Trase

DevOps Engineer

• Design, implement, and manage scalable and efficient CI/CD pipelines for our backend, frontend, and machine learning services.
• Own and optimize the Bazel build system, ensuring fast, reliable, and reproducible builds across the organization.
• Collaborate closely with engineering teams to understand their development workflows and improve the overall developer experience related to building and deploying code.
• Manage the infrastructure required for our build and deployment systems, using Infrastructure as Code (IaC) to automate provisioning.
• Implement and enforce security best practices within the CI/CD process to secure our software supply chain.
• Troubleshoot and resolve complex issues in the build and deployment pipeline, providing support to engineering teams.
• Stay up-to-date with the latest developments in CI/CD, build systems, and cloud technologies to drive continuous improvement.

Senior DevOps Engineer

• Design, Build, and Maintain Core Infrastructure: Architect and implement scalable, highly available, and secure infrastructure on cloud platforms (GCP, AWS, Azure) to support our AI-driven applications and services.
• Automate Everything: Develop and maintain automation tools and frameworks to eliminate manual effort in deployment, configuration, and management of our production environment.
• Ensure System Reliability and Performance: Establish and monitor Service Level Objectives (SLOs) and Service Level Indicators (SLIs) for our production systems. Proactively identify and resolve performance bottlenecks and availability issues.
• Manage ML Infrastructure and Pipelines: Collaborate with ML engineers to build and maintain robust CI/CD pipelines for machine learning models, ensuring seamless training, deployment, and monitoring.
• Incident Response and Post-Mortems: Lead incident response efforts to minimize downtime and conduct thorough post-incident reviews to identify root causes and implement preventative measures.
• Implement and Enhance Observability: Deploy and manage comprehensive monitoring, logging, and tracing solutions (e.g., Prometheus, Grafana, ELK stack) to provide deep visibility into system health.
• Capacity Planning and Cost Optimization: Forecast infrastructure needs and optimize resource utilization to ensure our platform can scale efficiently and cost-effectively.
• Foster a Culture of Reliability: Champion SRE best practices across the engineering organization and mentor team members on reliability, performance, and scalability.

Senior Site Reliability Engineer, Security Clearance

AI Research Scientist

• Lead ML Research and Development: Drive the research, development, and optimization of machine learning models, focusing on solving real-world business problems through advanced ML techniques.
• Architect Novel Training and Fine-Tuning Methodologies: Design, implement, and iterate on advanced training protocols, fine-tuning processes, and optimization strategies, particularly for Language Models (LLMs).
• Evaluate Model Performance and Innovation: Develop and refine techniques for assessing and enhancing the effectiveness of ML models, focusing on accuracy, scalability, and adaptability to dynamic enterprise requirements.
• Feedback System Design for Continuous Learning: Create systems that incorporate user and system feedback to iteratively improve model performance over time.
• Cross-Functional Collaboration: Work closely with product teams and domain experts to translate business needs into research questions and actionable ML strategies.
• Stay Current on ML Advancements: Actively monitor the latest research in ML and NLP, integrating cutting-edge practices and methodologies into our development pipeline.
• Mentor and Guide Team Members: Provide technical guidance to junior researchers, fostering a culture of continuous learning, experimentation, and research-driven development.

Senior AI/ML Researcher, Applied Machine Learning

Machine Learning Engineer

• Architect, Build, and Optimize ML Systems: Develop and deploy robust ML models that deliver high-impact results for real-world applications.
• Training Pipeline Development: Design and implement efficient, scalable pipelines to train and retrain ML models, ensuring they meet business needs.
• Fine-Tuning Large Language Models (LLMs): Continuously fine-tune LLMs to align with specific enterprise requirements, enhancing accuracy, relevance, and performance.
• Feedback Systems Design: Implement and refine feedback loops to iteratively improve the effectiveness of ML models over time.
• Cross-Functional Collaboration: Work closely with product and business teams to understand and translate requirements into ML solutions that provide tangible outcomes.
• Stay Current with ML Advancements: Keep up with the latest in ML research and best practices, applying insights to our ML infrastructure to ensure it remains at the cutting edge.
• Mentorship and Knowledge Sharing: Guide and mentor junior team members, fostering a culture of continuous improvement and technical growth.
• Technical Communication: Clearly and effectively communicate ML methodologies, results, and insights to non-technical stakeholders.

Senior AI/ML Engineer, Applied Machine Learning

• About Us: Co-founded in 2023 by Joe Laws and Grant Verstandig, Trase Systems is AI, Uncomplicated. Trase empowers enterprise leaders to harness the full potential of AI without the associated complexity and risks. We are an end-to-end solution for deploying, managing, and optimizing AI in the enterprise. Our platform specializes in bridging the “last mile” of AI adoption, unlocking AI's full potential while driving efficiency and significant cost savings.\\n• Trase is at the forefront of AI Agent innovation, topping the Hugging Face GAIA Leaderboard for Generalized AI Assistants, ahead of industry giants such as Google, Meta, Microsoft, and OpenAI. We are leveraging our cutting-edge technologies to develop mission-critical agentic applications in complex industries such as Healthcare, Oil & Gas, and National Security.\\n• About the Role: Are you passionate about building the systems that empower engineers to build and ship software quickly and reliably? Do you excel at optimizing complex build systems and creating frictionless CI/CD pipelines? If so, we have an exciting opportunity for you as a DevOps Engineer at Trase Systems.\\n• Responsibilities: Design, implement, and manage scalable and efficient CI/CD pipelines for our backend, frontend, and machine learning services.; Own and optimize the Bazel build system, ensuring fast, reliable, and reproducible builds across the organization.; Collaborate closely with engineering teams to understand their development workflows and improve the overall developer experience related to building and deploying code.; Manage the infrastructure required for our build and deployment systems, using Infrastructure as Code (IaC) to automate provisioning.; Implement and enforce security best practices within the CI/CD process to secure our software supply chain.; Troubleshoot and resolve complex issues in the build and deployment pipeline, providing support to engineering teams.; Stay up-to-date with the latest developments in CI/CD, build systems, and cloud technologies to drive continuous improvement.\\n• Requirements: Proven experience in a DevOps or a similar role focused on build and release engineering.; Deep, hands-on experience with the Bazel build system is required.; Extensive experience building and managing CI/CD pipelines using tools like GitLab CI, Jenkins, CircleCI, or similar.; Proficiency in scripting languages such as Python.; Strong experience with containerization technologies like Docker.; Excellent problem-solving skills, with a demonstrated ability to troubleshoot complex build and deployment issues.; Exceptional written and verbal communication skills, with the ability to effectively collaborate with team members and stakeholders.; A Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.\\n• Benefits: 100% employer-paid, comprehensive health care including medical, dental, and vision for you and your family. Paid maternity and paternity for 14 weeks at employees' normal pay. Unlimited PTO, with management approval. Opportunities for professional development and continued learning with educational reimbursements. Optional 401K, FSA, and equity incentives available. Mental health benefits through TARA Mind.\\n• Salary Range: $170,000-$220,000. This represents the typical salary range for this position based on experience, skills, and other factors.\\n• We’re an Equal Opportunity Employer: You’ll receive consideration for employment without regard to race, sex, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability.

• Design, Build, and Maintain Core Infrastructure: Architect and implement scalable, highly available, and secure infrastructure on cloud platforms (GCP, AWS, Azure) to support our AI-driven applications and services.\n• Automate Everything: Develop and maintain automation tools and frameworks to eliminate manual effort in deployment, configuration, and management of our production environment.\n• Ensure System Reliability and Performance: Establish and monitor Service Level Objectives (SLOs) and Service Level Indicators (SLIs) for our production systems. Proactively identify and resolve performance bottlenecks and availability issues.\n• Manage ML Infrastructure and Pipelines: Collaborate with ML engineers to build and maintain robust CI/CD pipelines for machine learning models, ensuring seamless training, deployment, and monitoring.\n• Incident Response and Post-Mortems: Lead incident response efforts to minimize downtime and conduct thorough post-incident reviews to identify root causes and implement preventative measures.\n• Implement and Enhance Observability: Deploy and manage comprehensive monitoring, logging, and tracing solutions (e.g., Prometheus, Grafana, ELK stack) to provide deep visibility into system health.\n• Capacity Planning and Cost Optimization: Forecast infrastructure needs and optimize resource utilization to ensure our platform can scale efficiently and cost-effectively.\n• Foster a Culture of Reliability: Champion SRE best practices across the engineering organization and mentor team members on reliability, performance, and scalability.