Applied Machine Learning Engineer

October 28

🤠 Texas – Remote

Although this job is listed in Texas, this company may be open to hiring remote in other states.

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

🦅 H1B Visa Sponsor

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SpyCloud

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Cybersecurity • Security • Enterprise

SpyCloud is a cybersecurity company that specializes in identity protection and threat intelligence. The company provides solutions for enterprise protection, consumer risk protection, and cybercrime investigations. SpyCloud's services include automated account takeover (ATO) prevention, post-infection remediation, ransomware prevention, session hijacking prevention, threat actor attribution, fraud prevention, dark web monitoring, and penetration testing. By integrating with SIEM and SOAR systems, SpyCloud helps organizations reduce their risk of ransomware and other critical attacks by securing digital identities. Their data partnerships enhance their offerings through access to breached, malware, and phished data. SpyCloud is committed to disrupting cybercrimes by leveraging advanced analytics to protect both employee and consumer accounts and unmask threat actors.

51 - 200 employees

🔒 Cybersecurity

🔐 Security

🏢 Enterprise

📋 Description

• Develop, train, and deploy machine learning models using real-world structured and unstructured data to power critical security features such as threat detection and alerting, entity resolution and risk scoring, and natural language-based tagging and classification • Responsible for building scalable preprocessing and feature engineering pipelines to ensure robust model performance in production • Own model monitoring and evaluation, designing feedback loops to continuously improve accuracy and effectiveness • Partner with product managers and domain experts to define machine learning requirements and success criteria • Rapidly prototype MVPs to test new features or signals • Work with data engineering teams to access, clean, and transform diverse data sources • Contribute to broader system design and architectural decisions involving machine learning components • Clearly articulate model design choices, tradeoffs, and outcomes to both technical and non-technical stakeholders • Maintain thorough documentation for models, pipelines, and evaluation methodologies

🎯 Requirements

• 5+ years of experience building and deploying machine learning systems in production • Strong background in applied math (linear algebra, optimization, statistics) and machine learning • Proficiency in Python and key ML libraries: PyTorch, TensorFlow, scikit-learn, XGBoost • Experience building scalable data and ML pipelines (e.g., with Airflow, Spark, Pandas) • Hands-on experience deploying ML models into cloud environments or containerized services • Strong communication skills and the ability to translate complex problems into actionable solutions • Experience with CI/CD, versioning (e.g., MLflow, DVC), and model monitoring in production environments

🏖️ Benefits

• 401(k) with Employer Contribution • Health, Vision, and Dental Insurance • Health Savings Account (HSA) available with Employer Contribution • Employer Paid Life, Short-term, and Long-term Disability Insurance • Generous PTO Plan and 16 paid holidays per year • Retirement Savings Plan with Employer Contribution • Employer Provided Private Health Insurance and Healthcare Cashplan • Employer Paid Life Insurance and Income Replacement • Generous Holiday Plan and 14 paid holidays per year