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Senior Machine Learning Engineer

3 hours, 13 minutes ago
Latin America
Full-time
Senior
Machine Learning Engineer
Software Development
Apache Spark AWS Azure Docker GCP Kafka Kubernetes LLM Machine Learning Microservices MLOps NumPy Pandas REST API SQL Terraform
Apply Now
SecurityScorecard

SecurityScorecard

SecurityScorecard is a cybersecurity company that provides a powerful AI-driven platform to identify and eliminate cyber risks across all attack surfaces.

IT Services
251-1K
Founded 2014
$292M raised
View All Jobs 55

Description

  • Design, optimize, and deploy LLM-based models, algorithms, and agents into production environments.
  • Develop and maintain LLM-powered systems and multi-agent architectures for cybersecurity risk assessment workflows.
  • Design conversational AI agents and orchestrate interactions between multiple agents.
  • Build and integrate scalable RESTful APIs and microservices to expose model capabilities for product integration.
  • Support observability, evaluation, and ongoing monitoring of LLM-based agents to maintain accuracy and stability.
  • Build and maintain scalable data pipelines to preprocess, clean, and transform data for analysis and model training.
  • Stay current on emerging agent, LLM, and ML techniques, tools, and frameworks and apply relevant improvements.
  • Collaborate with data scientists, ML engineers, software engineers, and product teams to integrate ML solutions into products.
  • Create clear documentation for models, processes, and systems to support collaboration and knowledge sharing.

Requirements

  • Bachelor’s degree in Computer Science, Engineering, Mathematics, Physics, or a related field.
  • 4+ years of experience or equivalent demonstrable skills in ML Engineering, Data Science, or a related discipline.
  • Experience with cloud platforms such as AWS, Azure, or GCP.
  • Experience with containerization technologies such as Docker and Kubernetes.
  • Proficiency in data manipulation, cleaning, and analysis using Polars, Pandas, NumPy, or SQL.
  • Solid understanding of supervised and unsupervised learning, statistical analysis, hypothesis testing, and predictive modeling.
  • Hands-on experience building multi-agent systems with LLMs and retrieval-augmented generation (RAG) using tools like LangChain.
  • Master’s degree in Computer Science, Engineering, Mathematics, Physics, or a related field (preferred).
  • Experience with big data technologies such as PySpark and Kafka (preferred).
  • Experience implementing MLOps practices, including CI/CD pipelines and infrastructure as code with Terraform (preferred).
  • Experience deploying and maintaining production-grade agentic solutions with monitoring, alerting, observability, reliability, and compliance (preferred).
  • Immigration sponsorship is not provided for this position.

Benefits

  • Estimated total compensation range of $75,000 - $90,000 (base plus bonus).
  • Eligibility for annual performance-based incentive compensation awards.
  • Eligibility for equity.
  • Opportunity to work at a company with a globally recognized cybersecurity mission.
  • Commitment to equal employment opportunity and reasonable accommodations for qualified individuals with disabilities.

Interested in this position?

Apply directly on the company website

Apply Now

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