Sr. Machine Learning Engineer, Amazon General Intelligence (AGI) (Basé à London)
Sr. Machine Learning Engineer, Amazon General Intelligence (AGI) (Basé à London)

Sr. Machine Learning Engineer, Amazon General Intelligence (AGI) (Basé à London)

Full-Time 48000 - 84000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Lead the development of cutting-edge ML training infrastructure and solve complex AI challenges.
  • Company: Join Amazon, a leader in AI innovation, shaping the future of technology.
  • Benefits: Enjoy competitive pay, remote work options, and a range of corporate perks.
  • Why this job: Be at the forefront of AI, collaborating with top minds and accelerating your career growth.
  • Qualifications: 8+ years in software development, expertise in ML infrastructure, and strong programming skills required.
  • Other info: This role offers a unique opportunity to create history in artificial intelligence.

The predicted salary is between 48000 - 84000 £ per year.

Our Machine Learning training infrastructure (ML Infra) team is responsible for designing, implementing, and optimizing large-scale computing infrastructure that powers our cutting-edge AI and machine learning initiatives. We leverage advanced hardware, innovative software architectures, and distributed computing techniques to enable breakthrough research and product development across the company.

We are seeking a Senior Machine Learning Engineer to join our team and lead the development of our next-generation ML training infrastructure. This is a high impact, high visibility role that will shape the future of our machine learning capabilities and contribute to the advancement of AI technology across the industry.

Key job responsibilities
  • Lead the definition, design, architecture quality, implementation, and delivery of the most advanced, most difficult, most cross-cutting, and/or most ambiguous challenges spanning across our ML infrastructure.
  • Align the teams in ML Infrastructure and related organizations to a coherent technical vision and deliver systems that fit well together.
  • Exert influence over multiple teams, increasing their productivity and effectiveness.
  • Considered to be an authority on technical issues by both the technical and research community, responsible for guiding difficult trade-off decisions and driving awareness about the impact and consequences of technical decisions on AI research and product development.
  • Demonstrate significant innovation, creativity, and judgement when solving challenging AI/ML infrastructure problems.
  • Identify future skills needed across your organization and advocate for the development and/or acquisition of those skills to senior leaders.
  • Scout top talent and recruit them to the company.
  • Actively mentor senior and Principal engineers, scale yourself by developing and institutionalizing best practices in AI/ML infrastructure and distributed computing across the organization.
A day in the life
  • 8+ years of professional software development experience in distributed systems with emphasis on ML infrastructure.
  • 8+ years of current programming experience building ML infrastructure using languages such as Python, C++ or Rust.
  • Hands-on experience with parallel computing platforms such as CUDA, OpenMP, etc.
  • Deep understanding of AI frameworks such as PyTorch, TensorFlow, and JAX, and their demands on underlying compute infrastructure, memory bandwidth, network interconnect, and storage as scale goes up.
  • Knowledge of emerging AI hardware accelerators and architectures.
  • Experience with containerization and orchestration technologies (Docker, Kubernetes).
  • Experience with cloud computing platforms (AWS, Azure, GCP) and their offerings.
About the team

Join our AGI team and work at the forefront of AI. Collaborate with top minds pushing boundaries in deep learning, reinforcement learning, and more. Gain valuable experience and accelerate your career growth. This is a unique opportunity to create history and shape the future of artificial intelligence.

Mission of the team: We leverage our hyper-scalable, general-purpose large model training and inference systems to develop and deploy cutting-edge sensory AI foundational models that revolutionize machine perception, interpretation and interaction, with humans and with the physical world.

BASIC QUALIFICATIONS
  • 5+ years of non-internship professional software development experience.
  • 5+ years of programming with at least one software programming language experience.
  • 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience.
  • Experience as a mentor, tech lead or leading an engineering team.
PREFERRED QUALIFICATIONS
  • 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience.
  • Bachelor's degree in computer science or equivalent.

Sr. Machine Learning Engineer, Amazon General Intelligence (AGI) (Basé à London) employer: Golden Bees

Amazon is an exceptional employer, particularly for a Senior Machine Learning Engineer in London, offering a dynamic work culture that fosters innovation and collaboration at the forefront of AI technology. Employees benefit from extensive growth opportunities, mentorship from industry leaders, and access to cutting-edge resources, all while contributing to impactful projects that shape the future of machine learning. With a commitment to inclusivity and a comprehensive benefits package, Amazon provides a rewarding environment for those looking to make a significant impact in their careers.
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Contact Detail:

Golden Bees Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Sr. Machine Learning Engineer, Amazon General Intelligence (AGI) (Basé à London)

Tip Number 1

Familiarise yourself with the latest advancements in AI and machine learning infrastructure. Being well-versed in emerging technologies and trends will not only help you during interviews but also demonstrate your passion for the field.

Tip Number 2

Network with professionals in the AI and ML community, especially those who work at Amazon or similar companies. Attend industry conferences, webinars, or local meetups to make connections that could lead to referrals.

Tip Number 3

Prepare to discuss your experience with distributed systems and ML infrastructure in detail. Be ready to share specific examples of challenges you've faced and how you overcame them, as this will showcase your problem-solving skills.

Tip Number 4

Research Amazon's culture and values, particularly their focus on innovation and customer obsession. Tailoring your conversations and examples to align with these values can significantly enhance your appeal as a candidate.

We think you need these skills to ace Sr. Machine Learning Engineer, Amazon General Intelligence (AGI) (Basé à London)

Distributed Systems Development
Machine Learning Infrastructure Design
Programming in Python, C++, or Rust
Parallel Computing (CUDA, OpenMP)
AI Frameworks (PyTorch, TensorFlow, JAX)
Understanding of AI Hardware Accelerators
Containerization Technologies (Docker, Kubernetes)
Cloud Computing Platforms (AWS, Azure, GCP)
Technical Leadership and Mentorship
Design Patterns and System Architecture
Software Development Life Cycle Management
Code Review and Source Control Management
Problem-Solving and Innovation
Collaboration and Team Alignment

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in machine learning and software development. Focus on your expertise with programming languages like Python, C++, or Rust, and mention any specific projects that demonstrate your skills in ML infrastructure.

Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and machine learning. Discuss how your background aligns with the responsibilities of the role, particularly your experience in leading design and architecture of systems, and your ability to mentor others.

Showcase Technical Skills: Clearly outline your technical skills related to AI frameworks such as PyTorch and TensorFlow, as well as your experience with cloud computing platforms like AWS. Use specific examples to illustrate your hands-on experience with distributed systems and parallel computing.

Highlight Leadership Experience: Since this role involves mentoring and leading teams, be sure to highlight any previous leadership roles you've held. Discuss how you have influenced team productivity and effectiveness, and provide examples of how you've guided teams through complex technical challenges.

How to prepare for a job interview at Golden Bees

Showcase Your Technical Expertise

Be prepared to discuss your experience with distributed systems and ML infrastructure in detail. Highlight specific projects where you've implemented advanced architectures or optimised performance, as this role requires a deep understanding of technical challenges.

Demonstrate Leadership Skills

Since this position involves mentoring and leading teams, be ready to share examples of how you've influenced team productivity and effectiveness in previous roles. Discuss your approach to guiding peers and making tough technical decisions.

Familiarise Yourself with AI Frameworks

Brush up on your knowledge of AI frameworks like PyTorch, TensorFlow, and JAX. Be prepared to discuss how these frameworks interact with underlying compute infrastructure and the implications for scaling and performance.

Prepare for Problem-Solving Scenarios

Expect to face technical problem-solving questions during the interview. Practice articulating your thought process when tackling complex AI/ML infrastructure issues, showcasing your innovation and creativity in finding solutions.

Sr. Machine Learning Engineer, Amazon General Intelligence (AGI) (Basé à London)
Golden Bees
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  • Sr. Machine Learning Engineer, Amazon General Intelligence (AGI) (Basé à London)

    Full-Time
    48000 - 84000 £ / year (est.)

    Application deadline: 2027-07-09

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    Golden Bees

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