Safety Engineer Jobs
Safety Engineer jobs are open across construction, manufacturing, oil and gas, utilities, and government contracting, from entry-level and EHS associate roles to senior and principal engineers, with specializations in process safety, industrial hygiene, and occupational health. Find a role that fits from the openings below and apply directly.
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Join Us in Shaping the Future of Generative AI at Apple!
Are you passionate about building and leading teams that make AI systems safer, more inclusive, and globally representative? Apple is seeking an experienced Engineering Manager to lead a team shaping the future of responsible AI evaluation for the next generation of generative features.
In this role, you will lead a team of machine learning engineers and data scientists working to assess, quantify, and improve the safety and inclusivity of Apple’s Generative-AI powered features and products. You and your team's work will tackle innovative problems in machine learning, particularly focused on large language models for text generation, diffusion models for image generation, and mixed model systems for multimodal applications. You will directly influence how we evaluate, align, and monitor the safety of large language and multimodal models, while upholding Apple's values, privacy, and quality standards.
As part of Apple’s Responsible AI group within the Software Engineering organization, you’ll collaborate with cross-functional partners to minimize unintended consequences across people, systems, and society while elevating feature capabilities and the overall user experience. You’ll set technical direction, anticipate safety risks, and develop a team to deliver trusted, high-quality AI experiences to users around the globe.
Description
We are seeking a visionary Machine Learning Engineering Leader to build, mentor, and develop a high-performing team, driving Responsible AI Evaluation efforts for global generative AI products. In this role, you will provide critical technical direction for operationalizing policy and risk assessments into measurable criteria; designing datasets; developing LLM- and human-in-the-loop methods for data analysis; and overseeing the implementation of data pipelines to produce reliable, scalable insights to inform ship/no-ship product decisions. Pre and Post-launch, you will remain hands-on-analyzing evaluation results, conducting failure investigations, and leveraging human and automated feedback to continuously improve feature safety and build user trust. As a champion for your team, you will foster an inclusive culture of technical excellence, empower senior leadership with safety recommendations, and systematically remove roadblocks to ensure team success. This role heavily draws on applied data science, scientific investigation and interpretation, strategic cross-functional stakeholder management, including negotiating requirements and defending safety metrics to leadership, and metrics reporting and presentation to stakeholders & decision-makers.","responsibilities":"Develop metrics for evaluation of safety and fairness risks inherent to generative models and Gen-AI features
Design datasets, identify data needs, and work on creative solutions, scaling and expanding data coverage through human and synthetic generation methods
Develop sampling strategies and combine human annotation with auto-grading to deliver high-quality, high-confidence insights at a fast pace and large scale
Use and implement data pipelines, and collaborate cross-functionally to execute end-to-end safety evaluations
Drive operational excellence by automating manual workflows, optimizing evaluation velocity, and scaling infrastructure to meet rapid product release cycles.
Distill project findings into insights for product engineering teams and safety policy development
Work with highly-sensitive content with exposure to offensive and controversial content
Preferred Qualifications
Experience working in the Responsible AI space
Passion for building innovative, high-impact products and teams that draw upon interdisciplinary skills
Curiosity about fairness and bias in generative AI systems, and a strong desire to help make the technology more equitable
A Social Science or Humanities background, or other demonstrable interest in socio-technical issues
Prior scientific research and publication experience
Proven track record of contributing to diverse teams in a collaborative environment
Experience working with multimodal models, agentic systems, and/or diverse languages and locales
Experience with compliance and regulatory needs in the AI space, specifically regarding child safety, clinical/health applications, or companionship chatbots
Experience conducting large scale benchmarking across models and capabilities
Minimum Qualifications
MS or PhD in Computer Science, Linguistics, Cognitive Science, HCI, Psychology, Mathematics, Physics, or a similar science or technology field with a strong basis in scientific data collection and analysis + at least 4 years of relevant work experience, or BA/BS with 8+ years of relevant work experience, with 2+ years directly managing engineering teams
Experience gathering and analyzing varied language, image, voice, video, and/or multi-modal data, including human- and LLM-generated data
Experience with LLM-Judges as well as human-in-the-loop techniques, including designing human annotation projects, writing guidelines, and dealing with highly multi-labeled, nuanced, and often conflicting data
Proficiency in data science, machine learning, analytics, programming with Python & Pandas, and AI-assisted coding tools; experience with one or more plotting & visualization libraries
Cross-functional collaboration skills to prioritize competing projects needs, set and maintain schedules for project milestones, and communicate with all levels of team members, as well as internal and external stakeholders
A rigorous approach to metric development; interpretation of experiments and evaluations; and presentation to executives
Comfortable leading a team that works with sensitive or potentially offensive content.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $184,700 and $324,800, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Join Us in Shaping the Future of Generative AI at Apple!
Are you passionate about building and leading teams that make AI systems safer, more inclusive, and globally representative? Apple is seeking an experienced Engineering Manager to lead a team shaping the future of responsible AI evaluation for the next generation of generative features.
In this role, you will lead a team of machine learning engineers and data scientists working to assess, quantify, and improve the safety and inclusivity of Apple’s Generative-AI powered features and products. You and your team's work will tackle innovative problems in machine learning, particularly focused on large language models for text generation, diffusion models for image generation, and mixed model systems for multimodal applications. You will directly influence how we evaluate, align, and monitor the safety of large language and multimodal models, while upholding Apple's values, privacy, and quality standards.
As part of Apple’s Responsible AI group within the Software Engineering organization, you’ll collaborate with cross-functional partners to minimize unintended consequences across people, systems, and society while elevating feature capabilities and the overall user experience. You’ll set technical direction, anticipate safety risks, and develop a team to deliver trusted, high-quality AI experiences to users around the globe.
Description
We are seeking a visionary Machine Learning Engineering Leader to build, mentor, and develop a high-performing team, driving Responsible AI Evaluation efforts for global generative AI products. In this role, you will provide critical technical direction for operationalizing policy and risk assessments into measurable criteria; designing datasets; developing LLM- and human-in-the-loop methods for data analysis; and overseeing the implementation of data pipelines to produce reliable, scalable insights to inform ship/no-ship product decisions. Pre and Post-launch, you will remain hands-on-analyzing evaluation results, conducting failure investigations, and leveraging human and automated feedback to continuously improve feature safety and build user trust. As a champion for your team, you will foster an inclusive culture of technical excellence, empower senior leadership with safety recommendations, and systematically remove roadblocks to ensure team success. This role heavily draws on applied data science, scientific investigation and interpretation, strategic cross-functional stakeholder management, including negotiating requirements and defending safety metrics to leadership, and metrics reporting and presentation to stakeholders & decision-makers.","responsibilities":"Develop metrics for evaluation of safety and fairness risks inherent to generative models and Gen-AI features
Design datasets, identify data needs, and work on creative solutions, scaling and expanding data coverage through human and synthetic generation methods
Develop sampling strategies and combine human annotation with auto-grading to deliver high-quality, high-confidence insights at a fast pace and large scale
Use and implement data pipelines, and collaborate cross-functionally to execute end-to-end safety evaluations
Drive operational excellence by automating manual workflows, optimizing evaluation velocity, and scaling infrastructure to meet rapid product release cycles.
Distill project findings into insights for product engineering teams and safety policy development
Work with highly-sensitive content with exposure to offensive and controversial content
Preferred Qualifications
Experience working in the Responsible AI space
Passion for building innovative, high-impact products and teams that draw upon interdisciplinary skills
Curiosity about fairness and bias in generative AI systems, and a strong desire to help make the technology more equitable
A Social Science or Humanities background, or other demonstrable interest in socio-technical issues
Prior scientific research and publication experience
Proven track record of contributing to diverse teams in a collaborative environment
Experience working with multimodal models, agentic systems, and/or diverse languages and locales
Experience with compliance and regulatory needs in the AI space, specifically regarding child safety, clinical/health applications, or companionship chatbots
Experience conducting large scale benchmarking across models and capabilities
Minimum Qualifications
MS or PhD in Computer Science, Linguistics, Cognitive Science, HCI, Psychology, Mathematics, Physics, or a similar science or technology field with a strong basis in scientific data collection and analysis + at least 4 years of relevant work experience, or BA/BS with 8+ years of relevant work experience, with 2+ years directly managing engineering teams
Experience gathering and analyzing varied language, image, voice, video, and/or multi-modal data, including human- and LLM-generated data
Experience with LLM-Judges as well as human-in-the-loop techniques, including designing human annotation projects, writing guidelines, and dealing with highly multi-labeled, nuanced, and often conflicting data
Proficiency in data science, machine learning, analytics, programming with Python & Pandas, and AI-assisted coding tools; experience with one or more plotting & visualization libraries
Cross-functional collaboration skills to prioritize competing projects needs, set and maintain schedules for project milestones, and communicate with all levels of team members, as well as internal and external stakeholders
A rigorous approach to metric development; interpretation of experiments and evaluations; and presentation to executives
Comfortable leading a team that works with sensitive or potentially offensive content.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $184,700 and $324,800, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Safety Engineer Jobs by Experience Level
Top Cities Hiring Safety Engineers
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Find Safety Engineer JobsSafety Engineer Job Market
Who's Hiring
- SpaceX40
- Northrop Grumman26
- Tesla23
- Lockheed Martin19
- Mortenson Construction18
Top Industries Hiring
- Technology & Software28
- Manufacturing23
- Consulting & Professional Services17
- Electronics & Hardware15
- Construction & Real Estate14
What Employers Look For
The qualifications that appear most often in safety engineer jobs.
- Bachelor's degree in occupational health, engineering, or a closely related field
- OSHA 30-hour construction or general industry certification
- Certified Safety Professional (CSP) designation or active pursuit of it
- Experience conducting job hazard analyses and incident root cause investigations
- Proficiency with safety management software and OSHA recordkeeping systems
- Familiarity with regulatory standards including OSHA, EPA, and NFPA codes
Tips for Your Safety Engineer Job Search
Tailor your resume to certifications
Hiring managers scan for CSP, CIH, or OSHA 30 credentials before reading anything else. List your certifications near the top with the issuing body and date, so they clear the ATS filter before your experience is ever reviewed.
Quantify incident reduction outcomes
Vague phrases like 'improved safety culture' get ignored. Replace them with specific outcomes you drove, such as reducing recordable incident rates, cutting near-miss reports, or bringing a site into regulatory compliance after a citation.
Apply early to roles that fit
Migrate Mate lists safety engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Filter openings by industry sector
Safety engineers in petrochemical plants face entirely different regulatory frameworks than those in healthcare or aerospace. Target openings in sectors where your experience with specific standards, such as OSHA PSM, NFPA, or FAA requirements, is directly transferable.
Prepare for scenario-based interview questions
Interviewers routinely ask you to walk through a real incident investigation you led, not just describe your process in the abstract. Prepare two or three detailed examples using the situation, your analysis, corrective actions, and the measurable outcome.
Negotiate beyond base salary on field roles
Field-based safety engineer positions often come with per diem, vehicle allowances, hazard pay, or relocation packages that vary widely by employer. Ask about each component separately during the offer stage rather than treating the offer as a single number.
Safety Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most safety engineers?
The companies hiring the most safety engineers right now include SpaceX, Northrop Grumman, and Tesla, with the largest share of openings in California, Texas, and Virginia, based on current listings on Migrate Mate as of November 2026. Construction, energy, and large manufacturers tend to post the highest volume of openings year-round.
How many safety engineer jobs are remote?
About 43% of safety engineer openings are fully remote or hybrid as of November 2026, though most of the role requires physical site presence. Sub-areas most likely to offer remote flexibility include corporate EHS program management, safety training development, and compliance auditing that relies on documentation review rather than direct field inspection.
How do you become a safety engineer?
Start with a bachelor's degree in occupational safety, environmental health, civil engineering, or a related technical field. Complete your OSHA 30-hour certification early, then build site experience through internships or entry-level EHS roles. Once you have enough field hours, sit for the Associate Safety Professional exam as a stepping stone to the Certified Safety Professional credential, which most senior roles require.
How do you get hired as a safety engineer with little experience?
Focus on roles titled EHS coordinator, safety specialist, or loss control associate, which are designed for candidates still building field hours. Completing an OSHA 30-hour course and volunteering for safety committee work at any current employer signals genuine commitment. Contractors and staffing firms that support large construction projects frequently hire entry-level safety personnel who gain rapid, hands-on exposure.
What does the safety engineer interview process look like?
Most processes start with a recruiter screen focused on certifications and industry background, followed by a technical interview where you walk through a real incident investigation or hazard assessment you led. A final round often includes a site tour or panel with operations leadership who evaluate whether your communication style fits a culture where you must influence behavior without direct authority.
Where can I find and apply to safety engineer jobs?
You can find and apply to safety engineer jobs on Migrate Mate, which lists current openings from across the United States. Find roles that match your experience and specialization, then apply directly to each listing without any extra steps between you and the employer.
See All 864+ Safety Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
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