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Salary
$180k – $250k per year
Location
In office (San Francisco)
Employment
Full-Time
Overview
Company
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Profile match
Building foundation models of human state to understand brains, bodies, and environments.

About Us

Constellation is creating the AI-human translation layer that ensures humanity evolves alongside our technology. Our mission is to leverage AI towards addressing deep and meaningful problems at the core of the human experience: empowering people towards their goals, augmenting our cognition and emotional wellness, and understanding ourselves and each other. Our path forward is to move away from AI that captures human knowledge towards AI that truly understands what it is to be human. We are generating the richest multimodal dataset ever collected to build a new class of foundation models and we're seeking the founding team of engineers to build the infrastructure that makes this ambitious future a reality.

The Role

We are looking for a Founding Applied Scientist to decode the human experience. You will get to work closely with the richest multimodal dataset ever collected, and tackle truly unique problems that no one has solved before. This is a hybrid Research and Engineering role. You will be responsible for architecting pipelines for transforming the data into useful and salient features. You will define the ground truth, design the benchmarks that measure our progress, and deploy models that power our product. You will also have full visibility into the lifecycle of our data and get to influence the data collection strategy.

Responsibilities

  • Train and fine-tune deep learning models (PyTorch/JAX). You will translate raw signals into interpretable behavioral constructs.

  • Perform advanced time-series analysis to identify latent state changes, clusters, and transitions. You will turn “data” into “insights” for both research and product.

  • Architect cloud-based pipelines capable of processing petabytes of data.

  • Define ground truth and evaluation metrics. You have experience defining rigorous benchmarks and curating validation data.

  • Implement active learning loops to improve model performance efficiently using our massive incoming data streams.

  • Clean, wrangle, and interpret noisy, high-variability real-world data.

Qualifications

  • Top-Tier Publications in major conferences (NeurIPS, ICLR, CVPR, ICML) or high-impact journals (Nature, Science).

  • Proficiency in PyTorch or JAX. You can implement papers from scratch and modify architectures for custom needs.

  • Strong expertise in Python.

  • Deep experience in Time-Series Analysis plus at least two of the following domains:

  • Computer Vision

  • NLP / Audio / Speech Processing

  • Biosignal / Neural Time Series

  • Experience architecting data processing pipelines and deploying models in the cloud.

  • Demonstrably adaptable and excited about finding creative solutions to problems nobody has solved before.

  • Passionate about positively imparting the well-being of humanity and not just capitalizing on it.

  • You thrive in a high-bandwidth, collaborative environment.

Nice to Have

  • Familiarity with neuroadaptive systems, biofeedback, or closed-loop stimulation paradigms.

  • Exposure to large-scale foundation models.

  • Experience working on a product where your analysis directly informed strategy or UX.

  • Interest in neurotech, mental health, or human-AI interaction.

Benefits

  • Comprehensive, high-quality health, dental, and vision insurance with premiums fully covered.

  • A renovated, light-filled office with a quirky layout and full kitchen in the heart of San Francisco's Mission District, surrounded by world-class food and coffee.

  • Relocation assistance for those joining us in SF and workspace setup stipend.

  • Bi-monthly team dinners and outings, plus twice-yearly off-sites and retreats.

  • Fully stocked kitchen (snacks!) and a dedicated meal budget.

  • Sponsorship for travel to relevant conferences and regular professional development activities to help you level up.

  • A minimum of 12 weeks of fully paid parental leave with a “soft-landing” transition back.

  • P aid time off (PTO)

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