MLOps

Dream is a pioneering AI cybersecurity company delivering revolutionary defense through artificial intelligence. Our proprietary AI platform creates a unified security system safeguarding assets against existing and emerging generative cyber threats. Dream's advanced AI automates discovery, calculates risks, performs real-time threat detection, and plans an automated response. With a core focus on the "unknowns," our AI transforms data into clear threat narratives and actionable defense strategies.

Dream's AI cybersecurity platform represents a paradigm shift in cyber defense, employing a novel, multi-layered approach across all organizational networks in real-time. At the core of our solution is Dream's proprietary Cyber Language Model, a groundbreaking innovation that provides real-time, contextualized intelligence for comprehensive, actionable insights into any cyber-related query or threat scenario.

We are looking for an experienced MLOps to join our Applications team within our platform engineering group. In this role, you'll be responsible for designing, building, deploying, and maintaining production-grade AI systems and ML pipelines. You'll translate cutting-edge data science research into practical, scalable solutions, handling model deployment both in cloud environments and on-premises using GPUs and CUDA. You’ll optimize and implement ML models, workflows, and AI agents to ensure high performance and reliability in production environments.

Responsibilities:

• Design, implement, and deploy ML models, AI-driven applications, AI workflows, and LLM-based agents into production.
• Build, manage, and maintain robust ML pipelines and systems.
• Deploy models on cloud and on-premises GPU servers.
• Optimize system performance, including model inference, scalability, and resource utilization both on cloud and on-premises.
• Develop and maintain services, APIs and integrate ML models into microservices-based applications.
• Collaborate with cross-functional teams including data science, backend, DevOps, and platform teams.
• Stay up to date with the latest developments in AI, machine learning, and related fields, focusing on LLMs, exploring how emerging technologies can be applied to improve products and services.
  
  

• At least 4-5 years of experience in building ML/AI solutions, specifically in production environment
• Strong experience in building and maintaining scalable machine learning infrastructures
• Strong proficiency in Python
• Solid understanding of Data Science and Machine Learning lifecycle and best practices for model deployment and serving
• Excellent problem-solving abilities, coupled with a creative and strategic mindset
• Extensive experience with ML frameworks
• Understanding of microservice design and architecture
• Proven ability to work effectively in a team setting
  
  

• Familiarity with distributed ML tools
• Experience with real-time machine learning model deployment.
• Familiarity with cybersecurity applications of machine learning
• Advanced skills in performance optimization for high throughput systems