About SecurityScorecard:

SecurityScorecard is the global leader in cybersecurity ratings, with over 12 million companies continuously rated, operating in 64 countries. Founded in 2013 by security and risk experts Dr. Alex Yampolskiy and Sam Kassoumeh and funded by world-class investors, SecurityScorecard’s patented rating technology is used by over 25,000 organizations for self-monitoring, third-party risk management, board reporting, and cyber insurance underwriting; making all organizations more resilient by allowing them to easily find and fix cybersecurity risks across their digital footprint. 

Headquartered in New York City, our culture has been recognized by Inc Magazine as a "Best Workplace,” by Crain’s NY as a "Best Places to Work in NYC," and as one of the 10 hottest SaaS startups in New York for two years in a row. Most recently, SecurityScorecard was named to Fast Company’s annual list of the World’s Most Innovative Companies for 2023 and to the Achievers 50 Most Engaged Workplaces in 2023 award recognizing “forward-thinking employers for their unwavering commitment to employee engagement.”  SecurityScorecard is proud to be funded by world-class investors including Silver Lake Waterman, Moody’s, Sequoia Capital, GV and Riverwood Capital.

About the Role:

As a Staff Machine Learning Engineer at SecurityScorecard, you'll play a pivotal role in the development and deployment of cutting-edge machine learning solutions as a member of our Data Science team. In this role, you will collaborate with a cross functional team of machine learning engineers, data engineers, MLOps engineers and data science researchers. You will be responsible for leading high-impact projects, providing technical expertise, and influencing a distributed team of engineers. Your responsibilities will encompass crafting and overseeing critical infrastructure components such as microservices, feature stores, data mesh, and our AI platform. Your expertise will drive the automation for training, deployment, and continuous updates of our machine learning models. If you're a problem solver, effective communicator, and enthusiastic about driving advancements in AI and ML in the security space, we want you on our team.

Responsibilities:

• Build, architect, and maintain AI platform to empower and accelerate AI research and delivery of ML model REST APIs while maintaining cost efficiency.
• Write high quality code with unit tests as well as data tests and perform code reviews.
• Build and maintain robust, scalable, and low latency ML Model REST APIs.
• Build high quality data cleansing and aggregation processes with associated testing and  monitoring to prevent corrupt data from flowing in our ML models.
• Become an expert in all security data sources and associated lineage and other nuances within the data to collaborate with research scientists.
• Create well-formed schemas and SQL migration processes as required for RDBMS (Postgres), KVS (ScyllaDB), streaming (Kafka) and vector data stores.
• Build, automate, and maintain batch and streaming data pipelines with cleansing, normalization, regularization and enrichment processes to automate the preparation of data for AI models, from diverse raw inputs to aggregated feature stores.
• Manage project priorities, deadlines, and deliverables while providing technical leadership on impactful projects.
• Influence and coach a distributed team of engineers, ensuring alignment and clarity on goals and timelines.
• Stay up-to-date and apply emerging AI/ML technologies and methodologies.
  

Required Qualifications:

• You have a bachelors or greater (Master’s or PhD preferred) in computer science, STEM or related field.
• 5+ years of software development experience with expertise in data structures, algorithms, design, and architecture.
• 3+ years of hands-on experience with machine learning algorithms, tools such as PyTorch, HuggingFace, AI, deep learning, and NLU / LLMs.
• Proficient in building and scaling highly available consumer-facing applications.
• Knowledge of architecting and scaling systems based on various data stores (RDBMs, KVS, in-memory data stores, etc.).
• Strong understanding of distributed computing, big data technologies (Hadoop, Spark), and ML infrastructure design.
• Skilled in software application development with modern languages (Python, Scala, Java, etc.), and best practices, standards and conventions.
• Experience with Git version control, CI/CD pipelines, and Agile project management.
• Proficiency in creating Docker containers, shell scripts, and familiarity with data orchestration tools (e.g., Airflow, Dagster, Dolt, and Great Expectations).
• Familiarity with serialization/deserialization formats for real-time and batch data processing (e.g., Parquet, Protobuf, Avro).
• Autonomous work style with strong communication and interpersonal skills.
• Strong technical estimating skills and analytical abilities.
• Detail-oriented and capable of managing  multiple assignments/projects simultaneously.
• Ownership mentality, adaptability to change, and a customer-focused approach.
• Strong written and verbal communication skills.
  

Preferred Qualifications:

• Expertise in creating streaming data-mesh infrastructure using Kafka.
• Skilled in designing enterprise real-time event-driven data lake architecture on distributed file systems like Hadoop, AWS, GCP, etc.
• Experience developing efficient, scalable, and reliable batch data lake ETL processes using Spark.
• Skilled with tools such as Ray, Airflow, Argo, MLFlow, and vector databases.
• Experience in the security industry.
  

Benefits:

Specific to each country, we offer a competitive salary, stock options, Health benefits, and unlimited PTO, parental leave, tuition reimbursements, and much more!

The estimated salary range for this position is $X - X. Actual compensation for the position is based on a variety of factors, including, but not limited to affordability, skills, qualifications and experience, and may vary from the range. In addition to base salary, employees may also be eligible for annual performance-based incentive compensation awards and equity, among other company benefits. 

SecurityScorecard is committed to Equal Employment Opportunity and embraces diversity. We believe that our team is strengthened through hiring and retaining employees with diverse backgrounds, skill sets, ideas, and perspectives. We make hiring decisions based on merit and do not discriminate based on race, color, religion, national origin, sex or gender (including pregnancy) gender identity or expression (including transgender status), sexual orientation, age, marital, veteran, disability status or any other protected category in accordance with applicable law. 

We also consider qualified applicants regardless of criminal histories, in accordance with applicable law. We are committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need assistance or accommodation due to a disability, please contact talentacquisitionoperations@securityscorecard.io.

Any information you submit to SecurityScorecard as part of your application will be processed in accordance with the Company’s privacy policy and applicable law. 

SecurityScorecard does not accept unsolicited resumes from employment agencies.  Please note that we do not provide immigration sponsorship for this position.

#LI-DNI