Neuroscience PhD / ML Engineer

Clera; United States; Hybrid; USD 135,000 - 165,000; Full time

Benefits offered by this job

Equity for founding team

Flexible remote/hybrid options

Job summary

Clera is seeking a founding-team researcher and engineer to own the core inference work for a wearable device that infers emotional states in real time. You will take a model from theory to deployment, shaping how data from multimodal sensors translates into meaningful states on users' wrists.

This role sits at the crossroads of computational neuroscience and production machine learning, requiring close collaboration with hardware and product teams to embed the model in the wearable pipeline and

Qualifications

• PhD in computational neuroscience, cognitive science, active inference, or closely related field.
• Experience bridging neuroscience research and production ML systems from theory to deployment.
• Strong Python proficiency for ML model development and deployment.

Responsibilities

• Design, develop, and iterate the inference model that quantifies emotional states from multimodal wearable sensor signals.
• Bridge neuroscience research and production-grade ML systems.
• Collaborate closely with hardware and product teams to integrate the model into the wearable pipeline.
• Take ownership of model performance, versioning, and deployment as the product scales.
• Help define the scientific and engineering roadmap for the inference layer as the company grows.

Skills

Python proficiency

Model deployment

ML for inference

Team collaboration

Education

PhD in computational neuroscience

Tools

Active inference frameworks

Job description

About the Role

This is a founding-team research and engineering position at a seed-stage, Y Combinator–backed startup building a wearable device that infers and interprets real-time emotional states. The company is early — prototypes are already on users' wrists — and this hire is expected to own and ultimately lead the core inference work as the team scales.

The role sits at the intersection of computational neuroscience and production machine learning. You will be the primary person responsible for the model that quantifies emotional states from wearable sensor data, and you are expected to carry that work from research through to deployment.

What You'll Do

• Design, develop, and iterate on the inference model that quantifies emotional states from multimodal wearable sensor signals (audio, biometric, and others).

• Bridge neuroscience research — including frameworks such as active inference — and production-grade ML systems.

• Collaborate closely with hardware and product team members to integrate the model into the wearable pipeline.

• Take ownership of model performance, versioning, and deployment as the product moves toward broader release.

• Help define the scientific and engineering roadmap for the inference layer as the company grows.

What We're Looking For

Required

• PhD in computational neuroscience, cognitive science, active inference, or a closely related field.

• Demonstrated experience bridging neuroscience research and production machine learning systems — you can take a model from theory to deployment.

• Strong Python proficiency for ML model development and deployment.

• US work authorization required (visa transfers considered; new visa sponsorship is not available).

Nice to Have

• Hands-on experience with active inference or predictive coding frameworks.

• Background working with wearable or physiological sensor data.

• Comfort operating as both a researcher and an engineer in a fast-moving, small team.

Not a Fit

• Wet-lab-only neuroscience backgrounds without computational or ML components.

Compensation & Benefits

• Base salary: ~$150,000 USD (or equivalent ~GBP 75,000 for London-based candidates)

• Equity: Meaningful founding-team equity (up to 1–2%) commensurate with the seniority and founding nature of the role.

Location

Primary office locations are London, UK and San Francisco, CA, USA. The team is open to remote or hybrid arrangements in addition to on-site. Location is flexible for the right candidate.