Applied AI Engineer, Enterprise in London
Applied AI Engineer, Enterprise

Applied AI Engineer, Enterprise in London

London Full-Time 36000 - 60000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Own and optimise Generative AI solutions for enterprise customers, engaging directly with clients.
  • Company: Join Scale, a leader in developing reliable AI systems for impactful decisions.
  • Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
  • Why this job: Shape the future of AI while working on cutting-edge technology with industry leaders.
  • Qualifications: Bachelor's degree in a quantitative field and 3+ years of engineering experience.
  • Other info: Dynamic environment with a focus on innovation and collaboration.

The predicted salary is between 36000 - 60000 £ per year.

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products.

At Scale, our Enterprise team works with a variety of customers looking to be at the forefront of incorporating Generative AI capabilities into their services. Forward Deployed ML Engineers (FDMLEs) work directly with our customers to build and own robust, production-grade services which directly integrate into their products. This exciting role lies at the intersection of customer delivery and ML engineering, providing you with a wealth of experience and stimulating both sides of your brain.

In this role, your daily tasks may include:

  • Engaging in discussions with customers and understanding their generative AI needs.
  • Using platform tools and packages to finetune and iterate on modeling experiments using Large Language Models (LLM) or Retrieval Augmented Generation (RAG).
  • Designing data-driven experiments focused on optimizing model performance by deeply understanding the training data and model outputs to systematically move key metrics.

If you are excited about shaping the future of the data-centric AI movement, we would love to hear from you!

You will:

  • Own, plan, and optimize our Enterprise customer's Generative AI problems, thereby becoming the ML voice in the room that our customers turn to for solutions.
  • Understand the tools available for optimizing performance around LLMs and how to most appropriately apply or combine them in different scenarios.
  • Be analytically rigorous by asking probing questions of the data and results to root out model weaknesses.
  • Demonstrate strong proficiency for writing, testing, and debugging Python code, capable of solving programming problems such as basic algorithms and data structure manipulations.
  • Have experience gathering business requirements and translating them into technical solutions.
  • Meet regularly with customer teams onsite and virtually, collaborating cross-functionally with all teams responsible for their data and ML needs.
  • Have strong communication skills and the ability to explain technical concepts to non-technical stakeholders.
  • Push production code in multiple development environments, writing and debugging code directly in both our customer's and Scale's codebases.
  • Deeply understand the AI strategy, goals, and needs of the customers.
  • Build deep relationships with technical stakeholders at all levels and across all roles, both internally and externally.
  • Be able and willing to multi-task and learn new technologies quickly.

Ideally you'd have:

  • Strong engineering background: a Bachelor's degree in Computer Science, Mathematics, or another quantitative field or equivalent strong engineering background.
  • 3+ years of engineering experience, post-graduation in a client-facing setting.
  • At least 2 years of model training experience, specifically in translating business problems into data/model problems.
  • Deep familiarity with a data-driven approach when iterating on machine learning models and how changes in datasets can influence model results.
  • Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.
  • Experience operating in a fast-paced environment with ambiguity.
  • Proficiency in Python to write, test and debug code using common libraries (ie numpy, pandas) and create functions to break down problems into modular components focused on robustness, readability and maintainability.

Nice to haves:

  • Strong knowledge of software engineering best practices.
  • Have experience with AI platforms and technologies, including generative models and LLMs.
  • Have built applications taking advantage of Generative AI in real, production use cases.
  • Familiarity with state of the art LLMs and their strengths/weaknesses.

About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com.

Applied AI Engineer, Enterprise in London employer: Scale

At Scale, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our commitment to employee growth is evident through continuous learning opportunities and the chance to work with cutting-edge AI technologies in a fast-paced environment. Located at the heart of the tech industry, we provide our team with the unique advantage of engaging directly with leading enterprises, ensuring that every day is both meaningful and rewarding.
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Contact Detail:

Scale Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Applied AI Engineer, Enterprise in London

✨Tip Number 1

Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. The more you engage, the better your chances of landing that Applied AI Engineer role.

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs or generative AI. This will give you an edge and demonstrate your hands-on experience to potential employers.

✨Tip Number 3

Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical stakeholders.

✨Tip Number 4

Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are genuinely interested in joining our mission at Scale.

We think you need these skills to ace Applied AI Engineer, Enterprise in London

Machine Learning Engineering
Generative AI
Large Language Models (LLM)
Retrieval Augmented Generation (RAG)
Data-Driven Experimentation
Python Programming
Debugging Skills
Cloud Technology (AWS or GCP)
Communication Skills
Client-Facing Experience
Model Training
Software Engineering Best Practices
Analytical Skills
Cross-Functional Collaboration
Adaptability

Some tips for your application 🫡

Show Your Passion for AI: When writing your application, let your enthusiasm for AI shine through! We want to see how excited you are about shaping the future of AI and how it can impact lives. Share any personal projects or experiences that highlight your passion.

Tailor Your Application: Make sure to customise your application to reflect the specific skills and experiences mentioned in the job description. We love seeing candidates who take the time to align their background with what we're looking for, especially around LLMs and generative AI.

Be Clear and Concise: Keep your writing clear and to the point. We appreciate well-structured applications that get straight to the heart of your qualifications. Avoid jargon unless it's relevant, and make sure your key achievements stand out!

Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re serious about joining our team at Scale!

How to prepare for a job interview at Scale

✨Know Your AI Stuff

Make sure you brush up on the latest trends in generative AI and large language models. Be ready to discuss how these technologies can be applied to real-world problems, especially in a client-facing context. This shows you're not just knowledgeable but also passionate about the field.

✨Show Off Your Problem-Solving Skills

Prepare to share specific examples of how you've tackled complex engineering challenges in the past. Think about times when you translated business needs into technical solutions, especially involving data-driven approaches. This will demonstrate your analytical rigor and ability to think critically.

✨Communicate Like a Pro

Since you'll be working with both technical and non-technical stakeholders, practice explaining complex concepts in simple terms. Use analogies or relatable examples to make your points clear. Strong communication skills are key in this role, so don’t underestimate their importance!

✨Get Familiar with the Tools

Before the interview, take some time to explore the tools and platforms mentioned in the job description, like AWS or GCP. Being able to discuss your experience with these technologies will show that you're proactive and ready to hit the ground running.

Applied AI Engineer, Enterprise in London
Scale
Location: London

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