Principal MLOps Engineer

2 Months ago • All levels • Artificial Intelligence • $191,600 PA - $279,000 PA

Job Summary

Job Description

This role requires a seasoned Principal ML Ops Engineer to architect, build, and optimize the ML inference platform. Responsibilities include architecting and optimizing data infrastructure for machine learning and deep learning models, collaborating with cross-functional teams, owning the development and operation of high-performance inference systems, and providing technical leadership and mentorship. The ideal candidate will have proven experience in designing and implementing scalable ML inference systems, hands-on experience with leading deep learning frameworks, and a strong foundation in machine learning algorithms. Experience with the Apache Hadoop ecosystem and public cloud services (GCP and Vertex AI) is crucial. The role requires strong communication and problem-solving skills, particularly in a remote setting.
Must have:
  • Design and implement scalable ML inference systems
  • Experience with TensorFlow, Keras, or Spark MLlib
  • Strong ML algorithms, NLP, and statistical modeling knowledge
  • Proficient in computer science fundamentals
  • Apache Hadoop ecosystem expertise (Oozie, Pig, Hive, MapReduce)
  • GCP and Vertex AI expertise
  • Excellent communication and problem-solving skills

Job Details

About the Role:

We are looking for a seasoned Principal ML OPS Engineer to architect, build, and optimize ML inference platform. The role demands an individual with significant expertise in Machine Learning engineering and infrastructure, with an emphasis on building Machine Learning inference systems. Proven experience in building and scaling ML inference platforms in a production environment is crucial. This remote position calls for exceptional communication skills and a knack for independently tackling complex challenges with innovative solutions.

What you will be doing:

    • 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. 
    • 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.
The following information is required by pay transparency legislation in the following states: CA, CO, HI, NY, and WA. This information applies only to individuals working in these states.
 
·       The anticipated starting pay range for Colorado is: $204,000 - $255,00
·       The anticipated starting pay range for the states of Hawaii and New York (not including NYC) is: $191,600 - 239,500
·       The anticipated starting pay range for California, New York City and Washington is: $223,200 - 279,000
 
Unless already included in the posted pay range and based on eligibility, the role may include variable compensation in the form of bonus, commissions, or other discretionary payments. These discretionary payments are based on company and/or individual performance and may change at any time. Actual compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. Information on benefits offered is here.


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About Rackspace Technology
We are the multicloud solutions experts. We combine our expertise with the world’s leading technologies — across applications, data and security — to deliver end-to-end solutions. We have a proven record of advising customers based on their business challenges, designing solutions that scale, building and managing those solutions, and optimizing returns into the future. Named a best place to work, year after year according to Fortune, Forbes and Glassdoor, we attract and develop world-class talent. Join us on our mission to embrace technology, empower customers and deliver the future.
 
 
More on Rackspace Technology
Though we’re all different, Rackers thrive through our connection to a central goal: to be a valued member of a winning team on an inspiring mission. We bring our whole selves to work every day. And we embrace the notion that unique perspectives fuel innovation and enable us to best serve our customers and communities around the globe. We welcome you to apply today and want you to know that we are committed to offering equal employment opportunity without regard to age, color, disability, gender reassignment or identity or expression, genetic information, marital or civil partner status, pregnancy or maternity status, military or veteran status, nationality, ethnic or national origin, race, religion or belief, sexual orientation, or any legally protected characteristic. If you have a disability or special need that requires accommodation, please let us know.
 
 

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