute pipelines for cataloging, exploring, and curating raw data into high-quality training setsDesign and scale distributed ML training on our GPU clustersTake ownership of performance, observability, efficiency, and security across the full pipelinePartner with the ML team to understand their workflows and translate them into reliable infrastructure that accelerates their work Key Responsibilities Work on data collection infrastructure that moves sensor data reliably and efficiently from our vehicles into our ML platformDevelop batch compute pipelines for cataloging, exploring, and curating raw data into high-quality training setsDesign and scale distributed ML training on our GPU clustersTake ownership of performance, observability, efficiency, and security across the full pipelinePartner with the ML team to understand their workflows and translate them into reliable infrastructure that accelerates their work Work on data collection infrastructure that moves sensor data reliably and efficiently from our vehicles into our ML platformDevelop batch compute pipelines for cataloging, exploring, and curating raw data into high-quality training setsDesign and scale distributed ML training on our GPU clustersTake ownership of performance, observability, efficiency, and security across the full pipelinePartner with the ML team to understand their workflows and translate them into reliable infrastructure that accelerates their work Work on data collection infrastructure that moves sensor data reliably and efficiently from our vehicles into our ML platformDevelop batch compute pipelines for cataloging, exploring, and curating raw data into high-quality training setsDesign and scale distributed ML training on our GPU clustersTake ownership of performance, observability, efficiency, and security across the full pipelinePartner with the ML team to understand their workflows and translate them into reliable infrastructure that accelerates their work Minimum QualificationsExperience building and operating high-availability web services on cloud infrastructureExperience with infrastructure-as-code and configuration management tools (we use Terraform and Ansible)Experience building and maintaining CI/CD pipelines and managing deploymentsFluent in security fundamentals including Linux hardening, network security, and cryptographic principlesHands-on experience with cluster scheduling systems for running large-scale batch computationComfortable reading, writing, and extending non-trivial code (not just scripting)Eligible to work in the United States Minimum QualificationsExperience building and operating high-availability web services on cloud infrastructureExperience with infrastructure-as-code and configuration management tools (we use Terraform and Ansible)Experience building and maintaining CI/CD pipelines and managing deploymentsFluent in security fundamentals including Linux hardening, network security, and cryptographic principlesHands-on experience with cluster scheduling systems for running large-scale batch computationComfortable reading, writing, and extending non-trivial code (not just scripting)Eligible to work in the United States Experience building and operating high-availability web services on cloud infrastructureExperience with infrastructure-as-code and configuration management tools (we use Terraform and Ansible)Experience building and maintaining CI/CD pipelines and managing deploymentsFluent in security fundamentals including Linux hardening, network security, and cryptographic principlesHands-on experience with cluster scheduling systems for running large-scale batch computationComfortable reading, writing, and extending non-trivial code (not just scripting)Eligible to work in the United States Experience building and operating high-availability web services on cloud infrastructureExperience with infrastructure-as-code and configuration management tools (we use Terraform and Ansible)Experience building and maintaining CI/CD pipelines and managing deploymentsFluent in security fundamentals including Linux hardening, network security, and cryptographic principlesHands-on experience with cluster scheduling systems for running large-scale batch computationComfortable reading, writing, and extending non-trivial code (not just scripting)Eligible to work in the United States Preferred Qualifications Hands-on experience managing large, high-performance ML training clustersWorking knowledge of distributed training frameworks and high-performance networking for ML workloadsPrior infrastructure experience at an early-stage autonomous vehicle or robotics companyComfort operating as an early team member-high ownership, low ego, fast iteration Preferred Qualifications Hands-on experience managing large, high-performance ML training clustersWorking knowledge of distributed training frameworks and high-performance networking for ML workloadsPrior infrastructure experience at an early-stage autonomous vehicle or robotics companyComfort operating as an early team member-high ownership, low ego, fast iteration Hands-on experience managing large, high-performance ML training clustersWorking knowledge of distributed training frameworks and high-performance networking for ML workloadsPrior infrastructure experience at an early-stage autonomous vehicle or robotics companyComfort operating as an early team member-high ownership, low ego, fast iteration Hands-on experience managing large, high-performance ML training clustersWorking knowledge of distributed training frameworks and high-performance networking for ML workloadsPrior infrastructure experience at an early-stage autonomous vehicle or robotics companyComfort operating as an early team member-high ownership, low ego, fast iteration CompensationThis role is eligible for base salary + benefits + equity compensation. Salary ranges are determined by role, level, and location. Within the range, individual pay is determined by additional factors, including qualifications, skills, experience, and location. CompensationThis role is eligible for base salary + benefits + equity compensation. Salary ranges are determined by role, level, and location. Within the range, individual pay is determined by additional factors, including qualifications, skills, experience, and location. This role is eligible for base salary + benefits + equity compensation. Salary ranges are determined by role, level, and location. Within the range, individual pay is determined by additional factors, including qualifications, skills, experience, and location. This role is eligible for base salary + benefits + equity compensation. Salary ranges are determined by role, level, and location. Within the range, individual pay is determined by additional factors, including qualifications, skills, experience, and location. This role is eligible for base salary + benefits + equity compensation. Salary ranges are determined by role, level, and location. Within the range, individual pay is determined by additional factors, including qualifications, skills, experience, and location. Additional Information As part of the interview process, we may use Artificial Intelligence (AI) tools to compare your qualifications and experience to the job description. A human reviews all AI output and makes a final hiring decision. Humble Robotics does not rely on the output to make any employment decisions. Some applicants may have a legal right to opt-out of the use of AI as part of our interview process. Contact [email protected] to exercise this right or if you have further questions on the use of AI tools in our hiring process.Humble Robotics is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, national origin, gender, age, religion, disability, sexual orientation, veteran status, marital status or any other characteristics protected by law. Humble Robotics will consider qualified applicants with arrest and conviction records in a manner consistent with local ordinances. Additional Information As part of the interview process, we may use Artificial Intelligence (AI) tools to compare your qualifications and experience to the job description. A human reviews all AI output and makes a final hiring decision. Humble Robotics does not rely on the output to make any employment decisions. Some applicants may have a legal right to opt-out of the use of AI as part of our interview process. Contact [email protected] to exercise this right or if you have further questions on the use of AI tools in our hiring process.Humble Robotics is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, national origin, gender, age, religion, disability, sexual orientation, veteran status, marital status or any other characteristics protected by law. Humble Robotics will consider qualified applicants with arrest and conviction records in a manner consistent with local ordinances. As part of the interview process, we may use Artificial Intelligence (AI) tools to compare your qualifications and experience to the job description. A human reviews all AI output and makes a final hiring decision. Humble Robotics does not rely on the output to make any employment decisions. Some applicants may have a legal right to opt-out of the use of AI as part of our interview process. Contact [email protected] to exercise this right or if you have further questions on the use of AI tools in our hiring process.Humble Robotics is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, national origin, gender, age, religion, disability, sexual orientation, veteran status, marital status or any other characteristics protected by law. Humble Robotics will consider qualified applicants with arrest and conviction records in a manner consistent with local ordinances. As part of the interview process, we may use Artificial Intelligence (AI) tools to compare your qualifications and experience to the job description. A human reviews all AI output and makes a final hiring decision. Humble Robotics does not rely on the output to make any employment decisions. Some applicants may have a legal right to opt-out of the use of AI as part of our interview process. Contact [email protected] to exercise this right or if you have further questions on the use of AI tools in our hiring process.Humble Robotics is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, national origin, gender, age, religion, disability, sexual orientation, veteran status, marital status or any other characteristics protected by law. Humble Robotics will consider qualified applicants with arrest and conviction records in a manner consistent with local ordinances. As part of the interview process, we may use Artificial Intelligence (AI) tools to compare your qualifications and experience to the job description. A human reviews all AI output and makes a final hiring decision. Humble Robotics does not rely on the output to make any employment decisions. Some applicants may have a legal right to opt-out of the use of AI as part of our interview process. Contact [email protected] to exercise this right or if you have further questions on the use of AI tools in our hiring process.Humble Robotics is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, national origin, gender, age, religion, disability, sexual orientation, veteran status, marital status or any other characteristics protected by law. Humble Robotics will consider qualified applicants with arrest and conviction records in a manner consistent with local ordinances. 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. 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.

• Experience building and operating high-availability web services on cloud infrastructure
• Experience with infrastructure-as-code and configuration management tools (we use Terraform and Ansible)
• Experience building and maintaining CI/CD pipelines and managing deployments
• Fluent in security fundamentals including Linux hardening, network security, and cryptographic principles
• Hands-on experience with cluster scheduling systems for running large-scale batch computation
• Comfortable reading, writing, and extending non-trivial code (not just scripting)
• Eligible to work in the United States, * Hands-on experience managing large, high-performance ML training clusters
• Working knowledge of distributed training frameworks and high-performance networking for ML workloads
• Prior infrastructure experience at an early-stage autonomous vehicle or robotics company
• Comfort operating as an early team member-high ownership, low ego, fast iteration

This role is eligible for base salary + benefits + equity compensation. Salary ranges are determined by role, level, and location. Within the range, individual pay is determined by additional factors, including qualifications, skills, experience, and location.