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Commission Machine Learning Neuroscience Jobs in California

D.) in computer science or a related field-such as artificial intelligence, computational neuroscience, or biomedical engineering-and at least three years of experience in machine learning research ...

About the role As a Machine Learning Lead at Nudge, you will drive the development of next-generation ML and imaging systems at the intersection of ultrasound, signal processing, and neuroscience.

About the role As a Machine Learning Lead at Nudge, you will drive the development of next-generation ML and imaging systems at the intersection of ultrasound, signal processing, and neuroscience.

PhD in computer science, machine learning, computational neuroscience, or related fields (or equivalent industry experience). * Expertise in deep learning frameworks (e.g., PyTorch, TensorFlow) and ...

PhD in computer science, machine learning, computational neuroscience, or related fields (or equivalent industry experience). * Expertise in deep learning frameworks (e.g., PyTorch, TensorFlow) and ...

Description We are seeking an experienced Machine Learning Research Engineer to design and apply ... Additionally, this role might be eligible for discretionary bonuses or commission payments as well ...

Machine Learning Engineer

Sunnyvale, CA · On-site

$150.40 - $277.60/hr

Sunnyvale, California, United States -- Machine Learning and AI Our team delivers algorithms that ... This role might also be eligible for discretionary bonuses or commission payments as well as ...

Machine Learning Engineer

San Francisco, CA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ... sales commissions). The final offer amount will depend on several factors, including geographic ...

Machine Learning Engineer

Mountain View, CA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ... sales commissions). The final offer amount will depend on several factors, including geographic ...

Preferred Qualifications MS or PhD in computer vision, computer graphics, machine learning ... Additionally, this role might be eligible for discretionary bonuses or commission payments as well ...

... Machine Learning Engineer with experience developing ML models for computer vision and graphics ... Additionally, this role might be eligible for discretionary bonuses or commission payments as well ...

We are looking for a Machine Learning Engineer to join and play a big part in the next revolution ... Additionally, this role might be eligible for discretionary bonuses or commission payments as well ...

Own small to medium components of machine learning systems from technical designthrough ... The amount and availability of any bonus, commission, incentive, benefits, or any other form of ...

Own small to medium components of machine learning systems from technical designthrough ... The amount and availability of any bonus, commission, incentive, benefits, or any other form of ...

The machine learning models will drive rapid design iterations by assessing potential risks and ... Additionally, this role might be eligible for discretionary bonuses or commission payments as well ...

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Commission Machine Learning Neuroscience information

What is the difference between Commission Machine Learning Neuroscience vs Data Scientist?

AspectCommission Machine Learning NeuroscienceData Scientist
Required CredentialsMaster's or PhD in Neuroscience, Machine Learning, or related fieldsBachelor's or Master's in Data Science, Computer Science, or related fields
Work EnvironmentResearch labs, healthcare, or tech companies focusing on neuroscience applicationsBusiness, tech firms, or consulting firms analyzing data across industries
Employer & Industry UsageResearch institutions, biotech, healthcare, AI startupsFinance, tech, marketing, healthcare, and consulting

Commission Machine Learning Neuroscience specialists focus on applying machine learning techniques to neuroscience data, often in research or healthcare settings. Data Scientists analyze large datasets across various industries, including finance and tech. While both roles require strong analytical skills, Commission Machine Learning Neuroscience emphasizes neuroscience expertise combined with machine learning, whereas Data Scientists have broader industry applications.

What are the most commonly searched types of Machine Learning Neuroscience jobs in California?

The most popular types of Machine Learning Neuroscience jobs in California are:

What cities in California are hiring for Commission Machine Learning Neuroscience jobs?

Cities in California with the most Commission Machine Learning Neuroscience job openings:

ML Research Scientist (Embodied AI & Reinforcement Learning)

Palo Alto, CA • On-site

Metamorphic
Software Development • 1 - 10 employees

$175 - $250/hr

Other

Posted 7 days ago


Job description

About Metamorphic

Metamorphic is developing new approaches to intelligence by combining machine learning with large-scale experimental neuroscience, informed by the principles that make the brain efficient, flexible, and robust. We are building foundation models trained on rich, continuous neural data — a high-resolution model of the brain at a scale never before possible.

Our founding team spans machine learning, neuroscience, and neurotechnology, with prior work including the MICrONS project, Neuropixels, and the Enigma project, as well as foundational scientific contributions in AI, neural computation, and embodied intelligence. Our work sits at the frontier of AI research, and we believe the highest-impact discoveries will come from researchers and engineers working as a single, tightly collaborative team.

The name Metamorphic reflects our belief that the next advances in intelligence will come from a change in form, beyond scale — from artificial to natural intelligence.

About the Role

We are hiring a Research Scientist to advance the learning algorithms and models that drive our neuro‑aligned embodied agents. You will design, train, and evaluate the methods that connect our foundation models to physical systems, working across areas such as world models, action models, reinforcement learning, and learning from demonstration. A central part of your work will be exploring how principles drawn from our neuroscience research can shape better representations, dynamics, and behaviors in embodied agents.

Unlike most labs working in this space, Metamorphic approaches embodied intelligence from the joint perspective of machine learning and large-scale neuroscience. This interdisciplinary research paradigm unlocks a new path towards safe AGI, and you will have substantial input into it. You will own end‑to‑end significant pieces of the research agenda from problem formulation through experimentation, scaling, and evaluation in both simulation and the real world. You will work closely with researchers and engineers across the team, with substantial autonomy over how methods and infrastructure evolve as the work scales.

You’ll thrive in this role if you:

  • Are excited about working in a fast‑paced, production‑focused research lab that often requires moving between algorithmic research, large‑scale experimentation, and hands‑on work in the same week

  • Have strong research taste and engineering instincts, and can move quickly between writing, shipping experiments, and rigorous evaluation

  • Are comfortable owning a research direction end‑to‑end — formulating the problem, designing experiments, running them at scale, and interpreting results carefully

  • Enjoy pair programming and deeply collaborative work, including hands‑on time with researchers and engineers across disciplines

  • Are eager to engage seriously with neuroscience and to let biological principles shape the algorithms you build, rather than treating them as decoration

  • Are enthusiastic to work at an organization that functions as a single, cohesive team pursuing large‑scale AI research

  • Have ambitious goals for AI progress and are excited to create the best outcomes over the long term

We offer:

  • The chance to work on one of the most scientifically consequential AI projects being pursued today

  • A small, world‑class team where your contributions directly shape the science and the company

  • Competitive compensation and benefits, along with visa sponsorship

  • Strong mentorship and career development

Salary Range

$175,000 - $250,000 USD

Based on experience. We additionally offer a competitive equity package and comprehensive benefits, as well as visa sponsorship for international candidates.

Minimum Qualifications
  • PhD in Machine Learning, Robotics, Computer Science, Computational Neuroscience, or a related field — or equivalent research experience demonstrated through publications and shipped systems

  • Strong publication record or technical track record in one or more of: reinforcement learning, world models, action models, imitation learning, or embodied AI

  • Deep working knowledge of modern deep learning, including large‑scale training, distributed optimization, and rigorous evaluation methodology

  • Strong software engineering skills and strong working proficiency in Python and a modern deep learning framework; ability to write training and evaluation infrastructure that other researchers can build on

  • Hands‑on experience training and evaluating policies in simulation

  • Comfort collaborating closely with engineers and researchers to deploy and evaluate methods in real‑world settings, and to iterate across models, environments, and hardware

  • Scientific rigor in experimental design, ablations, and interpretation of results

Nice to Have
  • Experience designing or extending world models, action models, or related architectures for embodied agents

  • Experience deploying learned policies on real robotic systems, including bimanual or humanoid platforms

  • Experience with sim‑to‑real transfer and co‑training across simulated and real data

  • Background in computational or systems neuroscience — neural population analysis, motor control, sensorimotor learning, or biologically‑plausible learning rules

  • Experience using neural data to constrain or evaluate machine learning models

  • Familiarity with multimodal foundation models and large‑scale pretraining

  • Experience with planning, model‑predictive control, or hybrid learning‑and‑planning approaches

  • Interest in the relationship between biological and artificial intelligence, and an appetite for cross‑disciplinary work

We encourage you to apply even if you do not believe you meet every single qualification. If you don't see a role that fits, we encourage you to submit a general application and tell us how you'd like to contribute to our mission.

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