‍The Role

‍As an AI/ML Engineer, you will be instrumental in bringing our data science innovations to life. You will be responsible for building, deploying, and maintaining the scalable, production-ready machine learning pipelines and infrastructure that power our AI Growth Suite. Your focus will be on MLOps, ensuring our predictive models and LLM capabilities are reliable, efficient, and seamlessly integrated into the Infinure platform to deliver tangible business outcomes.

What you will do:

• Design and build robust MLOps pipelines for model training, deployment, and monitoring.
• Collaborate with Data Scientists to containerize and productionize Machine Learning and LLM models.
• Implement scalable and secure model serving infrastructure to handle high-throughput, low-latency requests.
• Develop and manage data drift detection, performance monitoring, and model versioning systems.
• Work closely with DevOps and Data Engineering teams to ensure a seamless end-to-end AI workflow.
• Contribute to the design and implementation of our Retrieval-Augmented Generation (RAG) system, ensuring real-time data is effectively leveraged by our LLMs.

Who you are:

• 3+ years of experience in an AI/ML Engineering or MLOps role.
• Proficiency in Python and experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Solid experience with MLOps tools and platforms (e.g., MLflow, Kubeflow, Sagemaker).
• Experience with containerization (Docker) and orchestration (Kubernetes).
• Familiarity with cloud platforms (AWS, Azure, or GCP) and CI/CD pipelines.
• Strong understanding of software engineering principles and best practices for building scalable systems.

Join us and build the infrastructure that will power the next generation of enterprise AI.