SecurityScorecard Logo

SecurityScorecard

Machine Learning Engineer

Posted 16 Days Ago
Be an Early Applicant
Remote
Hiring Remotely in Canada
Mid level
Remote
Hiring Remotely in Canada
Mid level
As a Machine Learning Engineer at SecurityScorecard, you will design and optimize ML algorithms, build scalable data pipelines, deploy models, and collaborate with cross-functional teams to enhance cybersecurity resilience. Responsibilities include model development, data pipeline creation, performance monitoring, and documentation.
The summary above was generated by AI

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 Team:

At SecurityScorecard, the Data Science organization builds AI and ML products that empower our customers to manage cybersecurity risk. We leverage massive datasets sourced by our internal Threat Intelligence teams to create the core rating models that our customers use for assessing third-party risk and self-assessment. We also build LLM-powered systems for automating and accelerating cybersecurity risk assessment workflows.

About the Role:

As an ML Engineer, you will design and optimize machine learning algorithms, build scalable data pipelines, and deploy reliable models into production environments. You'll collaborate with cross-functional teams to integrate ML solutions into products, conduct research to stay ahead of emerging technologies, and ensure models perform optimally through ongoing monitoring and refinement. Your work will directly enhance cybersecurity resilience for organizations worldwide, making the world a safer place. If you’re passionate about solving complex problems and creating impactful solutions, this role offers the opportunity to make a significant impact while working in a dynamic, collaborative environment.

Responsibilities:

  • Model Development: Design, train, and optimize machine learning models and algorithms. 
  • Data Pipeline Creation: Build and maintain scalable data pipelines to preprocess, clean, and transform raw data for analysis and model training.
  • Model Deployment: Implement and manage models in production environments, ensuring scalability, reliability, and performance.
  • Research and Experimentation: Stay updated on the latest machine learning techniques, tools, and frameworks to enhance model accuracy and efficiency.
  • Collaboration: Work closely with data scientists, software engineers, and product teams to understand requirements and integrate ML solutions into products.
  • Performance Monitoring: Continuously monitor, evaluate, and fine-tune models post-deployment to maintain accuracy and robustness.
  • Documentation: Create clear and concise documentation for models, processes, and systems to support team collaboration and knowledge sharing.

Required Qualifications:

  • 3+ years of experience or equivalent demonstrable skills in ML Engineering, Data Science or related discipline.
  • Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Physics, or a related field.
  • Strong programming skills in Python.
  • Experience with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn.
  • Proficiency in data manipulation and analysis using tools such as Polars, Pandas, NumPy, or SQL.
  • Solid understanding of algorithms, statistics, and data structures.
  • Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
  • Knowledge of CI/CD pipelines and version control systems (e.g. Git).
  • Familiarity with Linux/Unix command line tools.

Preferred Qualifications:

  • PhD degree in Computer Science, Engineering, Mathematics, Physics or a related field.
  • Hands-on experience with LLMs, RAG, LangChain, or LlamaIndex.
  • Experience with big data technologies such as Hadoop, Spark, or Kafka.

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 total compensation range for this position is $80,000 - $95,000 (USD base plus bonus). 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 [email protected].

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

Top Skills

Python
SQL

Similar Jobs

2 Days Ago
8 Locations
Remote
Hybrid
12,000 Employees
Senior level
12,000 Employees
Senior level
Blockchain • eCommerce • Fintech • Payments • Software • Financial Services • Cryptocurrency
The Staff Machine Learning Engineer will lead the Conversational AI team at Square, focusing on designing and optimizing machine learning solutions across products. Responsibilities include driving ML projects from inception to production, collaborating with various stakeholders, and providing mentorship to team members.
2 Days Ago
4 Locations
Remote
3,000 Employees
Junior
3,000 Employees
Junior
eCommerce • Food • Software
Mid level machine learning engineer role at Instacart. Responsibilities include designing, developing, testing, and deploying machine learning models to solve customer problems and drive business forward. Requires strong programming skills and analytical abilities.
Yesterday
4 Locations
Remote
3,000 Employees
Entry level
3,000 Employees
Entry level
eCommerce • Food • Software
The Machine Learning Engineer II, Economist will design and build machine learning solutions, collaborate with cross-functional teams, and develop impactful solutions for Instacart's growth. Candidates with a background in economics and machine learning are preferred, with a focus on practical applications and empirical research.

What you need to know about the Toronto Tech Scene

Although home to some of the biggest names in tech, including Google, Microsoft and Amazon, Toronto has established itself as one of the largest startup ecosystems in the world. And with over 2,000 startups — more than 30 percent of the country's total startups — Toronto continues to attract new businesses. Be it helping entrepreneurs manage their finances, simplifying business operations by automating payroll or assisting pharmaceutical companies in launching new drugs, the city's tech scene is just getting started.

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account