Co-Founder & CTO

Remote (anywhere)
Full-time
Other
Posted recently

You’ll apply on Clera’s own site.

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About the Role
Join an early-stage AI marketing technology company as an equal technical co-founder, owning research strategy, product development, and team building. You will build a training and evaluation platform for creative AI, using data from a live product to improve how creative work is generated and assessed.
What You’ll Do

Set technical and research strategy, advancing current workflows into a proprietary training and evaluation platform.
Build data infrastructure connecting briefs, submissions, generation traces, decisions, critiques, and campaign outcomes.
Develop systems to evaluate, rank, critique, generate, and improve creative work.
Design allocation policies that direct campaign budgets and inform dataset collection.
Make decisions about frontier models, fine-tuning, post-training, reinforcement learning, and original research.
Build reliable infrastructure for creator workflows, campaigns, experimentation, training, and inference.
Establish standards for data quality, consent, privacy, measurement, and model evaluation.
Recruit and lead the initial engineering and research team, and work directly with creators and brands.

What We’re Looking For

Hands-on research or post-training experience at a leading AI research organization, with experience building preference or reward models, RLHF, ranking, or evaluation systems.
Practical reinforcement learning or agent-training experience, plus production ML infrastructure experience.
Experience shipping products or features used by people and owning a model, evaluation, or infrastructure program end to end.
Background in causal inference with observational data, including selection bias, off-policy or counterfactual evaluation, and adaptive experimentation.
Experience with noisy, delayed, or subjective outcomes and ads, marketplace, recommender, or ranking systems tied to business results.
Strong technical recruiting and team leadership experience. Bandits, sequential allocation, multimodal AI, planning, and latent-variable modeling are valuable.
Willingness to work full time, in person, with the commitment and uncertainty of an early-stage co-founder. A specific years-of-experience requirement was not provided.

Compensation & Benefits
Approximately 28% co-founder equity. Cash compensation is discussed based on circumstances and fit. Visa sponsorship is not available.
Location
On-site in San Francisco, California, United States.

Clera

Co-Founder & CTO

Remote (anywhere)
Full-time
Other
Posted recently

Apply on the company site

You’ll apply on Clera’s own site.

Translate this job description into

Set technical and research strategy, advancing current workflows into a proprietary training and evaluation platform.
Build data infrastructure connecting briefs, submissions, generation traces, decisions, critiques, and campaign outcomes.
Develop systems to evaluate, rank, critique, generate, and improve creative work.
Design allocation policies that direct campaign budgets and inform dataset collection.
Make decisions about frontier models, fine-tuning, post-training, reinforcement learning, and original research.
Build reliable infrastructure for creator workflows, campaigns, experimentation, training, and inference.
Establish standards for data quality, consent, privacy, measurement, and model evaluation.
Recruit and lead the initial engineering and research team, and work directly with creators and brands.

What We’re Looking For

Hands-on research or post-training experience at a leading AI research organization, with experience building preference or reward models, RLHF, ranking, or evaluation systems.
Practical reinforcement learning or agent-training experience, plus production ML infrastructure experience.
Experience shipping products or features used by people and owning a model, evaluation, or infrastructure program end to end.
Background in causal inference with observational data, including selection bias, off-policy or counterfactual evaluation, and adaptive experimentation.
Experience with noisy, delayed, or subjective outcomes and ads, marketplace, recommender, or ranking systems tied to business results.
Strong technical recruiting and team leadership experience. Bandits, sequential allocation, multimodal AI, planning, and latent-variable modeling are valuable.
Willingness to work full time, in person, with the commitment and uncertainty of an early-stage co-founder. A specific years-of-experience requirement was not provided.

Clera

Co-Founder & CTO

Remote (anywhere)
Full-time
Other
Posted recently

Apply on the company site

You’ll apply on Clera’s own site.

Translate this job description into

Set technical and research strategy, advancing current workflows into a proprietary training and evaluation platform.
Build data infrastructure connecting briefs, submissions, generation traces, decisions, critiques, and campaign outcomes.
Develop systems to evaluate, rank, critique, generate, and improve creative work.
Design allocation policies that direct campaign budgets and inform dataset collection.
Make decisions about frontier models, fine-tuning, post-training, reinforcement learning, and original research.
Build reliable infrastructure for creator workflows, campaigns, experimentation, training, and inference.
Establish standards for data quality, consent, privacy, measurement, and model evaluation.
Recruit and lead the initial engineering and research team, and work directly with creators and brands.

What We’re Looking For

Hands-on research or post-training experience at a leading AI research organization, with experience building preference or reward models, RLHF, ranking, or evaluation systems.
Practical reinforcement learning or agent-training experience, plus production ML infrastructure experience.
Experience shipping products or features used by people and owning a model, evaluation, or infrastructure program end to end.
Background in causal inference with observational data, including selection bias, off-policy or counterfactual evaluation, and adaptive experimentation.
Experience with noisy, delayed, or subjective outcomes and ads, marketplace, recommender, or ranking systems tied to business results.
Strong technical recruiting and team leadership experience. Bandits, sequential allocation, multimodal AI, planning, and latent-variable modeling are valuable.
Willingness to work full time, in person, with the commitment and uncertainty of an early-stage co-founder. A specific years-of-experience requirement was not provided.

Clera

Co-Founder & CTO

Remote (anywhere)
Full-time
Other
Posted recently

Apply on the company site

You’ll apply on Clera’s own site.

Translate this job description into

Set technical and research strategy, advancing current workflows into a proprietary training and evaluation platform.
Build data infrastructure connecting briefs, submissions, generation traces, decisions, critiques, and campaign outcomes.
Develop systems to evaluate, rank, critique, generate, and improve creative work.
Design allocation policies that direct campaign budgets and inform dataset collection.
Make decisions about frontier models, fine-tuning, post-training, reinforcement learning, and original research.
Build reliable infrastructure for creator workflows, campaigns, experimentation, training, and inference.
Establish standards for data quality, consent, privacy, measurement, and model evaluation.
Recruit and lead the initial engineering and research team, and work directly with creators and brands.

What We’re Looking For

Hands-on research or post-training experience at a leading AI research organization, with experience building preference or reward models, RLHF, ranking, or evaluation systems.
Practical reinforcement learning or agent-training experience, plus production ML infrastructure experience.
Experience shipping products or features used by people and owning a model, evaluation, or infrastructure program end to end.
Background in causal inference with observational data, including selection bias, off-policy or counterfactual evaluation, and adaptive experimentation.
Experience with noisy, delayed, or subjective outcomes and ads, marketplace, recommender, or ranking systems tied to business results.
Strong technical recruiting and team leadership experience. Bandits, sequential allocation, multimodal AI, planning, and latent-variable modeling are valuable.
Willingness to work full time, in person, with the commitment and uncertainty of an early-stage co-founder. A specific years-of-experience requirement was not provided.