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Abnormal Security Interview Questions

Abnormal Security Interview Guides

<p>You are testing hundreds of hypotheses with many <em>t</em>-tests. What considerations should be made?</p>


<p>What is a key disadvantage of the F-test when compared to multiple t-tests?</p>

What is a key disadvantage of the F-test when compared to multiple t-tests?

Hundreds of Hypotheses

You are testing hundreds of hypotheses with many t-tests. What considerations should be made?

<p>Let’s say that your company is running a standard control and variant AB test on a feature to increase conversion rates on the landing page. The PM checks the results and finds a .04 p-value.</p>

<p>How would you assess the validity of the result?</p>


Experiment Validity

<p>Suppose there exists a new airline named Jetco that flies domestically across North America. Jetco recently had a study commissioned that tested the boarding time of every airline, and it came out that Jetco had the fastest average boarding times of any airline.</p>

<p>What factors could have biased this result, and what would you look into?</p>


<p>What could potentially bias the average boarding time in favor of an airline that only flies domestically?</p>

What could potentially bias the average boarding time in favor of an airline that only flies domestically?

Boarding Times Bias

A new airline came out as the fastest average boarding times compared to other airlines.  What factors could have biased this result and what would you look into?

Abnormal Security Salaries by Position

<h3>Job Description</h3><div>Job Description<div>About The Role<p>Abnormal Security is looking for a Software Engineer II who is a solid software developer with a strong interest in Security & Privacy to join the Platform Security team. The Platform Security team owns the Security and Privacy platform services and infrastructure to uphold industry standards for the company's security posture and customer data protection. This role will design, develop, and release Secure Service to Service communication frameworks and toolings, Customer Data Security & Privacy workflows, and then integrate them with Security Operational analytics and auditing services to monitor, protect, and secure Abnormal infrastructure. The ideal candidate will have:</p><ul><li>Security mindset - ability to identify potential security flaws in any step of the software development lifecycle.</li><li>Ability to translate Security & Privacy requirements into technical requirements and drive end to end execution of the projects.</li><li>Opportunity to facilitate and drive cross team collaboration with product engineering teams to adopt security best practices and secure-by-design platform services and components.</li><li>Opportunity to grow into Senior Software Engineer on the team and deliver bigger scope, higher impact, and additional leadership responsibilities.</li></ul>What You Will Do <ul><li>Own, lead, and deliver the Platform Security features, services, and components for Abnormal microservices such as Zero-Trust networking, Secure Service to Service communications, Customer Data Security & Privacy, Secret Management, etc…</li><li>Design and develop secure and scalable customer integration frameworks and toolings to integrate Abnormal ecosystem with external applications such as Salesforce, Slack, Github, Zoom, etc… to enable Secure by design Multi Product Platform.</li><li>Integrate Platform and Infrastructure components with Security Operational analytics and auditing tooling such as Okta, Dazz, Splunk, SIEM.</li><li>Utilize prior industry experience to contribute and deliver the Platform Security team and the Platform & Infrastructure division roadmap.</li><li>Reconcile Platform and Security requirements to build a secure platform while enabling global engineering teams to deliver high quality software at high velocity.</li><li>Contribute to vendor review and selection for related software purchases in key problem areas such as VPN solution, Just In Time access, and other Security monitoring tools.</li></ul>Must Have<ul><li>BS degree in Computer Science, Electrical Engineering, Computer Engineering or other related engineering field.</li><li>2+ years of experience as a Software Engineer.</li><li>Strong Computer Science and programming fundamentals.</li><li>Experience with system design and cloud infrastructure.</li><li>Experience with Golang and Python programming languages.</li><li>Proven track record of leading feature development and delivering high quality software.</li></ul>Nice To Have <ul><li>Knowledge of Authentication & Authorization and Network Security problem space, best practices, and related technologies.</li><li>Understanding of distributed computing, CAP theorem, and system design tradeoffs.</li><li>Ability to differentiate must-have versus nice-to-have Security and Privacy requirements.</li></ul><p>#LI-RT1</p><div><div><hr /><p><br />At Abnormal Security certain roles are eligible for a bonus, restricted stock units (RSUs), and benefits. Individual compensation packages are based on factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons. We know that benefits are also an important piece of your total compensation package. Learn more about our Compensation and Equity Philosophy on our Benefits & Perks page.</p></div><div>Base salary range:</div><div>$147,200—$173,200 USD</div></div></div></div>

<h3>Job Description</h3><div>Job Description<div>About The Role<p>Abnormal Security is looking for a Senior Machine Learning Engineer to join the Message Detection Decisioning team. At Abnormal, we protect our customers against nefarious adversaries who are constantly evolving their techniques and tactics to outwit and undermine the traditional approaches to Security. That's what makes our novel behavioral-based approach so…<em>Abnormal. </em>Abnormal has constantly been named as one of the top cybersecurity startups and our behavioral AI system has helped us win various cybersecurity accolades resulting in being trusted to protect more than 8% of the Fortune 1000 ( and ever growing ).</p><p>In a landscape where a single successful attack can lead to financial losses of millions of dollars, the Message Detection Decisioning team plays the central role of building an extremely precise Detection Engine that can operate on hundreds of millions of messages at milliseconds latency. Every email ingested by Abnormal flows through the workflow owned by the Detection Decisioning team which applies hundreds of signals and detectors on a message based on the message and user context. The system then computes the final overall decision for the system and consequently chronicles attribution to drive various offline and online metrics such as offline precision, online precision, online False Negative Rate etc.</p><p>This team is solving a multi-layered detection problem, which involves modeling communication patterns to establish enterprise-wide baselines, incorporating these patterns as robust signals, and combining these signals with contextual information to create extremely high precision systems. The team builds discriminative signals at various levels including message level (eg. presence of particular phrases), sender-level (eg.frequency of sender) and recipient level (eg.likelihood of receiving a safe message) which forms the foundation to create highly accurate heuristic and model based detectors. Additionally to maintain an overall high precise detection system, the team innovates on software systems and processes which can be quickly adapted to solve trends seen in the short term as well as generalize well in the longer term.</p><p>This role would also have an opportunity to have a huge impact on the overall charter, direction and growth of the team. The Senior Machine Learning Engineer would be involved in understanding the most pressing customer problems in the domain of false positives and build out the associated technical roadmap to continuously operate our detection decisioning system at an extremely high precision.</p>What You Will Do <ul><li>Design and implement systems that combine rules, models, feature engineering, and business and product inputs into an email detection product.</li><li>Identify and recommend new features groups or ML model approaches that can significantly improve detection efficacy for a product. Work with infrastructure & systems engineers to productionize signals to feed into the detection system.</li><li>Understand features that distinguish safe emails from email attacks, and how our detector stack enables us to catch them. </li><li>Be the expert in main detection pipelines and decision data flow to be able to drive debugging in systematic degradations caused by bad detectors.</li><li>Writes code with testability, readability, edge cases, and errors in mind.</li><li>Train models on well-defined datasets to improve model efficacy on specialized attacks</li><li>Actively monitor and improve False Positive rates and efficacy rates for our message detection product attack categories, through feature engineering, rules and ML modeling.</li><li>Analyze False Negative and False Posi datasets to categorize capability gaps and recommend short term feature and rule ideas to improve our detection efficacy.</li><li>Contribute in other areas of the stack: building and debugging data pipelines, or presenting results back to customers in our tools when the occasion arises</li><li>Lead the team's medium and long term roadmap and drive planning and execution strategy for the pod.</li><li>Coach and mentor junior engineers to uplevel their code quality and ML effectiveness by providing quality code reviews and design reviews.</li><li>Participate in building a world-class detection engine across all layers - data quality, feature engineering, model development, experimentation and operation.</li></ul>Must Have <ul><li>Track record of success in translating business requirements into scalable, maintainable systems with a bias toward simpler but iterative systems.</li><li>4+ Experience with production ML systems - understands the pillars of a modern ML stack and the development, maintenance and tuning processes of ML models.</li><li>Uses a systematic approach to debug both data and system issues within ML / heuristics models.</li><li>Fluent with Python and machine learning libraries like numpy and scikit-learn.</li><li>Experience with data analytics and wielding SQL+pandas+spark framework to both build data and metric generation pipelines, and answer critical questions about system efficacy or counterfactual treatments. </li><li>Independently responsible for the entire lifecycle of projects or features including eng design, development, and deployment.</li><li>Works well with other stakeholders - has worked with cross-functional teams to drive projects over the finish-line.</li><li>Machine learning academic background (Bachelor's degree in Computer Science or related fields).</li></ul>Nice to Have <ul><li>MS degree in Computer Science, Electrical Engineering or other related engineering field</li><li>Experience with big data or statistics</li><li>Familiarity with cyber security industry</li></ul><strong>This Position Is Not</strong><ul><li>A role focused on optimizing existing machine learning models </li><li>A research-oriented role that's two-steps removed from the product or customer</li><li>A statistics/data science meets ML role</li></ul><p>#LI-RT1</p><div><div><hr /><p><br />At Abnormal Security certain roles are eligible for a bonus, restricted stock units (RSUs), and benefits. Individual compensation packages are based on factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons. We know that benefits are also an important piece of your total compensation package. Learn more about our Compensation and Equity Philosophy on our Benefits & Perks page.</p></div><div>Base salary range:</div><div>$184,100—$216,600 USD</div></div></div></div>

<h3>Job Description</h3><div>Job Description<div>About the Role<p>Abnormal Security is looking for a Senior ML Infra Engineer to join the Detection Team. The Detection Division is focused on building the world's most advanced technology for identifying and stopping email and cloud-based attacks that were previously undetectable and help make the world a safer place. As an ML Infra Engineer focused on building systems for Detection's Signal Platform, you will be responsible for making feature development at Abnormal a fast, responsive, stable, and confident experience for Machine Learning Engineers.</p><p>The ideal candidate would have the following qualities:</p><ul><li>A first principles approach to building scalable, customer-centric solutions</li><li>A drive to solve meaningful & pragmatic problems for real-world people</li><li>An ownership and impact oriented outlook on your efforts and growth</li><li>An ability to iterate in real-time-solving novel problems, quickly and autonomously</li></ul><p>An ability to iterate in real-time - solving novel problems, quickly and autonomously.</p>What you will do<ul><li>Architect, design, build, and deploy backend services and infrastructure that support a world-class Detection Engine</li><li>Ownership projects that enable us to meet ambitious goals for, such as building the plan to scale components of Detection's Scoring Pipeline by 10x </li><li>Collaborate closely with MLE teams, by distilling feedback, correlating it to our strategy, and executing</li><li>Coach and mentor junior engineers via 1on1s, pair programming, high quality code reviews and design reviews</li></ul>Must Haves<ul><li>5+ years of professional experience as a hands-on engineer building data-oriented products </li><li>Experience with real-time, online, and/or high-throughput & low-latency distributed systems</li><li>Works well with other stakeholders - has worked with cross-functional teams to drive projects over the finish-line.</li><li>High standards - sets high standards and expectations for project execution for themselves and for collaborators</li></ul>Nice to Haves<ul><li>Knowledge of ML systems/products and/or distributed system technologies (Kafka, Redis, Docker, Kubernetes, feature platform serving systems, ML training and ML serving platforms, etc.)</li><li>Experience working with high-throughput online systems in Python and/or Go</li><li>MS degree in Computer Science, Electrical Engineering or other related engineering field</li><li>Familiarity with cyber security industry</li></ul><p></p><p>#LI-RT1</p><div><div><hr /><p><br />At Abnormal Security certain roles are eligible for a bonus, restricted stock units (RSUs), and benefits. Individual compensation packages are based on factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons. We know that benefits are also an important piece of your total compensation package. Learn more about our Compensation and Equity Philosophy on our Benefits & Perks page.</p></div><div>Base salary range:</div><div>$175,800—$206,000 USD</div></div></div></div>

<h3>Job Description</h3><div>Job Description<div><strong>About the Job</strong><p>As the Senior Data Analyst for the R&D Engine Team at our company, you will play a critical role in defining, implementing, and monitoring metrics that drive the performance and effectiveness of our Product Divisions and Standing Teams. Your expertise in data analysis and metrics management will ensure that our teams are aligned with our strategic goals and are consistently delivering high-quality results. You will be responsible for the end-to-end metrics program, from defining stable and effective metrics to conducting regular inspections to ensure adherence and quality.</p><strong>Key Responsibilities</strong><ul><li>Metrics Program Management: Develop and oversee the metrics program for Divisions and Standing Teams, ensuring that metrics are defined, implemented, and monitored effectively.</li><li>Metrics Definition Process: Lead the process of defining metrics for teams, ensuring that they are stable, effective, and aligned with our strategic objectives.</li><li>Metrics Inspection Process: Conduct regular inspections of metrics at all levels (Standing Team, Product Division, R&D) to ensure consistency, accuracy, and effectiveness.</li><li>Data Analysis and Reporting: Analyze data and provide insights to support decision-making and continuous improvement within R&D teams.</li><li>Stakeholder Collaboration: Work closely with R&D leadership, Product Division heads, and Standing Team leads to ensure that metrics are understood, adopted, and utilized effectively.</li><li>Process Improvement: Continuously evaluate and improve the metrics definition and inspection processes to enhance their relevance and impact.</li><li>Training and Support: Provide training and support to teams in understanding and utilizing metrics effectively.</li></ul><p><strong>Key Metric for the Role:</strong></p><ul><li>Percentage of Standing Teams using a consistent metrics process.</li><li>Hygiene of the metrics and the process adopted at the team level.</li></ul><strong>Qualifications</strong><ul><li>Proven experience as a Data Analyst, preferably in a technology or R&D-focused environment.</li><li>Strong understanding of metrics development, data analysis, and reporting.</li><li>Excellent analytical and problem-solving skills.</li><li>Experience with data visualization tools and techniques.</li><li>Strong communication and collaboration skills, with the ability to engage effectively with diverse teams.</li><li>Ability to manage multiple priorities and projects in a fast-paced environment.</li></ul><strong>What We Offer</strong><ul><li>A critical role in shaping the performance measurement and continuous improvement of our R&D operations.</li><li>The opportunity to work in a dynamic and innovative environment.</li><li>A collaborative and supportive team culture.</li><li>Competitive compensation and benefits package.</li><li>Career development and growth opportunities.</li></ul><p></p><p>#LI-ML1</p><div><div><hr /><p><br />At Abnormal Security certain roles are eligible for a bonus, restricted stock units (RSUs), and benefits. Individual compensation packages are based on factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons. We know that benefits are also an important piece of your total compensation package. Learn more about our Compensation and Equity Philosophy on our Benefits & Perks page.</p></div><div>Base salary range:</div><div>$143,000—$168,300 USD</div></div></div></div>

<h3>Job Description</h3><div>Job Description<div>About the Role<p>Abnormal Security is a leading cyber security organization committed to maintaining the highest standards of cybersecurity. As a Cyber Defense Engineering Manager with AWS expertise, you will lead a team of security professionals responsible for protecting our organization's digital assets and cloud infrastructure. You'll play a crucial role in developing and implementing robust cybersecurity strategies, overseeing incident response, and ensuring compliance with industry standards and regulations, with a particular focus on AWS environments. This position requires a blend of technical expertise in cloud security, leadership skills, and strategic thinking to stay ahead of evolving cyber threats in cloud-based infrastructures.</p>What you will do<ul><li>Lead and mentor a team of cyber defense engineers, fostering their growth and development</li><li>Develop and maintain the organization's cybersecurity policies, procedures, and best practices for AWS cloud environments</li><li>Oversee the design, implementation, and maintenance of security systems and controls in AWS</li><li>Conduct regular risk assessments and vulnerability analyses to identify potential security gaps in cloud infrastructures</li><li>Manage incident response processes and lead investigations into security breaches, including those in AWS environments</li><li>Collaborate with other departments to ensure security measures are integrated across the organization's cloud systems</li><li>Review Infrastructure as Code (IAC) pull requests to implement security controls.</li><li>Stay informed about emerging threats and technologies in cloud security, adapting strategies accordingly</li><li>Prepare and present reports to senior management on security status and initiatives, including AWS-specific metrics and insights</li><li>Manage budgets and resources for the cyber defense team, including AWS security tools and services</li><li>Ensure compliance with relevant industry standards and regulations (e.g., NIST, ISO 27001, GDPR, FedRAMP) in cloud environments</li></ul>Must Haves<ul><li>Bachelor's Degree in Information Security, Computer Science, Digital Forensics, Cyber Security, or equivalent years of professional experience to meet job requirements and expectations</li><li>7+ years of experience in cybersecurity, with at least 3 years in a leadership role</li><li>Strong knowledge of network security, encryption, access control, and security protocols</li><li>In-Depth knowledge of EDR, CDR, and SIEM technologies.</li><li>Strong understanding of cloud security, particularly in AWS environments</li><li>Familiarity with Kuberenetes environments and associated security controls</li><li>Demonstrated ability to mentor and train security engineers</li><li>Excellent communications skills and the ability to collaborate across teams</li><li>Knowledge of Infrastructure as Code (IaC) and security automation in AWS (e.g., AWS CloudFormation, AWS CDK, Terraform)</li><li>Familiarity with DevSecOps practices and tools, especially in AWS CI/CD pipelines</li><li>Knowledge of containerization security (e.g., Docker, Kubernetes) in AWS ECS or EKS</li><li>Proficiency in GitHub and its pull request process, including code review practices and security considerations</li></ul>Nice to Haves<ul><li>Master's degree in Cybersecurity or a related field</li><li>Relevant security certifications such as CISSP, CISM, GIAC, GCIH or equivalent</li><li>Proficiency in programming languages such as Python, GoLang, or Java for security automations and code reviews</li><li>Experience with penetration testing and ethical hacking techniques in cloud environment</li><li>Public speaking or presentation skills for security awareness training</li><li>Knowledge of digital forensics and malware analysis in cloud contexts</li></ul><p>#LI-MA1</p><div><div><hr /><p><br />At Abnormal Security certain roles are eligible for a bonus, restricted stock units (RSUs), and benefits. Individual compensation packages are based on factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons. We know that benefits are also an important piece of your total compensation package. Learn more about our Compensation and Equity Philosophy on our Benefits & Perks page.</p></div><div>Base salary range:</div><div>$163,800—$192,200 USD</div></div></div></div>

<h3>Job Description</h3><div>Job Description<div>About The Role<p>Enterprises of all sizes trust Abnormal Security's cloud products to stop cybercrime. These products are data intensive SaaS applications that depend on reliable, scalable, and secure access to data. This is where our Data Platform team fits in, offering scalable storage systems (Postgresql, OpenSearch, Redis, Kafka, RocksDB), as well as providing a reliable platform (Databricks, Spark, AWS/Azure) for moving and processing data that feeds the company's powerful ML models to detect and prevent cyberattacks. </p><p>Abnormal Security is looking for a Staff Software Engineer to spearhead the key initiatives owned by the Data Platform team. The individual in this role will have the opportunity to mentor a small team of high-caliber engineers, define and build the roadmap to unlock the next generation data platform, and execute on ambitious and challenging technical projects to deliver value.</p>About You<ul><li>Capable of tackling complex and ambiguous business problems, exploring solutions spaces and building consensus, decomposing them into execution plans, and contributing actively.</li><li>Have a track record of building data intensive applications that directly or implicitly contribute to the company's business goals.</li><li>Can effectively earn trust and credibility from a diverse set of Engineering, Product, and Design team members.</li></ul>What You Will Do <ul><li>Shape the Data Platform architecture and roadmap of Abnormal Security to empower and scale the growing list of AI / ML applications across the company.</li><li>Deep dive into the product workflows and recommend correct trade offs for the transition.</li><li>Act as the technical lead of the team. Own their quarterly roadmap, to set, execute and deliver.</li></ul>Must Have <ul><li>5+ years experience in building platforms, tools, and systems to serve the needs of engineering teams, empower them to ship with velocity and reliability.</li><li>Experience in building data intensive, distributed systems that are complex and high scale as a back-end engineer. This is not a Data Engineering role. </li><li>Proven track record of being a Change Agent, defining and driving engineering initiatives that involve cross-team collaboration.</li><li>Experience with or interested in Abnormal Security Tech Stack: Python, Golang, Terraform / Terragrunt, Postgresql, Kafka, Redis, OpenSearch, AWS/Azure, Kubernetes.</li></ul>Nice to Have <ul><li>Experience in operating complex AI / ML applications at scale.</li><li>Knowledge and/or experience building out platform offerings to support other engineering teams. </li></ul><p>#LI-RT1</p><div><div><hr /><p><br />At Abnormal Security certain roles are eligible for a bonus, restricted stock units (RSUs), and benefits. Individual compensation packages are based on factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons. We know that benefits are also an important piece of your total compensation package. Learn more about our Compensation and Equity Philosophy on our Benefits & Perks page.</p></div><div>Base salary range:</div><div>$209,800—$246,800 USD</div></div></div></div>

<h3>Job Description</h3><div>Job Description<div><p>Enterprises of all sizes trust Abnormal Security's cloud products to stop cybercrime. These products are data intensive SaaS applications that depend on reliable, scalable, and secure access to data. This is where our Data Platform team fits in, enabling efficient, reliable and scalable data processing across both realtime and offline processing systems. Come empower the rest of engineering to stop cybercrime as we expand our offerings across both clouds and regions. </p><p><strong>The Data Platform team is looking to add a Senior Software Engineer. </strong>The individual in this role will have the opportunity to partner closely with our existing world class team of engineers as we define and build the next generation data platform. </p><p><strong>There are a lot of opportunities for growth and career advancement – it's up to you to own your career here. Some potential career paths for this role include: </strong></p><ul><li>Solving zero-to-one or one-to-million problems</li><li>Growing into a Staff technical leadership role</li></ul>What you will do <ul><li>Scale and optimize our use of online datastores in critical services.</li><li>Work cross functionally with R&D teams to identify scalability gaps in their data intensive systems, build and execute on plans to mitigate them.</li><li>Define and deliver our data platform offerings across AWS, Azure to empower and delight our internal engineering customers. </li></ul><ul><li>Optimize the performance of offline data processing systems (we use Spark / Databricks) to increase efficiency and cut costs.</li></ul>Must Have<ul><li>5+ years of experience working on data-intensive applications and distributed systems.</li><li>Strong programming skills in Python, Golang, or similar languages.</li><li>Depth in at least one key area of the Data Platform tech stack - Relational DBs, key value and/or document datastores, caches, Kafka, Spark (or other batch processing systems)</li><li>Excellent ability and strong desire to onboard and mentor other engineers.</li><li>Experience in working with AWS (or a similar public commercial cloud such as Azure / GCP).</li></ul>Nice to Have<ul><li>Prior experience in up-leveling the use of Airflow (or similar data orchestration systems) in a tech startup to support their growth and scale.</li></ul><p></p><p>#LI-MA1</p><div><div><hr /><p><br />At Abnormal Security certain roles are eligible for a bonus, restricted stock units (RSUs), and benefits. Individual compensation packages are based on factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons. We know that benefits are also an important piece of your total compensation package. Learn more about our Compensation and Equity Philosophy on our Benefits & Perks page.</p></div><div>Base salary range:</div><div>$175,800—$206,000 USD</div></div></div></div>

<h3>Job Description</h3><div>Job Description<div>About The Role<p>Abnormal Security is looking for a Software Engineer to join the Detection Team, working on projects that advance our Message Processing, Model Inference systems, and ML Infrastructure to 5x Scale. </p><p>The Detection Division is focused on building the world's most advanced technology for identifying and stopping email and cloud-based attacks that were previously undetectable and helping make the world a safer place. As an Engineer focused on building the Platform for our Email Detection Engine, you'll leverage your experience with high scale, distributed systems to build resilient solutions that solve critical problems such as:</p><ul><li>Providing low latency live scoring for emails at 50k+ QPS</li><li>Evolving our ML inference systems to power computationally intensive LLMs and other complex models</li><li>Ensuring that we have highly available signals, generated and served within tight SLA</li></ul><p>The ideal candidate has the following qualities: </p><ul><li>A first principles approach to building scalable, customer-centric solutions</li><li>A drive to solve meaningful & pragmatic problems for real-world people</li><li>An ownership and impact oriented outlook on your efforts and growth</li><li>An ability to iterate in real-time-solving novel problems, quickly and autonomously</li></ul>What You Will Do <ul><li>Architect, design, build, and deploy backend services and infrastructure that support a world-class Detection Engine</li><li>Ownership of projects that enable us to meet ambitious goals for, such as building the plan to scale components of Detection's ML Platform, such as our Behavioral Aggregate Systems, by 10x </li><li>Collaborate closely with MLE teams, by distilling feedback, correlating it to our strategy, and executing</li><li>Enhance your engineering expertise and develop new skills by collaborating with world-class engineers</li></ul>Must Have<ul><li>2-5 years of professional experience as a hands-on engineer building data-oriented products</li><li>Experience with real-time, online, and/or high-throughput & low-latency distributed systems</li><li>Works well with other stakeholders - has worked with cross-functional teams to drive projects over the finish-line</li><li>High standards - sets high standards and expectations for project execution for themselves and for collaborators</li></ul>Nice To Have <ul><li>MS degree in Computer Science, Electrical Engineering or other related engineering field</li><li>Experience building ML systems/products</li><li>Knowledge of key ML Ops team technologies (Spark, Data platform and Data coordination, Hadoop, Hive, feature platform serving systems, ML training and ML serving platforms, etc.)</li><li>Experience with big data or statistics </li><li>Experience in ML development</li><li>Familiarity with cyber security industry</li></ul><p></p><p>#LI-RT1</p><div><div><hr /><p><br />At Abnormal Security certain roles are eligible for a bonus, restricted stock units (RSUs), and benefits. Individual compensation packages are based on factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons. We know that benefits are also an important piece of your total compensation package. Learn more about our Compensation and Equity Philosophy on our Benefits & Perks page.</p></div><div>Base salary range:</div><div>$147,200—$173,200 USD</div></div></div></div>

Abnormal Security Interview Questions

Abnormal Security Interview Guides

Abnormal Security Interview Questions

Abnormal Security Salaries by Position

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