Research Engineer - Data
United Kingdom - Remote
Leonardo.Ai
Transform your projects with our AI image generator. Generate high-quality, AI generated images with unparalleled speed and style to elevate your creative visionLeonardo.Ai, now part of the Canva family, is on a mission to redefine creativity through cutting-edge generative AI. Our platform empowers millions worldwide to effortlessly produce high-quality images, videos, and more. With nearly a quarter of a billion users, we’re building a world-class R&D team to push the boundaries of AI creativity.
The Role:
As a Research Engineer – Data at Leonardo, you will architect and manage petascale data pipelines, combining text, images, 3D models, and other data modalities to drive world-class AI models. You’ll work hand-in-hand with our Researchers to create and curate large, multi-modal datasets, including synthetic data, that supercharge SOTA generative AI solutions. Your expertise in distributed systems, data processing, and experimentation will shape the backbone of our research work.
Responsibilities:
Data Acquisition & Curation
Lead the ingestion, unification, and organization of large, unstructured data sources (e.g., text, images, 3D geometry, code snippets) into scalable, high-quality datasets suitable for machine learning research and production.High-Performance Data Pipelines
Develop and optimize distributed systems for data processing, including filtering, indexing, and retrieval, leveraging frameworks like Ray, Metaflow, Spark, or Hadoop.Synthetic Data Generation
Build and orchestrate pipelines to generate synthetic data at scale, advancing research on cost-efficient inference and training strategies.Experiments & Analysis
Design and conduct experiments on dataset quality, scalability, and performance.Security & Compliance
Collaborate with legal and safety teams to ensure all data usage respects privacy, security, and ethical standards.Open-Source Contributions
Contribute to internal and external libraries or frameworks, sharing insights and breakthroughs with the wider AI community through publications or technical blogs.
Skills we like you to have:
Multi-Modal Data Expertise
Hands-on experience with images, videos, 3D geometry (mesh/solid modeling), and/or text data. Well-rounded expertise in Python and PyTorch.Synthetic Data & Inference
Passion for synthetic data generation making use of inference of pretrained models, 3D rendering engines, and/or other softwares.Distributed Computing & MLOps
Demonstrated proficiency in setting up large-scale, robust data pipelines, using frameworks like Spark, Ray, or Metaflow. Comfortable with model versioning, and experiment tracking.Performance Optimization
Good understanding of parallel and distributed computing. Experienced with setting up evaluation methodsCloud & Storage Systems
Experience with AWS, Azure, or other cloud platforms. Proficient in both relational (MySQL, PostgreSQL) and NoSQL (MongoDB, Cassandra) databases, plus vector data stores.
Our Culture
Inclusive Culture: We celebrate diversity and are committed to creating an inclusive environment where everyone feels valued and empowered. Your unique perspectives and experiences are essential to our success.
Flexible Work Environment: We understand the importance of work-life balance. Thrive personally and professionally with the option to work remotely or in our vibrant offices.
Empowering Growth: We invest in your development with continuous learning opportunities and clear pathways for career advancement tailored to your goals.
Meaningful Impact: Be part of shaping the future of AI and contribute to innovative projects with global impact.
If you’re passionate about building scalable data ecosystems that fuel the next frontier of AI innovation—and you’re excited to collaborate with top-tier researchers and engineers—join us at Leonardo.Ai to make creativity boundless for everyone.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AWS Azure Cassandra Data pipelines Distributed Systems Generative AI Hadoop Machine Learning MLOps Model inference MongoDB MySQL NoSQL Open Source Pipelines PostgreSQL Privacy Python PyTorch R R&D Research Security Spark Unstructured data
Perks/benefits: Career development
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