AI Research Engineer at Cantina Labs - Remote USA/EU — Columbus
Traveler-Friendly Insight
Location Flexibility: This role is open to candidates in both the USA and Europe, suggesting a distributed or hybrid remote setup. While the job description doesn't specify fully remote work explicitly, the cross-continental hiring scope strongly implies remote or async-compatible work arrangements — a positive signal for location-independent professionals.
Timezone Considerations: With hiring across both US and European timezones (roughly UTC-8 to UTC+3), expect some overlap hours. Research roles at AI startups often favor async communication for deep work, with sync meetings concentrated in a few daily windows. Nomads based in Lisbon (UTC+0/+1) or Warsaw (UTC+2) would align comfortably with both regions.
Visa Options for Nomads: Portugal's Digital Nomad Visa (D8) and Spain's Digital Nomad Visa suit US or non-EU applicants well. Within Europe, EU citizens have full freedom of movement. For US-based contractors, standard tourist visas allow stays of 90 days in Schengen.
Lifestyle Stipend Advantage: The $500/month lifestyle spending account is a standout perk — easily covers coworking memberships in Bangkok (~$150/mo), Medellín (~$120/mo), or Lisbon (~$200/mo), with funds left over for travel expenses.
- Lisbon: ~$2,500/mo comfortable living — well within reach with AI research salaries
- Bangkok: ~$1,800/mo — high savings potential
- Medellín: ~$1,500/mo — strong nomad community for tech workers
Confirm full remote status and async policies directly with the hiring team before applying.
About Cantina
Cantina Labs is a social AI company developing a suite of advanced real-time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning.
If you're excited about the potential AI has to shape human creativity and social interactions, join us in building the future!
About the Role
We're working on real-time video generation for interactive characters, spanning realistic humans, stylized characters, and non-human identities. We want these characters to feel present: to speak, react, and express themselves through their face, gestures, and body language.
This brings together a set of closely connected research problems. A character needs a consistent appearance, expressive and coherent motion, and a natural relationship between speech and movement. The model also needs to respond quickly and keep generating reliably as an interaction unfolds. Quality, controllability, and efficiency all matter.
You'll work across streaming generation, fine-tuning, distillation, inference optimization, and data. Some problems will call for a new training approach; others will come down to better examples, a more useful evaluation, or understanding a bottleneck in the implementation. Part of the job is figuring out which intervention is worth making.
You'll have substantial freedom to propose directions, investigate unfamiliar ideas, and shape what we work on next. We're looking for someone who enjoys that freedom and can turn it into a steady sequence of useful experiments.
What You'll Work On
Real-time and streaming generation. Develop models that support responsive interaction while maintaining visual quality and consistency over time. Investigate latency, continuity, and how model behavior changes during longer generation.
Character expression and motion. Explore how appearance, facial expression, gesture, and body movement come together into a coherent character. Improve the relationship between speech and motion across different identities and visual styles.
Fine-tuning and post-training. Adapt video models to new data, behaviors, and capabilities. Investigate training objectives and conditioning methods, and follow promising ideas through implementation and evaluation.
Distillation and inference optimization. Make generation faster and more efficient. Work across model-level approaches and runtime improvements, measuring their effects on quality, latency, and memory.
Data development. Spend meaningful time with the actual training examples. Identify missing coverage and recurring failure modes, improve curation and sampling, and develop data that helps models learn the behavior we want.
Evaluation. Build comparisons that make progress visible and failures understandable. Combine quantitative measurements with careful inspection of generated video and the experience of interacting with the model.
Research and collaboration. Read relevant work, reproduce and adapt useful ideas, and share early experiments, demos, and findings. Help the team decide what deserves more time and compute.
What You'll Bring
Experience training or fine-tuning video or related generative models.
Ability to learn unfamiliar methods quickly and turn ideas into useful experiments.
Good experimental judgment, ownership, and clear communication.
You'll have freedom to explore new approaches. We expect fast iteration and early sharing of results.
Compensation
When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.
Benefits for U.S.-based roles:
- Competitive salary and generous company equity
- Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina
- 42 days of paid time off, including:
- 15 PTO days
- 10 sick days
- 15 company holidays
- 2 floating holidays
- Generous parental leave & fertility support
- 401(k) retirement savings plan
- Lifestyle spending account – $500/month to use however you'd like
- Complimentary lunch and snacks for in-office employees
- One Medical membership, and more!