Principal MLOPs Engineer (Canada)

Rackspace Technology; Toronto; Remote; CAD 90,000 - 150,000; Full time

Job summary

An innovative firm is seeking a Principal ML OPS Engineer to drive the architecture and optimization of an ML inference platform. This remote opportunity calls for a seasoned expert with a strong background in machine learning engineering, particularly in scaling inference systems in production. You'll collaborate with cross-functional teams to translate business objectives into engineering solutions, while also providing mentorship to a high-performing engineering team. If you have a passion for technology and a knack for solving complex challenges, this role offers an exciting chance to shape the future of multicloud solutions.

Qualifications

• 10+ years of experience in ML inference systems design and implementation.
• Hands-on expertise in Java and machine learning frameworks.

Responsibilities

• Architect and optimize data infrastructure for ML and deep learning models.
• Lead development of high-performance inference systems for various models.

Skills

Machine Learning Engineering

Java

NLP

Statistical Modeling

TensorFlow

Keras

Spark MLlib

Cloud Services (GCP, Vertex AI)

Apache Hadoop

Model Optimization Techniques

Education

Bachelor's in Computer Science

Master's in Computer Science

Tools

TensorFlow

Keras

Spark MLlib

Apache Hadoop

Job description

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About the Role:

We are looking for a seasoned Principal ML OPS Engineer to architect, build, and optimize an ML inference platform. The role demands significant expertise in Machine Learning engineering and infrastructure, with a focus on building ML inference systems. Proven experience in scaling ML inference platforms in production is crucial. This remote position requires excellent communication skills and the ability to independently solve complex challenges with innovative solutions.

What you will be doing:

• Architect and optimize data infrastructure to support advanced machine learning and deep learning models.
• Collaborate with cross-functional teams to convert business objectives into engineering solutions.
• Lead the development and operation of high-performance, cost-effective inference systems for various models, including state-of-the-art LLMs.
• Provide technical leadership and mentorship to foster a high-performing engineering team.

Requirements:

• Proven experience in designing and implementing scalable ML inference systems.
• Hands-on experience with frameworks like TensorFlow, Keras, or Spark MLlib.
• Strong foundation in machine learning algorithms, NLP, and statistical modeling.
• Solid understanding of algorithms, distributed systems, data structures, and databases.
• Proficiency and recent experience in Java (must have).
• Ability to solve complex problems with critical thinking and innovative solutions.
• Effective remote work experience with strong written and verbal communication skills.
• Experience with Apache Hadoop ecosystem (Oozie, Pig, Hive, MapReduce).
• Expertise in cloud services, especially GCP and Vertex AI.

Must have:

• Expertise in model optimization techniques like distillation, quantization, hardware acceleration.
• Recent and proficient experience in Java.
• Deep understanding of LLM architectures, scaling, and deployment trade-offs.
• Educational background: Bachelor's in CS with 10+ years or Master's in CS with 8+ years of relevant experience.
• Specialization in Machine Learning is preferred.

About Rackspace:

We are multicloud solutions experts, combining leading technologies across applications, data, and security to deliver end-to-end solutions. Recognized as a great place to work, we attract and develop top talent. Join us to embrace technology, empower customers, and shape the future.

We value diversity and are committed to equal employment opportunities. If you need accommodations, please let us know.