Principal MLOps Engineer

August 15

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Rackspace Technology

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IT as a Service • Multi-Cloud • Managed Hosting • Managed AWS/Azure/Google Cloud Platform/OpenStack/Alibaba • Managed Private Cloud for VMware/Microsoft/OpenStack

5001 - 10000

Description

• Architect and optimize our existing data infrastructure to support cutting-edge machine learning and deep learning models. • Collaborate closely with cross-functional teams to translate business objectives into robust engineering solutions. • Own the end-to-end development and operation of high-performance, cost-effective inference systems for a diverse range of models, including state-of-the-art LLMs. • Provide technical leadership and mentorship to foster a high-performing engineering team.

Requirements

• Proven track record in designing and implementing cost-effective and scalable ML inference systems. • Hands-on experience with leading deep learning frameworks such as TensorFlow, Keras, or Spark MLlib. • Solid foundation in machine learning algorithms, natural language processing, and statistical modeling. • Strong grasp of fundamental computer science concepts including algorithms, distributed systems, data structures, and database management. • Expert-level proficiency in at least one programming language such as Java, Python, or C++. • Ability to tackle complex challenges and devise effective solutions. Use critical thinking to approach problems from various angles and propose innovative solutions. • Worked effectively in a remote setting, maintaining strong written and verbal communication skills. Collaborate with team members and stakeholders, ensuring clear understanding of technical requirements and project goals. • Proven experience in Apache Hadoop ecosystem (Oozie, Pig, Hive, Map Reduce). • Expertise in public cloud services, particularly in GCP and Vertex AI.