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Senior Machine Learning Engineer (Inference)

  • Job
    Full-time
    Senior Level
  • United States
    Remote
  • Quick Apply

AI generated summary

  • You need strong ML inference system design skills, experience with TensorFlow or Keras, knowledge of algorithms and NLP, proficiency in a programming language, and experience in the Hadoop ecosystem and cloud services.
  • You will optimize data infrastructure, develop inference systems for various models, collaborate to align business with tech solutions, and mentor the 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.
  • 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 8 years of relevant industry experience, or
  • A Master's degree in Computer Science with at least 6 years of relevant industry experience.
  • A specialization in Machine Learning is preferred.

Responsibilities

  • 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.

FAQs

What is the primary focus of the Senior Machine Learning Engineer (Inference) role?

The primary focus is to architect, build, and optimize a Machine Learning inference platform, with an emphasis on creating high-performance and cost-effective inference systems for various models.

What qualifications are required for this position?

Candidates must have a Bachelor's degree in Computer Science with a minimum of 8 years of relevant industry experience, or a Master's degree with at least 6 years of experience, preferably with a specialization in Machine Learning.

Which programming languages are essential for this role?

Expert-level proficiency is required in at least one programming language, such as Java, Python, or C++.

Are there specific deep learning frameworks that candidates should be familiar with?

Yes, candidates should have hands-on experience with leading deep learning frameworks such as TensorFlow, Keras, or Spark MLlib.

How crucial is experience in building and scaling ML inference platforms?

Proven experience in building and scaling ML inference platforms in a production environment is crucial for this role.

Is experience with public cloud services required?

Yes, expertise in public cloud services, particularly in Google Cloud Platform (GCP) and Vertex AI, is required.

What is expected of candidates regarding team collaboration?

Candidates should be able to collaborate closely with cross-functional teams, ensuring a clear understanding of technical needs and project goals, while maintaining strong communication skills in a remote environment.

Are there any must-have skills for this role?

Must-have skills include expertise in model optimization techniques, a strong understanding of LLM architectures, and the ability to tackle complex challenges with innovative solutions.

Does Rackspace Technology value diversity and inclusion?

Yes, Rackspace Technology is committed to equal employment opportunity and embraces diverse perspectives to fuel innovation and better serve customers and communities globally.

What kind of work environment does the company promote?

Rackspace Technology promotes a remote work environment where employees are encouraged to bring their whole selves to work and thrive as valued members of a winning team.

Realize the full value of the cloud.

Technology
Industry
5001-10,000
Employees
1998
Founded Year

Mission & Purpose

Rackspace is a leading managed cloud computing company that provides a range of services to help businesses manage their cloud infrastructure and applications. They offer services such as cloud hosting, managed services, data analytics, and security solutions. Rackspace's ultimate mission is to be the trusted partner for businesses navigating the complex world of cloud computing, offering expertise and support to maximise the benefits of cloud technology. Their purpose is to empower businesses to succeed in the digital age by providing reliable and scalable cloud solutions that enhance agility, performance, and security. Rackspace aims to simplify the cloud journey for their clients, enabling them to focus on their core business while leveraging the power of the cloud to drive innovation and achieve their strategic goals.

Culture & Values

  • Excellence

    We are an accountable, disciplined, high-performing company with proven results

  • Customer-driven

    We are proactive, collaborative and committed to success for our customers.

  • Expertise

    Rackers are passionate learners who are embedded in our customers’ businesses to provide unbiased solutions.

  • Agility

    We adopt new technologies and evolve services to meet customers where they are in their journey.

  • Compassion

    We’re one team doing the right thing for our customers, communities and each other.

Benefits

  • The foundation

    Health coverage and retirement/pension plans

  • Take the time

    Enjoy generous time off and paid corporate holidays

  • Be well

    Stay active with gym memberships, health & wellness challenges, and quarterly team outings

  • Family planning

    Support your newest addition with paid maternity, paternity, and adoption leave

  • Flexible working

    For some roles, working remotely or flexibly is an option