As a Senior MLOps Engineer, you will play a crucial role in enabling applied AI. Your main focus will be on the design, build, and maintenance of secure, scalable and efficient ML Platform, with a platform as a product mindset, that automates the end-to-end life-cycle for traditional ML models and LLM models, as part of the Cloud platforms engineering (CPE) directorate. CPE’s mission is to enable our Engineering teams to ship value faster, securely, efficiently and reliably.
In this role, you will:
1. Design and implement robust MLOps and LLMOps pipelines to automate and optimize machine learning model training, testing, deployment, and scaling.
2. Collaborate with data scientists and software engineers to ensure operational criteria are met before deployment.
3. Maintain and enhance continuous integration (CI) and continuous deployment (CD) environments for machine learning systems.
4. Develop tools to improve visibility into the system's operation and to facilitate rapid troubleshooting and debugging.
5. Foster a culture of continuous improvement by incorporating feedback and lessons learned into future ML deployments.
6. Lead initiatives to increase the resilience and scalability of ML systems.
What you need:
7. Bachelor’s degree in computer science, Engineering, Statistics, or a related field.
8. Experience in software development or data engineering, with at least 3 years focused on MLOps or similar roles.
9. Proven track record in designing and deploying scalable machine learning systems in production.
10. Strong programming skills in Python and experience with ML frameworks and tools (e.g., TensorFlow, PyTorch, MLFlow, MetaFlow, vLLM, Kubeflow, Jupyter notebook, Azure ML Studio, Amazon Sagemaker, Apache Spark, Apache Flink).
11. Expertise in containerization technologies (e.g., Docker, Kubernetes) and automation tools (e.g., Jenkins, GitLab CI).
12. Excellent problem-solving skills and the ability to work independently or as part of a team.
Bonus if you have:
13. Experience with data governance and ensuring compliance with data security regulations.
14. Familiarity with performance tuning of big data technologies.
15. LLM Model development
What you will gain at Intapp:
Our culture at Intapp emphasizes accountability, responsibility, and growth. We support each other in a positive, open atmosphere that fosters creativity, approachability, and teamwork. We’re committed to creating a modern work environment that’s connected yet flexible, supporting both professional success and work-life balance. In return for your passion, commitment, and collaborative approach, we offer:
16. Competitive base salary plus variable compensation and equity
17. Generous paid parental leave, including adoptive leave
18. Traditional comprehensive benefits, plus:
Generous Paid Time Off
Tuition reimbursement plan
Family Formation benefit offered by Carrot
Wellness programs and benefits provided by Modern Health
Paid volunteer time off and donation matching for the causes you care about
19. Opportunities for personal growth and professional development supported by a community of talented professionals
20. An open, collaborative environment where your background and contributions are valued
21. Experience at a growing public company where you can make an impact and achieve your goals
22. Open offices and kitchens stocked with beverages and snacks