Machine Learning Engineer

Summary

Join SecurityScorecard as an ML Engineer and design, optimize, and deploy machine learning algorithms to enhance cybersecurity resilience globally. You will build scalable data pipelines, collaborate with cross-functional teams, and conduct research on emerging technologies. This role requires experience in ML engineering, data science, or a related field, proficiency in Python and various ML frameworks, and a strong understanding of algorithms and data structures. SecurityScorecard offers a competitive salary, stock options, health benefits, unlimited PTO, parental leave, and tuition reimbursements.

Requirements

• 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

Responsibilities

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

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

• Competitive salary
• Stock options
• Health benefits
• Unlimited PTO
• Parental leave
• Tuition reimbursements
• Annual performance-based incentive compensation awards
• Equity