Machine Learning Operations (MLOps) Architect - GCP
Job Summary
Job Description
We are seeking a Machine Learning Operations (MLOps) Architect to build and optimize ML inference platforms. This role requires significant expertise in Machine Learning engineering and infrastructure, focusing on building ML inference systems. You will be responsible for architecting and optimizing data infrastructure for machine learning and deep learning models, collaborating with cross-functional teams, and owning the end-to-end development and operation of high-performance inference systems for various models, including LLMs. The position also involves providing technical leadership and mentorship. The ideal candidate will have proven experience in designing and implementing scalable ML inference systems, hands-on experience with deep learning frameworks like TensorFlow or PyTorch, a solid understanding of machine learning algorithms and NLP, strong computer science fundamentals, and excellent communication and problem-solving skills, with experience in remote work environments.
Must have:
- Expertise in model optimization techniques (distillation, quantization, hardware acceleration) for production.
- In-depth understanding of LLM architectures, parameter scaling, and deployment trade-offs.
- Technical degree (BS CS with 10+ years experience or MS CS with 8+ years experience).
- Specialization in Machine Learning preferred.
Good to have:
- Architect and optimize data infrastructure for ML/DL models.
- Translate business objectives into engineering solutions.
- Own end-to-end development of high-performance inference systems.
- Provide technical leadership and mentorship.
- Experience with leading deep learning frameworks (TensorFlow, Keras, Spark MLlib).
- Solid foundation in ML algorithms, NLP, and statistical modeling.
- Strong computer science concepts (algorithms, distributed systems, data structures).
- Experience with Apache Hadoop ecosystem (Oozie, Pig, Hive, Map Reduce).
- Expertise in GCP and Vertex AI.
Perks:
- Travel as needed per business requirements
12 skills required
Job Details
About the Role:
We are looking for a seasoned Machine Learning Operations (MLOPs) Architect to 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.
Must have:
- Proven expertise in applying model optimization techniques (distillation, quantization, hardware acceleration) to production environments.
- In-depth understanding of LLM architectures, parameter scaling, and deployment trade-offs.
- Technical degree: Bachelor's degree in Computer Science with a minimum of 10+ years of relevant industry experience, or
- A Master's degree in Computer Science with at least 8+ years of relevant industry experience.
- A specialization in Machine Learning is preferred.
Travel
- Travel as needed per business requirements
Sponsorship
- This role is not sponsorship eligible
- Candidates need to be legally able to work in the US for any employers
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: $143,700 - 210,760
· The anticipated starting pay range for the states of Hawaii and New York (not including NYC) is: $153,000 - 224,400
· The anticipated starting pay range for California, New York City and Washington is: $167,400 - 245,520
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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