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Abnormal
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  • Remote Machine Learning Engineer II  

    Abnormal
    - Arapahoe County
    Apply Now
    About The Role Abnormal AI is looking for a Machine Learning Engineer... Read More
    About The Role Abnormal AI is looking for a Machine Learning Engineer to join the Message Detection - Attack Detection 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… Abnormal. 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 25% of the Fortune 500 ( and ever growing ). In a landscape where a single successful attack can lead to financial losses of millions of dollars, the Attack Detection team plays the central role of building an extremely high recall Detection Engine that can operate on hundreds of millions of messages at milliseconds latency. The Attack Detection team’s mission statement is to provide world-class detector efficacy to tackle changing attack landscape using a combination of generalizable and auto trained models as well as specific detectors for high value attack categories. 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 precise 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). These signals are then combined and utilized to train highly accurate model based as well as heuristic detectors. Additionally, to continuously adapt to new unseen attacks, the team builds out different stages in our automated model retraining pipelines including data analytics and generation stages, modeling stages, production evaluation stages as well as automated deployment stages. This role would also have an opportunity to have a significant impact on the overall charter, direction and roadmap of the team. The Machine Learning Engineer would be involved in understanding the domain of false negatives i.e. the current and future attacks which can cause significant customer workflow disruption. They would help define the technical roadmap required to address the most pressing customer problems and simultaneously operate our detection decisioning system at an extremely high recall. What You Will Do Design and implement systems that combine rules, models, feature engineering, and business and product inputs into an email detection product, with senior engineer guidance. Understand features that distinguish safe emails from email attacks, and how our model stack enables us to catch them. Identify and recommend new features groups or ML model approaches that can significantly improve detection efficacy for a product. Work with infrastructure Read Less
    Apply Now

  • Remote Machine Learning Engineer II  

    Abnormal
    - Anchorage Municipality
    Apply Now
    About The Role Abnormal AI is looking for a Machine Learning Engineer... Read More
    About The Role Abnormal AI is looking for a Machine Learning Engineer to join the Message Detection - Attack Detection 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… Abnormal. 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 25% of the Fortune 500 ( and ever growing ). In a landscape where a single successful attack can lead to financial losses of millions of dollars, the Attack Detection team plays the central role of building an extremely high recall Detection Engine that can operate on hundreds of millions of messages at milliseconds latency. The Attack Detection team’s mission statement is to provide world-class detector efficacy to tackle changing attack landscape using a combination of generalizable and auto trained models as well as specific detectors for high value attack categories. 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 precise 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). These signals are then combined and utilized to train highly accurate model based as well as heuristic detectors. Additionally, to continuously adapt to new unseen attacks, the team builds out different stages in our automated model retraining pipelines including data analytics and generation stages, modeling stages, production evaluation stages as well as automated deployment stages. This role would also have an opportunity to have a significant impact on the overall charter, direction and roadmap of the team. The Machine Learning Engineer would be involved in understanding the domain of false negatives i.e. the current and future attacks which can cause significant customer workflow disruption. They would help define the technical roadmap required to address the most pressing customer problems and simultaneously operate our detection decisioning system at an extremely high recall. What You Will Do Design and implement systems that combine rules, models, feature engineering, and business and product inputs into an email detection product, with senior engineer guidance. Understand features that distinguish safe emails from email attacks, and how our model stack enables us to catch them. Identify and recommend new features groups or ML model approaches that can significantly improve detection efficacy for a product. Work with infrastructure Read Less
    Apply Now

  • Remote Senior Customer Success Manager, Canada  

    Abnormal
    - Washoe County
    Apply Now
    About the Role As a Senior Customer Success Manager, you will independ... Read More
    About the Role As a Senior Customer Success Manager, you will independently manage strategic customer relationships and ensure long-term value realization across a portfolio of mid-market and enterprise accounts. You will lead success planning, drive adoption and engagement, and mitigate risk while collaborating cross-functionally with Product, Engineering, Sales, and Support. Your work will have a direct impact on retention, satisfaction, and account growth, and you’ll contribute insights to help evolve customer and internal processes. Who you are Confident operating independently, navigating strategic accounts, and aligning customer needs with organizational goals Comfortable managing technical and strategic issues, leveraging internal partnerships to drive outcomes Effective communicator with the ability to present complex ideas clearly across a range of audiences Adaptable and proactive in dynamic, fast-paced environments with a continuous improvement mindset What you will do Manage strategic customer relationships post-sale, focusing on adoption, retention, and value delivery with minimal oversight Deliver outcome-oriented QBRs/EBRs and lead success planning to align customer goals with platform capabilities Drive platform adoption and feature engagement through best practices, enablement, and education on roadmap developments Monitor account health using data-driven insights; proactively identify risks and lead coordinated mitigation efforts Resolve complex escalations with timely, clear communication and a focus on long-term customer trust and satisfaction Collaborate with Sales, Engineering, and Support to influence renewal and expansion outcomes Represent the customer voice internally, providing structured feedback to Product and other teams Support knowledge sharing and contribute to internal process development or mentoring where relevant Must Haves 8+ years of experience in enterprise SaaS, with at least 3 years in Customer Success, TAM, or support roles Proven track record managing complex customer relationships, including executive-level stakeholders Strong communication, analytical, and problem-solving skills with an emphasis on delivering measurable outcomes Technical familiarity with internet and networking technologies; experience with security products is a plus Proficiency in CRM and support tools such as Salesforce and Jira Bachelor’s degree in a technical field (e.g., Computer Science, Engineering) or equivalent professional experience #LI-EM3 Read Less
    Apply Now

  • Remote Machine Learning Engineer II  

    Abnormal
    - Pima County
    Apply Now
    About The Role Abnormal AI is looking for a Machine Learning Engineer... Read More
    About The Role Abnormal AI is looking for a Machine Learning Engineer to join the Message Detection - Attack Detection 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… Abnormal. 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 25% of the Fortune 500 ( and ever growing ). In a landscape where a single successful attack can lead to financial losses of millions of dollars, the Attack Detection team plays the central role of building an extremely high recall Detection Engine that can operate on hundreds of millions of messages at milliseconds latency. The Attack Detection team’s mission statement is to provide world-class detector efficacy to tackle changing attack landscape using a combination of generalizable and auto trained models as well as specific detectors for high value attack categories. 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 precise 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). These signals are then combined and utilized to train highly accurate model based as well as heuristic detectors. Additionally, to continuously adapt to new unseen attacks, the team builds out different stages in our automated model retraining pipelines including data analytics and generation stages, modeling stages, production evaluation stages as well as automated deployment stages. This role would also have an opportunity to have a significant impact on the overall charter, direction and roadmap of the team. The Machine Learning Engineer would be involved in understanding the domain of false negatives i.e. the current and future attacks which can cause significant customer workflow disruption. They would help define the technical roadmap required to address the most pressing customer problems and simultaneously operate our detection decisioning system at an extremely high recall. What You Will Do Design and implement systems that combine rules, models, feature engineering, and business and product inputs into an email detection product, with senior engineer guidance. Understand features that distinguish safe emails from email attacks, and how our model stack enables us to catch them. Identify and recommend new features groups or ML model approaches that can significantly improve detection efficacy for a product. Work with infrastructure Read Less
    Apply Now

  • Remote Machine Learning Engineer II  

    Abnormal
    - Hamilton County
    Apply Now
    About The Role Abnormal AI is looking for a Machine Learning Engineer... Read More
    About The Role Abnormal AI is looking for a Machine Learning Engineer to join the Message Detection - Attack Detection 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… Abnormal. 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 25% of the Fortune 500 ( and ever growing ). In a landscape where a single successful attack can lead to financial losses of millions of dollars, the Attack Detection team plays the central role of building an extremely high recall Detection Engine that can operate on hundreds of millions of messages at milliseconds latency. The Attack Detection team’s mission statement is to provide world-class detector efficacy to tackle changing attack landscape using a combination of generalizable and auto trained models as well as specific detectors for high value attack categories. 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 precise 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). These signals are then combined and utilized to train highly accurate model based as well as heuristic detectors. Additionally, to continuously adapt to new unseen attacks, the team builds out different stages in our automated model retraining pipelines including data analytics and generation stages, modeling stages, production evaluation stages as well as automated deployment stages. This role would also have an opportunity to have a significant impact on the overall charter, direction and roadmap of the team. The Machine Learning Engineer would be involved in understanding the domain of false negatives i.e. the current and future attacks which can cause significant customer workflow disruption. They would help define the technical roadmap required to address the most pressing customer problems and simultaneously operate our detection decisioning system at an extremely high recall. What You Will Do Design and implement systems that combine rules, models, feature engineering, and business and product inputs into an email detection product, with senior engineer guidance. Understand features that distinguish safe emails from email attacks, and how our model stack enables us to catch them. Identify and recommend new features groups or ML model approaches that can significantly improve detection efficacy for a product. Work with infrastructure Read Less
    Apply Now

  • Remote Senior Customer Success Manager, Canada  

    Abnormal
    - Essex County
    Apply Now
    About the Role As a Senior Customer Success Manager, you will independ... Read More
    About the Role As a Senior Customer Success Manager, you will independently manage strategic customer relationships and ensure long-term value realization across a portfolio of mid-market and enterprise accounts. You will lead success planning, drive adoption and engagement, and mitigate risk while collaborating cross-functionally with Product, Engineering, Sales, and Support. Your work will have a direct impact on retention, satisfaction, and account growth, and you’ll contribute insights to help evolve customer and internal processes. Who you are Confident operating independently, navigating strategic accounts, and aligning customer needs with organizational goals Comfortable managing technical and strategic issues, leveraging internal partnerships to drive outcomes Effective communicator with the ability to present complex ideas clearly across a range of audiences Adaptable and proactive in dynamic, fast-paced environments with a continuous improvement mindset What you will do Manage strategic customer relationships post-sale, focusing on adoption, retention, and value delivery with minimal oversight Deliver outcome-oriented QBRs/EBRs and lead success planning to align customer goals with platform capabilities Drive platform adoption and feature engagement through best practices, enablement, and education on roadmap developments Monitor account health using data-driven insights; proactively identify risks and lead coordinated mitigation efforts Resolve complex escalations with timely, clear communication and a focus on long-term customer trust and satisfaction Collaborate with Sales, Engineering, and Support to influence renewal and expansion outcomes Represent the customer voice internally, providing structured feedback to Product and other teams Support knowledge sharing and contribute to internal process development or mentoring where relevant Must Haves 8+ years of experience in enterprise SaaS, with at least 3 years in Customer Success, TAM, or support roles Proven track record managing complex customer relationships, including executive-level stakeholders Strong communication, analytical, and problem-solving skills with an emphasis on delivering measurable outcomes Technical familiarity with internet and networking technologies; experience with security products is a plus Proficiency in CRM and support tools such as Salesforce and Jira Bachelor’s degree in a technical field (e.g., Computer Science, Engineering) or equivalent professional experience #LI-EM3 Read Less
    Apply Now

  • Remote Machine Learning Engineer II  

    Abnormal
    - El Paso County
    Apply Now
    About The Role Abnormal AI is looking for a Machine Learning Engineer... Read More
    About The Role Abnormal AI is looking for a Machine Learning Engineer to join the Message Detection - Attack Detection 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… Abnormal. 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 25% of the Fortune 500 ( and ever growing ). In a landscape where a single successful attack can lead to financial losses of millions of dollars, the Attack Detection team plays the central role of building an extremely high recall Detection Engine that can operate on hundreds of millions of messages at milliseconds latency. The Attack Detection team’s mission statement is to provide world-class detector efficacy to tackle changing attack landscape using a combination of generalizable and auto trained models as well as specific detectors for high value attack categories. 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 precise 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). These signals are then combined and utilized to train highly accurate model based as well as heuristic detectors. Additionally, to continuously adapt to new unseen attacks, the team builds out different stages in our automated model retraining pipelines including data analytics and generation stages, modeling stages, production evaluation stages as well as automated deployment stages. This role would also have an opportunity to have a significant impact on the overall charter, direction and roadmap of the team. The Machine Learning Engineer would be involved in understanding the domain of false negatives i.e. the current and future attacks which can cause significant customer workflow disruption. They would help define the technical roadmap required to address the most pressing customer problems and simultaneously operate our detection decisioning system at an extremely high recall. What You Will Do Design and implement systems that combine rules, models, feature engineering, and business and product inputs into an email detection product, with senior engineer guidance. Understand features that distinguish safe emails from email attacks, and how our model stack enables us to catch them. Identify and recommend new features groups or ML model approaches that can significantly improve detection efficacy for a product. Work with infrastructure Read Less
    Apply Now

  • Remote Senior Customer Success Manager, Canada  

    Abnormal
    - Ramsey County
    Apply Now
    About the Role As a Senior Customer Success Manager, you will independ... Read More
    About the Role As a Senior Customer Success Manager, you will independently manage strategic customer relationships and ensure long-term value realization across a portfolio of mid-market and enterprise accounts. You will lead success planning, drive adoption and engagement, and mitigate risk while collaborating cross-functionally with Product, Engineering, Sales, and Support. Your work will have a direct impact on retention, satisfaction, and account growth, and you’ll contribute insights to help evolve customer and internal processes. Who you are Confident operating independently, navigating strategic accounts, and aligning customer needs with organizational goals Comfortable managing technical and strategic issues, leveraging internal partnerships to drive outcomes Effective communicator with the ability to present complex ideas clearly across a range of audiences Adaptable and proactive in dynamic, fast-paced environments with a continuous improvement mindset What you will do Manage strategic customer relationships post-sale, focusing on adoption, retention, and value delivery with minimal oversight Deliver outcome-oriented QBRs/EBRs and lead success planning to align customer goals with platform capabilities Drive platform adoption and feature engagement through best practices, enablement, and education on roadmap developments Monitor account health using data-driven insights; proactively identify risks and lead coordinated mitigation efforts Resolve complex escalations with timely, clear communication and a focus on long-term customer trust and satisfaction Collaborate with Sales, Engineering, and Support to influence renewal and expansion outcomes Represent the customer voice internally, providing structured feedback to Product and other teams Support knowledge sharing and contribute to internal process development or mentoring where relevant Must Haves 8+ years of experience in enterprise SaaS, with at least 3 years in Customer Success, TAM, or support roles Proven track record managing complex customer relationships, including executive-level stakeholders Strong communication, analytical, and problem-solving skills with an emphasis on delivering measurable outcomes Technical familiarity with internet and networking technologies; experience with security products is a plus Proficiency in CRM and support tools such as Salesforce and Jira Bachelor’s degree in a technical field (e.g., Computer Science, Engineering) or equivalent professional experience #LI-EM3 Read Less
    Apply Now

  • Remote Machine Learning Engineer II  

    Abnormal
    - Clark County
    Apply Now
    About The Role Abnormal AI is looking for a Machine Learning Engineer... Read More
    About The Role Abnormal AI is looking for a Machine Learning Engineer to join the Message Detection - Attack Detection 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… Abnormal. 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 25% of the Fortune 500 ( and ever growing ). In a landscape where a single successful attack can lead to financial losses of millions of dollars, the Attack Detection team plays the central role of building an extremely high recall Detection Engine that can operate on hundreds of millions of messages at milliseconds latency. The Attack Detection team’s mission statement is to provide world-class detector efficacy to tackle changing attack landscape using a combination of generalizable and auto trained models as well as specific detectors for high value attack categories. 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 precise 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). These signals are then combined and utilized to train highly accurate model based as well as heuristic detectors. Additionally, to continuously adapt to new unseen attacks, the team builds out different stages in our automated model retraining pipelines including data analytics and generation stages, modeling stages, production evaluation stages as well as automated deployment stages. This role would also have an opportunity to have a significant impact on the overall charter, direction and roadmap of the team. The Machine Learning Engineer would be involved in understanding the domain of false negatives i.e. the current and future attacks which can cause significant customer workflow disruption. They would help define the technical roadmap required to address the most pressing customer problems and simultaneously operate our detection decisioning system at an extremely high recall. What You Will Do Design and implement systems that combine rules, models, feature engineering, and business and product inputs into an email detection product, with senior engineer guidance. Understand features that distinguish safe emails from email attacks, and how our model stack enables us to catch them. Identify and recommend new features groups or ML model approaches that can significantly improve detection efficacy for a product. Work with infrastructure Read Less
    Apply Now

  • Remote Machine Learning Engineer II  

    Abnormal
    - Tarrant County
    Apply Now
    About The Role Abnormal AI is looking for a Machine Learning Engineer... Read More
    About The Role Abnormal AI is looking for a Machine Learning Engineer to join the Message Detection - Attack Detection 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… Abnormal. 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 25% of the Fortune 500 ( and ever growing ). In a landscape where a single successful attack can lead to financial losses of millions of dollars, the Attack Detection team plays the central role of building an extremely high recall Detection Engine that can operate on hundreds of millions of messages at milliseconds latency. The Attack Detection team’s mission statement is to provide world-class detector efficacy to tackle changing attack landscape using a combination of generalizable and auto trained models as well as specific detectors for high value attack categories. 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 precise 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). These signals are then combined and utilized to train highly accurate model based as well as heuristic detectors. Additionally, to continuously adapt to new unseen attacks, the team builds out different stages in our automated model retraining pipelines including data analytics and generation stages, modeling stages, production evaluation stages as well as automated deployment stages. This role would also have an opportunity to have a significant impact on the overall charter, direction and roadmap of the team. The Machine Learning Engineer would be involved in understanding the domain of false negatives i.e. the current and future attacks which can cause significant customer workflow disruption. They would help define the technical roadmap required to address the most pressing customer problems and simultaneously operate our detection decisioning system at an extremely high recall. What You Will Do Design and implement systems that combine rules, models, feature engineering, and business and product inputs into an email detection product, with senior engineer guidance. Understand features that distinguish safe emails from email attacks, and how our model stack enables us to catch them. Identify and recommend new features groups or ML model approaches that can significantly improve detection efficacy for a product. Work with infrastructure Read Less
    Apply Now
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