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E11 Bio - Machine Learning Scientist I/II
Alameda, CA, Open to Remote
Actively hiring, first seen by us 5 hours ago- Pay
Multiple pay statements — pay source
Stipend for fitness and wellness activities. Base Salary Range: $130,000 - $225,000 Bonus: Performance-based, up to 20% of base salary
401k match: up to 6% of base salary Total potential compensation range: $163,800 - $283,500 Salary
Salary 130,000 – 225,000 USD per year E11 Bio, LLC is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. We do not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender-identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. We strive for a healthy and safe workplace and strictly prohibit harassment of any kind.
Read the full posting- Work setting
Working pattern needs review — work setting source
Listed location: Alameda, CA, Open to Remote
Work setup in the employer’s posting: onsite
From the employer’s posting- Employment
Full-time — employment source
Employment type Full Time
Employment type in the employer’s posting: Full Time
From the employer’s posting
What you’ll work on
Full postingOwn the deployment of scalable workflows to ingest large connectomic datasets into standard proofreading software (WebKnossos, CAVE)
Collaborate with academic and industry experts on building and extending tools for automated proofreading and interactive visualization
From the employer’s posting
Contribute to developing innovative ML approaches for automatic proofreading of segmentations in large PB-scale optical connectomics volumes, leveraging shape and barcode information Own the deployment of scalable workflows to ingest large connectomic datasets into standard proofreading software (WebKnossos, CAVE) Collaborate with academic and industry experts on building and extending tools for automated proofreading and interactive visualization
Own the deployment of scalable workflows to ingest large connectomic datasets into standard proofreading software (WebKnossos, CAVE) Collaborate with academic and industry experts on building and extending tools for automated proofreading and interactive visualization Develop, implement, and evaluate scalable pipelines for synapse detection and partner assignment in large-scale optical connectomics datasets, integrating morphological and protein labeling information
What you’ll bring
All qualificationsCore experience
- 3-5 years of relevant work or research experience, with strong history of independent and autonomous execution of novel ML solutions
- Experience with software engineering best practices (e.g.
- Excellent communication and collaboration skills, record keeping ability, and attention to detail
Preferred experience
- Experience with graph, sequence, or point based ML methods (GNNs, Transformers, Pointnets, etc.)
- Experience with processing large chunked data (e.g Zarr) in the cloud (e.g.
- Experience with large scale connectomics data and tools (e.g.
Qualification wording
3-5 years of relevant work or research experience, with strong history of independent and autonomous execution of novel ML solutions
Experience with software engineering best practices (e.g. version control, code reviews, etc)
Excellent communication and collaboration skills, record keeping ability, and attention to detail
Experience with graph, sequence, or point based ML methods (GNNs, Transformers, Pointnets, etc.)
Experience with processing large chunked data (e.g Zarr) in the cloud (e.g. AWS or GCP)
Experience with large scale connectomics data and tools (e.g. Neuroglancer, WebKnossos, CAVE, CATMAID, etc.)
Education & alternatives
Required qualifications - Ph.D. in computer science, machine learning, applied math, computational biology or a related field in science and/or engineering or Ph.D.-equivalent publication history - 3-5 years of relevant work or research experience, with strong history of independent and autonomous execution of novel ML solutions
Posting record
Report an errorActively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 15, 2026today
- Recorded sightings
- 1
- Employer says posted
- Nov 13, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
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Where the posting names them
- Experience with graph, sequence, or point based ML methods (GNNs, Transformers, Pointnets, etc.) - Experience with processing large chunked data (e.g Zarr) in the cloud (e.g. AWS or GCP) - Experience with large scale connectomics data and tools (e.g. Neuroglancer, WebKnossos, CAVE, CATMAID, etc.)
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Demand for Data Scientist roles
New Data Scientist postings at the employers we follow are down 5% over the last 6 weeks compared with the 6 before.
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About the role
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
US government figures for data scientists
- Median yearly pay, May 2025
- $120,230
- Expected change, 2025 to 2035
- 34.6% more jobsagainst 3.5% for all jobs
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Job description
E11 Bio is on a mission to advance connectomics towards the scale of whole mammalian brains. We are a collaborative and interdisciplinary team of scientists and engineers engaged in a neuroscience moonshot project to develop a radical technology platform for scalable brain mapping. E11 Bio is a non-profit Convergent Research focused research organization located in Alameda, California, pursuing blue-skies neuroscience research yet operating like a nimble, tight-knit start-up. Read our technology roadmap.
We are seeking a creative and mission-driven Machine Learning Scientist to develop scalable automatic proofreading methods leveraging barcode and shape information. In this role, you will own core ML pipelines for automated proofreading of neuron and synaptic reconstructions in optical connectomics datasets, working closely with wet lab scientists, microscopists, and domain experts to ensure biological fidelity and scalability. Your work will directly support E11’s goal of making reliable connectomic data accessible to the broader neuroscience community.
In this role you will be focused on decreasing segmentation and proofreading costs for optical connectomics datasets that we are generating at E11, a critical bottleneck in the connectomics field. You will be responsible for improving initial segmentations using large spatial contexts with rich data features, and ingesting resulting datasets into scalable proofreading software for dissemination to the scientific community.
Responsibilities
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Contribute to developing innovative ML approaches for automatic proofreading of segmentations in large PB-scale optical connectomics volumes, leveraging shape and barcode information
-
Own the deployment of scalable workflows to ingest large connectomic datasets into standard proofreading software (WebKnossos, CAVE)
-
Collaborate with academic and industry experts on building and extending tools for automated proofreading and interactive visualization
-
Develop, implement, and evaluate scalable pipelines for synapse detection and partner assignment in large-scale optical connectomics datasets, integrating morphological and protein labeling information
-
Identify and build ML-based image processing tools that remove key bottlenecks in our data processing and analysis pipeline
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Maintain excellent laboratory science practices, communicate results through reports and presentations, and contribute to and assist in preparation of manuscripts, abstracts and other scientific documents.
Required qualifications
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Ph.D. in computer science, machine learning, applied math, computational biology or a related field in science and/or engineering or Ph.D.-equivalent publication history
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3-5 years of relevant work or research experience, with strong history of independent and autonomous execution of novel ML solutions
-
Strong background in computer vision and applying ML tools to the analysis of large microscopy data sets
-
Experience with software engineering best practices (e.g. version control, code reviews, etc)
-
Excellent communication and collaboration skills, record keeping ability, and attention to detail
Preferred qualifications
-
Experience with graph, sequence, or point based ML methods (GNNs, Transformers, Pointnets, etc.)
-
Experience with processing large chunked data (e.g Zarr) in the cloud (e.g. AWS or GCP)
-
Experience with large scale connectomics data and tools (e.g. Neuroglancer, WebKnossos, CAVE, CATMAID, etc.)
-
Strong record of publications in peer reviewed scientific journals a plus.
In the first six months, you will:
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Become familiar with our existing ML and distributed processing code bases
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Own the processing (segmentations) of a new dataset end-to-end and identify areas for improvement (accuracy and efficiency)
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Integrate internal graph-based methods for automatic proofreading into standard block-wise workflows for PB-scale optical connectomics volumes
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Optimize ingestion of smaller segmentation graphs into standard proofreading software (e.g WebKnossos, CAVE) for improving efficiency of ground truth generation
In 12 months, you will:
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Develop novel innovative ML approaches for automatic proofreading of neuron segmentations, leveraging both shape and barcode information
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Contribute to algorithmic development across the segmentation pipelines increasing computational throughput
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Contribute to achieving cubic-mm scale reconstruction at 100x lower proofreading costs
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Scale ingestion of PB-sized optical volumes into proofreading software and pilot proofreading and dissemination of large connectomic subgraphs
You would love this job if…
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You are passionate about moonshot neuroscience, and want to broadly accelerate science through long-term commitment to a high-impact project with a tight-knit team
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You have a strong desire and intrinsic motivation to work collaboratively and inclusively as part of an interdisciplinary team science effort
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You are committed to the ethos of open science, and want to see your work transparently disseminated
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You’re mission-driven, and are seeking an environment where you can take long-term risks on moonshot science, shielded from academic or for-profit incentives
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You’re seeking a high-leverage, non-traditional opportunity to maximize the impact of your science, establishing relationships with key stakeholders in the neuroscience community
We Offer
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An opportunity to help change the world and work with a world-class interdisciplinary team of scientists and engineers on a field-defining moonshot
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Excellent medical, dental, and vision insurance through a PPO plan; parental leave.
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Generous time off + paid holidays.
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401K matching up to 6% of base salary
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Ample healthy and energizing food including daily lunches.
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Stipend for fitness and wellness activities.
Base Salary Range: $130,000 - $225,000
Bonus: Performance-based, up to 20% of base salary
401k match: up to 6% of base salary
Total potential compensation range: $163,800 - $283,500
Salary
130,000 – 225,000 USD per year
E11 Bio, LLC is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. We do not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender-identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. We strive for a healthy and safe workplace and strictly prohibit harassment of any kind.
Employment type
Full Time
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Stipend for fitness and wellness activities. Base Salary Range: $130,000 - $225,000 Bonus: Performance-based, up to 20% of base salary
More source context
401k match: up to 6% of base salary Total potential compensation range: $163,800 - $283,500 Salary
More relevant text appears in the full description.
- Location & working pattern
Alameda, CA, Open to Remote
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.