Material Security Logo

Material Security

Staff Machine Learning Engineer

Reposted 21 Days Ago
Remote
Hiring Remotely in USA
225K-255K Annually
Senior level
Remote
Hiring Remotely in USA
225K-255K Annually
Senior level
As a Machine Learning Engineer, you'll design, build, and maintain models to detect security threats, ensuring model efficiency and aligning initiatives with business goals.
The summary above was generated by AI

As a Machine Learning Engineer at Material Security, you'll be part of a team of experienced, world-class engineers, working to protect our users and their privacy (e.g., inboxes from breaches, targeted phishing, fraud, and lateral account takeover). Your mission is to build, deploy, and maintain high quality models that detect security relevant data and behavior (phishing emails, sensitive data in email and drives).

Responsibilities
  • Design, build, train, and deploy machine learning models to detect sensitive data and malicious threats (phishing emails).

  • Write production-level code to convert your ML models into working pipelines and participate in code reviews to ensure code quality and distribute knowledge.

  • Architect scalable, reliable, and maintainable machine learning pipelines, integrating seamlessly with existing backend systems.

  • Explore recent advancements in generative AI and LLMs as potential additions to our detection capabilities.

  • Work closely with machine learning engineers, product managers, designers, data scientists, and software engineers to align machine learning initiatives with business goals.

  • Stay ahead of the curve by exploring new algorithms, technologies, and frameworks to enhance our detection models.

  • Contribute to great engineering culture through active participation and mentorship.

What We’re Looking For

Must Haves

  • B.S., M.S. or Ph.D. in Computer Science or related technical field or relevant work experience.

  • 8+ years (or Ph.D. with 6+ years) of experience in machine learning, data science, or related fields, with at least 3 years in a senior or staff engineering role.

  • Deep understanding of supervised/unsupervised learning techniques and LLMs

  • Strong experience writing efficient and effective data pipelines.

  • Practical knowledge of how to build efficient end-to-end ML workflows and a strong drive to won the entire process of model development from conception through deployment, to maintenance..

  • Experience with machine learning libraries (e.g., scikit, Pandas)

Nice to have

  • Experience in API development on top of a fast API

  • Experience tracking text embedding modeling

  • Strong knowledge of cloud platforms (e.g., AWS, GCP) and containerization tools (e.g., Docker, Kubernetes).

---

Material Security is a remote-first workplace with an office in San Francisco, California.


By clicking "Apply for this Job", you acknowledge that you have read the California Candidate Privacy Notice Regarding Use of Personal Information and hereby agree to its terms.

Compensation at Material Security is determined by a range of factors, including but not limited to the individual’s particular combination of knowledge, skills, competencies, and experience. The projected compensation range for this position is $225,000-255,000.

 

Equal Opportunity Employer Statement

Material Security is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, creed, national origin, ancestry, sex, gender, gender identity or expression, sexual orientation, age, marital status, veteran status, disability, genetic information, or any other legally protected status. All employment decisions are based on qualifications, merit, and business needs.

Similar Jobs

12 Days Ago
Remote or Hybrid
206K-230K Annually
Senior level
206K-230K Annually
Senior level
eCommerce • Mobile • Payments
Lead design, development, and deployment of production-grade, large-scale ML systems. Influence ML strategy, integrate models with platform and data infrastructure, mentor engineers, communicate results to stakeholders, and mature ML infrastructure and abstractions across teams.
Top Skills: AWSDatabricksKafkaPythonSagemakerScikit-LearnSparkSpark MlTensorFlow
13 Days Ago
In-Office or Remote
CA, USA
200K-415K Annually
Expert/Leader
200K-415K Annually
Expert/Leader
Blockchain • eCommerce • Fintech • Payments • Software • Financial Services • Cryptocurrency
Lead development and production of underwriting and credit decisioning models across Cash App Borrow and Afterpay. Own full modeling lifecycle: problem formulation, feature engineering, training, calibration, experimentation, deployment, monitoring, and iteration. Build decision frameworks, agentic engineering workflows, and collaborate with cross-functional partners to align model behavior with business and regulatory goals.
Top Skills: AirflowAWSClaude CodeCopilotCursorFeature StoreGCPGitLightgbmMlflowModel Hosting PlatformNumpyPandasPrefectPythonPyTorchScikit-LearnSnowflakeSQLXgboost
14 Days Ago
Remote or Hybrid
CA, USA
200K-415K Annually
Expert/Leader
200K-415K Annually
Expert/Leader
Blockchain • Fintech • Mobile • Payments • Software • Financial Services
Senior individual contributor building and maintaining underwriting and credit decisioning ML systems for Cash App Borrow and Afterpay. Responsibilities include feature engineering, model training, calibration, experimentation, deployment, monitoring, and portfolio-level analysis. Collaborate with cross-functional teams to align models with business and regulatory goals and develop AI-native engineering workflows and governance for reliable, auditable model development.
Top Skills: AirflowAWSClaude CodeCopilotCursorGCPGitInternal Feature StoreLightgbmMlflowModel Hosting PlatformNumpyPandasPrefectPythonPyTorchScikit-LearnSnowflakeSQLXgboost

What you need to know about the NYC Tech Scene

As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.

Key Facts About NYC Tech

  • Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
  • Key Industries: Artificial intelligence, Fintech
  • Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
  • Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account