Principal AI Engineer (London, hybrid)

Kittl
London
4 days ago
Applications closed

Related Jobs

View all jobs

Principal Data Scientist - NLP

Principal Machine Learning Engineer, Director (London) (Basé à London)

Urgent: Senior / Principal ML Research Engineer EngineeringLondon, UK

Principal Data Scientist and Senior Data Engineer

Principal Data Scientist

Principle Engineer

We’re in an exciting growth phase following our Series B funding and are expanding our team. Our hybrid working culture includes three office days per week (Monday, Wednesday, and Friday) at our Berlin headquarters. Looking ahead, we’re also growing London as our second location, with a new office planned for 2025.

A little about us

  • Redefining graphic design:Kittl is transforming how creators work with an intuitive platform that stands as a modern, competitive alternative to traditional design tools: Build the new Adobe of tomorrow.

  • Rapid growth:Millions of users within just two years of launch

  • Diverse team:120+ team members representing 30+ different countries

  • Truly product-led company:Engineers, Product managers and designers are at the core of Kittl - shaping an engineering driven working culture

  • Strong funding:Raised over $45M from world-renowned investors who have also backed companies like Slack, Dropbox, and Figma

Your role at Kittl

As a Principal AI Engineer at Kittl, you will lead the AI Platform team, driving AI initiatives across the company and ensuring seamless integration of state-of-the-art models into our product ecosystem. Your work will directly influence the development of transformative features, optimizing workflows, and scaling AI-powered capabilities, specifically for graphic design. You will collaborate closely with product and business stakeholders to align AI advancements with strategic goals while maintaining and evolving the internal AI infrastructure. You will report to the CTO.

What you’ll do

  • Lead AI infrastructure development:Architect, maintain, and evolve the internal AI inference infrastructure to support scalable and efficient model deployment.

  • Drive AI strategy & roadmap:Develop and execute the technical roadmap for AI at Kittl, aligning it with business objectives while identifying opportunities for AI-driven innovation across the company. Establish best practices, ethical guidelines, and governance frameworks to ensure responsible AI adoption and a sustainable, long-term AI strategy.

  • Enable cross-team AI adoption:Establish processes and best practices to help product managers and engineers uncover AI opportunities, fostering AI-driven decision-making across teams.

  • Optimize AI performance & efficiency:Ensure robust, scalable, and cost-effective AI inference by optimizing model deployment, resource allocation, and infrastructure scalability.

  • Bridge product & business needs:Work closely with product and business teams to translate high-level goals into actionable AI solutions, ensuring AI initiatives deliver measurable impact.

What you’ll need

  • Experience with Gen AI & deep learning:At least 5 years of demonstrated success in deploying and optimizing deep learning models in production, with a focus on diffusion models and LLMs.

  • Leadership:At least 2 years in a leadership role guiding teams and defining AI strategy.

  • Infrastructure & scalability expertise:Strong knowledge of AI infrastructure, cloud platforms (AWS, GCP, or Azure), and model optimization techniques for efficient deployment.

  • Strategic & leadership skills:Ability to define and execute an AI strategy, aligning technical roadmaps with business goals while guiding cross-functional teams.

  • Hands-on technical skills:Proficiency in Python, Pytorch, Diffusers, and distributed computing frameworks.

  • Strong communication & collaboration:Ability to convey complex AI concepts to technical and non-technical stakeholders, driving alignment and adoption across teams.

  • Continuous learning & adaptability:Stay up-to-date with the latest advancements in AI, ensuring Kittl remains at the forefront of innovation in a rapidly evolving field.

We are looking for someone

  • Exceptionally driven to drive impact and challenge the status quo.

  • Who takes extreme ownership & gets things done.

  • Who goes above and beyond in their role.

  • Who is deeply passionate about what they do.

Benefits

  • Maximise your impact:No matter if you’re leading a team or you stand out by your domain expertise - all we care about is supporting you to maximise your own impact.

  • Hackathons:Our quarterly hackathons provide an environment to experiment with new concepts, push boundaries, and potentially deliver the next big thing.

  • Kittl Week:Each year, our global team gathers together for a whole week, to work, celebrate, get inspired, and have fun.

  • Flexible working hours:Our core hours are 11am–5pm CET, leaving the rest of your schedule flexible to fit your style.

  • Workspace access:Premium WeWork All Access account, enabling you to work from any global WeWork location.

  • Remote work:Work up to 50 days (10 weeks) fully remote per year from anywhere in the world, as long as you maintain our core hours.

  • Learning & development:Our L&D budget supports your professional growth.

  • Vacation:Up to 30 vacation days per year.

At Kittl, we embrace diversity and value every team members unique background, identity, and experience. Were all about respect, honesty, and inclusivity. Together, we create a safe and supportive work environment where everyone thrives. Join us on this exciting journey of making our company and product even better!

J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

McKinsey & Company Data‑Science Jobs in 2025: Your Complete UK Guide to Turning Data into Impact

When CEOs need to unlock billion‑pound efficiencies or launch AI‑first products, they often call McKinsey & Company. What many graduates don’t realise is that behind every famous strategy deck sits a global network of data scientists, engineers and AI practitioners—unified under QuantumBlack, AI by McKinsey. From optimising Formula One pit stops to reducing NHS wait times, McKinsey’s analytics teams turn messy data into operational gold. With the launch of the McKinsey AI Studio in late 2024 and sustained demand for GenAI strategy, the firm is growing its UK analytics headcount faster than ever. The McKinsey careers portal lists 350+ open analytics roles worldwide, over 120 in the UK, spanning data science, machine‑learning engineering, data engineering, product management and AI consulting. Whether you love Python notebooks, Airflow DAGs, or white‑boarding an LLM governance roadmap for a FTSE 100 board, this guide details how to land a McKinsey data‑science job in 2025.

Data Science vs. Data Mining vs. Business Intelligence Jobs: Which Path Should You Choose?

Data Science has evolved into one of the most popular and transformative professions of the 21st century. Yet as the demand for data-related roles expands, other fields—such as Data Mining and Business Intelligence (BI)—are also thriving. With so many data-centric career options available, it can be challenging to determine where your skills and interests best align. If you’re browsing Data Science jobs on www.datascience-jobs.co.uk, you’ve no doubt seen numerous listings that mention machine learning, analytics, or business intelligence. But how does Data Science really differ from Data Mining or Business Intelligence? And which path should you follow? This article demystifies these three interrelated yet distinct fields. We’ll define the core aims of Data Science, Data Mining, and Business Intelligence, highlight where their responsibilities overlap, explore salary ranges, and provide real-world examples of each role in action. By the end, you’ll have a clearer sense of which profession could be your ideal fit—and how to position yourself for success in this ever-evolving data landscape.

UK Visa & Work Permits Explained: Your Essential Guide for International Data Science Talent

Data science has rapidly evolved into a driving force for businesses and organisations worldwide. In the United Kingdom, companies across sectors—including finance, retail, healthcare, tech start-ups, and government agencies—are turning to data-driven insights to boost competitiveness and innovation. Whether you specialise in statistical modelling, machine learning, or advanced analytics, data scientists are in high demand throughout the UK’s vibrant tech ecosystem. If you’re an international data scientist aiming to launch or grow your career in the UK, one essential part of the journey is navigating the country’s visa and work permit system. From understanding how to secure sponsorship as a Skilled Worker to exploring the Global Talent Visa for leading experts, this article will help you understand the most relevant routes, criteria, and practical steps for your move. Let’s delve into everything you need to know about working in data science in the UK as an international professional.