Interested in this AI/ML Engineer role at CrowdStrike?
Apply Now →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 proud to work for a mission-driven company leveraging AI to transform the way we work. CrowdStrikers drive their careers through flexibility and autonomy while also being expected to contribute to a culture of responsible AI adoption, experimentation, and innovation. We use an AI-first mindset as a force multiplier to proactively and continuously accelerate execution, build expertise, uncover insights, and solve complex problems. 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 Role:
CrowdStrike Falcon Host is a two-component security product. One component is a “sensor”: a driver installed on client machines that observes system activity and recognizes malicious behavior, then provides on-box prevention capability and remote telemetry to the Falcon Host cloud. The sensor processes thousands of events per second to provide deep visibility into operations on the endpoint, and performs rich correlation and computation to identify malicious events and blocks malicious activity.
The cloud component aggregates sensor telemetry for each customer’s network, correlates malicious behavior across multiple machines, and presents our customers’ operations teams with a prioritized summary of the threats detected in their environments.
This is a Sr. Engineering Manager role in the CTIO team. In this role you will build and lead a team that brings multiple AI-based strategies together into a cohesive, integrated capability on our next-generation sensor platform across Windows, macOS and Linux. You will own the roadmap for AI on the endpoint, from operationalizing machine learning models and building the data pipelines that feed them to delivering efficient on-device inference, and you will partner closely with data science, cloud and sensor platform teams to turn research into shipped product. As a Sr Engineering Manager, you will be expected to have ownership over all major components and development projects as well as hiring, training and growing your team. You will be required to assist with architecting solutions and support in implementing our core features. Features will cross-cut most core OS subsystems such as file system, memory and process, and networking. Many features are also built in a way that they will have shared components across multiple platforms. You need to be able to lead projects efficiently while maximizing performance and minimizing costs, making sure high standards are being followed when it comes to design, coding quality, and unit and component testing.
The CTIO team at CrowdStrike is responsible for defining and executing the company's technology vision and strategy, driving innovation and overseeing the development and evolution of the Falcon platform. The CTIO ensures CrowdStrike maintains its position as a technology leader by fostering engineering excellence, aligning technical capabilities with business objectives, and anticipating emerging threats and market trends.
What You'll Do:
- Collaborate with all the sensor development teams, across the company, on architecture and strategic initiatives.
- Conceptualize and develop new product features.
- Provide guidance and support to development teams in designing and implementing software for cross-platform delivery (Windows, macOS, Linux).
- Take ownership of features throughout the entire lifecycle, from initial design to final delivery, including presenting product demonstrations at the conclusion of each sprint.
- Engage in cross-functional collaboration with teams situated in various locations.
What You'll Need:
- General knowledge and understanding of C++ and Windows/macOS/Linux Operating System internals
- Hands-on experience operationalizing machine learning models on the endpoint, including building the data pipelines that collect, transform and deliver sensor telemetry for model training, evaluation and on-device inference.
- Experience working with teams to ship major features and releases.
- Previous experience as either a Sr. Manager or Engineering Manager with direct reports
- Ability to lead, mentor, communicate, collaborate, and work effectively in a distributed team
Bonus Points:
- Strong background in scalable, light-weight and highly performing systems
- OS system expertise for core concepts and subsystems
- Familiarity and experience with Agile process
- Knowledge and expertise in the Security landscape
#LI-DR1
Benefits of Working at CrowdStrike:
- Market 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.
If you need assistance accessing or reviewing the information on this website or need help submitting an application for employment or requesting an accommodation, please contact us at [email protected] for further assistance.
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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 $160,000 - $250,000 per year, with eligibility for bonuses, equity grants and a comprehensive benefits package that includes health insurance, 401k and paid time off. For detailed information about the U.S. benefits package, please click here.
CrowdStrike Canada ULC is committed to equal pay for equal work in its compensation practices. The base salary range for this position in Canada is $175,000 - $250,000 CAD per year + variable/incentive compensation + equity + benefits. A candidate’s salary is determined by various factors including, but not limited to, relevant work experience, skills, certifications and location. This is Canadian-based employment, and it is expected that all employees maintain legal entitlement to work in Canada. Applicants selected to move forward in the hiring process are subject to background checks, including but not limited to criminal record, credit, and/or reference checks.
Salary Context
This $160K-$250K range is above the median for AI/ML Engineer roles in our dataset (median: $178K across 1623 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 9,079 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At CrowdStrike, 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 in Demand for This Role
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 $211,950 based on 13,048 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $229,300. Disclosed range: $160K to $250K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
CrowdStrike AI Hiring
CrowdStrike has 6 open AI roles right now. They're hiring across AI/ML Engineer, AI Agent Developer, AI Architect, MLOps Engineer. Positions span Sunnyvale, CA, US, Remote, US, New York, NY. Compensation range: $250K - $375K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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