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:
- Design and implement robust MLOps and LLMOps pipelines to automate and optimize machine learning model training, testing, deployment, and scaling.
- Collaborate with data scientists and software engineers to ensure operational criteria are met before deployment.
- Maintain and enhance continuous integration (CI) and continuous deployment (CD) environments for machine learning systems.
- Develop tools to improve visibility into the system's operation and to facilitate rapid troubleshooting and debugging.
- Foster a culture of continuous improvement by incorporating feedback and lessons learned into future ML deployments.
- Lead initiatives to increase the resilience and scalability of ML systems.
What you need:
- Bachelor’s degree in computer science, Engineering, Statistics, or a related field.
- Experience in software development or data engineering, with at least 3 years focused on MLOps or similar roles.
- Proven track record in designing and deploying scalable machine learning systems in production.
- 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).
- Expertise in containerization technologies (e.g., Docker, Kubernetes) and automation tools (e.g., Jenkins, GitLab CI).
- Excellent problem-solving skills and the ability to work independently or as part of a team.
Bonus if you have:
- Experience with data governance and ensuring compliance with data security regulations.
- Familiarity with performance tuning of big data technologies.
- 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:
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Intapp provides equal employment opportunities to all qualified applicants and will make hiring decisions without regard to race, color, sex, sexual orientation, gender identity or expression, religion, national origin or ancestry, age, disability, marital status, pregnancy, protected veteran status, protected genetic information, political affiliation, or any other characteristic protected by federal, state or local laws. All offers are contingent upon passing a criminal history and other background checks if applicable to the position.
Please note: Intapp will not hire through text message, social media, or email alone. We will never extend a job offer unless you have been contacted directly by an Intapp recruiter and have participated in the interview process which will generally consist of 3 or more virtual or in person meetings. Please note that Intapp only uses company email addresses, which contain “@intapp.com” or “@dealcloud.com” to communicate with candidates via email. Intapp will never ask for financial information of any kind or for any payment during the job application process. We post all legitimate job openings on the Intapp Career Site at https://www.intapp.com/working-at-intapp/. If you believe you were a victim of such a scam, you may contact your local authorities. Intapp is not responsible for any claims, losses, damages, or expenses resulting from scammers.
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