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About This Role
As a global leader in cybersecurity, CrowdStrike protects the people, processes and technologies that drive modern organizations. Since 2011, our mission hasn't changed — we're here to stop breaches, and we've redefined modern security with the world's most advanced AI\-native platform. We work on large scale distributed systems, processing almost 3 trillion events per day and this traffic is growing daily. Our customers span all industries, and they count on CrowdStrike to keep their businesses running, their communities safe and their lives moving forward. We're also a mission\-driven company. We cultivate a culture that gives every CrowdStriker both the flexibility and autonomy to own their careers. We're always looking to add talented CrowdStrikers to the team who have limitless passion, a relentless focus on innovation and a fanatical commitment to our customers, our community and each other. Ready to join a mission that matters? The future of cybersecurity starts with you.About the RoleCrowdStrike is looking for AI engineers who have strong experience in building AI applications and agents on various cloud platforms. The candidate should have a deep understanding of various LLM concepts like RAG, AI Workflows, Agentic AI, AI Agents, AI Agent Frameworks, MCP, A2A is required. The candidate should have expert level knowledge of a few of the various frameworks like TensorFlow, PyTorch, Autogen, LlamaIndex, LangChain, AWS Agent Core, AI Agent Studio, MS Copilot Studio, etc.The candidate should be able to understand the requirements, research possible solutions, prototype and implement production quality scalable, performant and code for the requirement along with necessary unity and functional tests required for productionizing the code.PLEASE NOTE: This role is hybrid, requiring 2\-3 days per week on\-site at one of the posted locations.Success MeansArchitecting and delivering scalable implementations for various features.Ability to research and compare/contrast various solutions for a given problem.Gather feedback and iterate towards a final solution while addressing the feedback.Ability to provide detailed design and architecture documents for the feature.The ability to present the problem and describe the solution in easy to understand ways for a larger audience is critical.Ability to present and explain the feature in the context of the product to the customers as needed.Deep understanding of 2 of cloud infrastructure and services \- AWS, GCP, Azure or OCI.Expert level knowledge of Go and/or Python.Moderate to expert level knowledge of K8s.What You'll DoUnderstand the requirements.Design and present the solution, gather feedback and iterate towards an acceptable solution.Implement prototypes and high quality scalable, performant, testable production level code.Build and maintain dashboards necessary to monitor and report on the production metrics of the feature (efficacy and performance).Iterate and improve the solution as necessary wrt features, efficacy, scale and performance.What You'll Need6\+ years of combined experience as a cloud app developer.4\+ years of experience in implementing Generative AI Apps and features.Building Apps on Azure Cloud Platform, MS CoPilot, AI Agents.Bonus PointsPrevious experience in security companies and working in close coordination with or in security products.Deep understanding of Security landscape, especially AI Security (securing the use and application of AI).Benefits of Working at CrowdStrikeMarket leader in compensation and equity awards.Comprehensive physical and mental wellness programs.Competitive vacation and holidays for recharge.Paid parental and adoption leaves.Professional development opportunities for all employees regardless of level or role.Employee Networks, geographic neighborhood groups, and volunteer opportunities to build connections.Vibrant office culture with world class amenities.Great Place to Work Certified across the globe.CrowdStrike is proud to be an equal opportunity employer. We are committed to fostering a culture of belonging where everyone is valued for who they are and empowered to succeed. We support veterans and individuals with disabilities through our affirmative action program.CrowdStrike is committed to providing equal employment opportunity for all employees and applicants for employment. The Company does not discriminate in employment opportunities or practices on the basis of race, color, creed, ethnicity, religion, sex (including pregnancy or pregnancy\-related medical conditions), sexual orientation, gender identity, marital or family status, veteran status, age, national origin, ancestry, physical disability (including HIV and AIDS), mental disability, medical condition, genetic information, membership or activity in a local human rights commission, status with regard to public assistance, or any other characteristic protected by law. We base all employment decisions—including recruitment, selection, training, compensation, benefits, discipline, promotions, transfers, lay‑offs, return from lay‑off, terminations and social/recreational programs—on valid job requirements.CrowdStrike participates in the E‑Verify program.Right to Work. CrowdStrike, Inc. is committed to fair and equitable compensation practices. Placement within the pay range is dependent on a variety of factors including, but not limited to, relevant work experience, skills, certifications, job level, supervisory status, and location. The base salary range for this position for all U.S. candidates is $140,000 \- $215,000 per year, with eligibility for bonuses, equity grants and a comprehensive benefits package that includes health insurance, 401k and paid time off.\#J\-18808\-Ljbffr
As a global leader in cybersecurity, CrowdStrike protects the people, processes and technologies that drive modern organizations. Since 2011, our mission hasn't changed — we're here to stop breaches, and we've redefined modern security with the world's most advanced AI\-native platform. We work on large scale distributed systems, processing almost 3 trillion events per day and this traffic is growing daily. Our customers span all industries, and they count on CrowdStrike to keep their businesses running, their communities safe and their lives moving forward. We're also a mission\-driven company. We cultivate a culture that gives every CrowdStriker both the flexibility and autonomy to own their careers. We're always looking to add talented CrowdStrikers to the team who have limitless passion, a relentless focus on innovation and a fanatical commitment to our customers, our community and each other. Ready to join a mission that matters? The future of cybersecurity starts with you.About the RoleCrowdStrike is looking for AI engineers who have strong experience in building AI applications and agents on various cloud platforms. The candidate should have a deep understanding of various LLM concepts like RAG, AI Workflows, Agentic AI, AI Agents, AI Agent Frameworks, MCP, A2A is required. The candidate should have expert level knowledge of a few of the various frameworks like TensorFlow, PyTorch, Autogen, LlamaIndex, LangChain, AWS Agent Core, AI Agent Studio, MS Copilot Studio, etc.The candidate should be able to understand the requirements, research possible solutions, prototype and implement production quality scalable, performant and code for the requirement along with necessary unity and functional tests required for productionizing the code.PLEASE NOTE: This role is hybrid, requiring 2\-3 days per week on\-site at one of the posted locations.Success MeansArchitecting and delivering scalable implementations for various features.Ability to research and compare/contrast various solutions for a given problem.Gather feedback and iterate towards a final solution while addressing the feedback.Ability to provide detailed design and architecture documents for the feature.The ability to present the problem and describe the solution in easy to understand ways for a larger audience is critical.Ability to present and explain the feature in the context of the product to the customers as needed.Deep understanding of 2 of cloud infrastructure and services \- AWS, GCP, Azure or OCI.Expert level knowledge of Go and/or Python.Moderate to expert level knowledge of K8s.What You'll DoUnderstand the requirements.Design and present the solution, gather feedback and iterate towards an acceptable solution.Implement prototypes and high quality scalable, performant, testable production level code.Build and maintain dashboards necessary to monitor and report on the production metrics of the feature (efficacy and performance).Iterate and improve the solution as necessary wrt features, efficacy, scale and performance.What You'll Need6\+ years of combined experience as a cloud app developer.4\+ years of experience in implementing Generative AI Apps and features.Building Apps on Azure Cloud Platform, MS CoPilot, AI Agents.Bonus PointsPrevious experience in security companies and working in close coordination with or in security products.Deep understanding of Security landscape, especially AI Security (securing the use and application of AI).Benefits of Working at CrowdStrikeMarket leader in compensation and equity awards.Comprehensive physical and mental wellness programs.Competitive vacation and holidays for recharge.Paid parental and adoption leaves.Professional development opportunities for all employees regardless of level or role.Employee Networks, geographic neighborhood groups, and volunteer opportunities to build connections.Vibrant office culture with world class amenities.Great Place to Work Certified across the globe.CrowdStrike is proud to be an equal opportunity employer. We are committed to fostering a culture of belonging where everyone is valued for who they are and empowered to succeed. We support veterans and individuals with disabilities through our affirmative action program.CrowdStrike is committed to providing equal employment opportunity for all employees and applicants for employment. The Company does not discriminate in employment opportunities or practices on the basis of race, color, creed, ethnicity, religion, sex (including pregnancy or pregnancy\-related medical conditions), sexual orientation, gender identity, marital or family status, veteran status, age, national origin, ancestry, physical disability (including HIV and AIDS), mental disability, medical condition, genetic information, membership or activity in a local human rights commission, status with regard to public assistance, or any other characteristic protected by law. We base all employment decisions—including recruitment, selection, training, compensation, benefits, discipline, promotions, transfers, lay‑offs, return from lay‑off, terminations and social/recreational programs—on valid job requirements.CrowdStrike participates in the E‑Verify program.Right to Work. CrowdStrike, Inc. is committed to fair and equitable compensation practices. Placement within the pay range is dependent on a variety of factors including, but not limited to, relevant work experience, skills, certifications, job level, supervisory status, and location. The base salary range for this position for all U.S. candidates is $140,000 \- $215,000 per year, with eligibility for bonuses, equity grants and a comprehensive benefits package that includes health insurance, 401k and paid time off.\#J\-18808\-Ljbffr
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- Sr. Engineer, AI \- AI Detection and Response (AIDR) (Hybrid)
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- Dormont Manufacturing Company
- Sunnyvale, California 94087 United States View Map
- Posted: Jul 11, 2026
- Location: Sunnyvale,California
- Full Time
- Public Safety
Salary Context
This $140K-$215K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Dormont Manufacturing, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $218,750 based on 3,817 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($177K) sits 19% below the category median. Disclosed range: $140K to $215K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Dormont Manufacturing AI Hiring
Dormont Manufacturing has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Sunnyvale, CA, US. Compensation range: $215K - $215K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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