Luma AI
Research Scientist / Engineer - Controllability, Personalization & Productization
Be an Early Applicant
The role focuses on refining Luma's foundation models for better controllability and personalization while collaborating across research, product, and design teams.
About the Role
What You’ll Do
Who You Are
Bonus Points
This is a foundational opportunity to refine, personalize, and build the final capabilities and control interface of Luma’s foundation models and drive real-world value.
You’ll sit at the intersection of research, product, and partnerships, helping close the gap between generalist capability and production needs. Your mission is to make our video foundation models more expressive, controllable, and personalized – solving the “last mile” challenges demanded by top-tier creative workflows.
You will work as a fullstack researcher across modeling, data, systems, and evaluation to translate foundational capabilities into the personalized and high-fidelity tools required by top-tier creative production.
- Controllability and Features: You will use SFT, RL, distillation, and adapter-based methods to give Luma’s models precise control and creative capabilities for high-fidelity, partner-grade workflows.
- Personalization: You will use context management, PEFT, and preference learning to embed domain expertise and long-horizon memory into our models. You’ll ground our data engine in real-world workflows, translating usage into training and data insights that shape future models.
- End-User Quality: You will define and drive end-user quality – setting success metrics, building user-aligned evaluations, and iterating on the model/data/evals loop to meet strict fidelity and reliability targets in specific verticals.
- Cross-functional Collaboration: You will partner with Product and Design to turn creative intent and user feedback into clear specs and shippable model behaviors, delivering intuitive control and dependable capabilities for users and partners.
Who You Are
- Strong foundation in machine learning with deep experience in visual generative models (diffusion/transformers or related architectures). Ideal candidates also have a deep understanding of at least one: fine-tuning, personalization, domain adaptation, data curation, targeted distillation, interpretability, or human-feedback-driven refinement.
- You are a product-obsessed researcher/engineer. You treat end users and partners as collaborators and enjoy solving specific “last mile” problems – not just optimizing public metrics.
- Hands-on experience with PyTorch and large model training.
- Contributions to state-of-the-art models in image/video generation.
- Experience collaborating with creative partners (VFX, animation, film, design tools).
- Track record building workflows/tools that materially improve iteration speed and evaluation rigor.
- Familiarity with large-scale training infrastructure and distributed systems (Ray, Slurm, Kubernetes).
The base pay range for this role is $200,000 – $450,000 per year.
About LumaLuma’s mission is to build unified general intelligence that can generate, understand, and operate in the physical world.
We believe that multimodality is critical for intelligence. To go beyond language models and build more aware, capable and useful systems, the next step function change will come from vision. So, we are working on training and scaling up multimodal foundation models for systems that can see and understand, show and explain, and eventually interact with our world to effect change.
Similar Jobs
Big Data • Fintech • Mobile • Payments • Financial Services
Lead and grow a team of 2-3 PMs owning agent tooling and workflows. Define vision and roadmap for agent experience, drive AI-first automation, partner with Operations and cross-functional teams, deliver scalable systems, and measure impact through analytics and experimentation.
Top Skills:
Agent ToolingAIAnalyticsAutomationChat SystemsExperimentationPhone SystemsWorkflow Systems
Artificial Intelligence • Hardware • Healthtech • Software
The Senior Data Platform Engineer will manage and develop the data infrastructure on Databricks and AWS, ensuring scalable and efficient data capabilities while collaborating across teams.
Top Skills:
AWSDatabricksKafkaKinesis
Artificial Intelligence • Cloud • Consumer Web • Productivity • Software • App development • Data Privacy
Lead design and implementation of shared, reusable data models and a certified metrics layer. Standardize pipeline patterns, CI/CD, and governance; modernize orchestration and observability; partner with Data Science, Infrastructure, and Product to deliver reliable analytics pipelines and enable AI-native data development.
Top Skills:
AirflowAtlanDatabricksDatabricks Metric ViewsDbtDbt MetricflowDelta LakeGreat ExpectationsMonte CarloPythonSpark SqlSQLUnity Catalog
What you need to know about the Vancouver Tech Scene
Raincouver, Vancity, The Big Smoke — Vancouver is known by many names, and in recent years, it has gained a reputation as a growing hub for both tech and sustainability. Renowned for its natural beauty, the city has become a magnet for professionals eager to create environmental solutions, and with an emphasis on clean technology, renewable energy and environmental innovation, it's attracted companies across various industries, all working toward a shared goal: advancing clean technology.
