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computational scientist 3 - cell & tissue genomics Jobs in San Francisco

product engineer

applied scientist

THRAD

<div><h3 class="jobSectionHeader">The Role</h3>
We are looking for an Applied Scientist to own the models that decide which ad appears in which AI conversation, in real time, across millions of queries a day. Ad selection inside LLM chats is a genuinely new problem: no click history, no cookies, no page context. Just an evolving conversation and a few hundred milliseconds to make a decision that has to feel native to the user, relevant to the advertiser, and profitable for the publisher.
This is a research role with a production mandate. Your models go live, not into a paper. You will work directly with our CTO and the founding engineering team on the systems powering millions of ads a day across Fortune 500 campaigns.<h3 class="jobSectionHeader">
Core Tech Stack</h3><ul><li>
ML: PyTorch, embedding-based retrieval, modern transformer architectures</li><li>
Backend: Python (FastAPI), async serving, real-time inference</li><li>
Data: PostgreSQL for transactional, ClickHouse for analytics and event data</li><li>
Infra: AWS, Docker, CI/CD</li><li>
Plus: whatever the problem demands. We pick tools that ship.</li></ul><h3 class="jobSectionHeader">
Example Projects</h3><ul><li>
Design and train contextual ad relevance models for LLM conversations, from retrieval through ranking through creative selection.</li><li>
Build efficient algorithms for real-time bidding and auction mechanics, balancing publisher yield and advertiser ROAS.</li><li>
Productionize regression models to predict downstream conversion from early conversational signals.</li><li>
Apply privacy-preserving clustering methods to categorize conversational context and improve advertiser targeting without compromising user data.</li><li>
Run live experiments against real traffic on our publisher network. Iterate on CTR, ROAS, and conversation quality metrics.</li><li>
Own the evaluation framework for ad quality, relevance, and user experience across the marketplace.</li><li>
Read an ArXiv paper on Monday. Have a prototype running on Friday.</li></ul><h3 class="jobSectionHeader">
What You Will Do</h3><ul><li>
Own the research and shipping of the models powering ad selection across Thrad's network.</li><li>
Move research to production end to end: hypothesis, training, evaluation, deployment, monitoring.</li><li>
Collaborate directly with the CTO and co-founders to translate research direction into working systems, often within the same day.</li><li>
Partner with the Data and Product teams to design and analyze live experiments on real traffic.</li><li>
Contribute to system architecture decisions as we scale from millions to billions of daily ad impressions.</li><li>
Communicate findings clearly to both technical and non-technical audiences across the team.</li></ul><h3 class="jobSectionHeader">
Who You Are</h3>
Must-haves<ul><li>
2 to 5 years of applied ML experience, ideally in ads, search, recommendations, ranking, or NLP.</li><li>
An advanced degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related field &mdash; or equivalent experience shipping production ML.</li><li>
Strong fundamentals in mathematical and statistical modeling. You know why your model works, not just that it does.</li><li>
Fluent in PyTorch, modern transformer architectures, and embedding-based retrieval.</li><li>
Strong Python, comfort with distributed training and inference.</li><li>
You have shipped ML to production at scale. Not just notebooks.</li><li>
You enjoy identifying and owning hard, open-ended problems. You form testable hypotheses and run them to ground.</li><li>
Based in San Francisco or willing to relocate. This is an in-person role at our SF HQ.</li></ul>
Nice-to-haves<ul><li>
Experience with RLHF, preference modeling, or LLM fine-tuning.</li><li>
Background in auction theory, bidding systems, real-time pricing, or yield optimization.</li><li>
Prior work at an ad-tech, search, recommendations, or marketplace company.</li><li>
Published research at NeurIPS, ICML, ACL, KDD, RecSys, or equivalent.</li><li>
Familiarity with ClickHouse or other column-oriented OLAP databases for analytical workloads.</li><li>
A relentless interest in the AI and LLM ecosystem and how advertising will evolve inside conversational interfaces.</li></ul><h3 class="jobSectionHeader">
Why Thrad</h3><ul><li>
First mover: We are defining a new category. Paid ads in AI is an inevitable market and we are building the infrastructure for it.</li><li>
Real traction: Fortune 500 clients, millions of daily impressions, and publisher partners across the AI web, all pre-seed.</li><li>
Research with teeth: Your work ships. Your models run in production against real traffic with real revenue on the line.</li><li>
Direct impact: Small founding team. Your decisions shape the models, the product, and the company.</li><li>
Ownership: Meaningful equity in a company at the intersection of two massive markets: AI and ad tech.</li><li>
Craft: A team that cares about shipping quality, not just quantity.</li></ul><h3 class="jobSectionHeader">
How to Apply</h3>
Send your CV and a brief note on what excites you about building at the intersection of AI and advertising. If you have published work, a GitHub, or models you have shipped that you are proud of, include them. We read every application.</div>

Applied Scientist

Google

<div>
 Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.
 
 
 Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
 
 San Francisco, CA, USA; Reston, VA, USA
 
 .
 
 Minimum qualifications:
 
 
 
 <ul>
 <li>
 Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
 </li>
 <li>
 3 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
 
 
 </li>
 </ul>
 
 Preferred qualifications:
 
 
 
 <ul>
 <li>
 3 years of experience developing and deploying machine learning and AI models in production settings.
 </li>
 <li>
 Experience at the intersection of security or fraud and ML.
 </li>
 <li>
 Experience applying a variety of unsupervised, semi-supervised, and supervised machine learning techniques, and the ability to turn big data into actionable intelligence.
 </li>
 <li>
 Experience building LLM-powered applications to automate the analysis and contextualization of complex data.
 </li>
 <li>
 Experience with the challenges in applying machine learning in a non-stationary and adversarial environment.
 </li>
 <li>
 Ability to evaluate, analyze, and improve machine learning models and LLM-driven systems.
 
 
 </li>
 </ul>
 
 About The Job
 
 
 
 The Google Cloud Gusto AI Data Science Research team develops innovative, data-driven solutions to today&rsquo;s most challenging cybersecurity problems. By leveraging data derived from Google's unparalleled view of the threat landscape, our cross-functional, applied research team experiments and delivers impactful findings for both our customers and the broader cybersecurity industry.
 
 
 We are looking for a Research Data Scientist to help us solve challenging cybersecurity problems and protect billions of customers by applying their expert knowledge of machine learning, statistics, and Generative AI. In this role, you will partner with subject matter experts on the front lines defending against advanced threat actors, iteratively develop new capabilities, and work closely with our engineering team to deploy and maintain them. Our team works on a wide variety of cybersecurity challenges including agentic security operations, threat intelligence contextualization, security-tuning LLMs, dark web threat detection, and more. We encourage sharing impactful learnings through publications at academic conferences and talks at industry venues.
 
 
 The US base salary range for this full-time position is $147,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
 
 
 Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Explore promising areas of future research at the intersection of cybersecurity and machine learning.
 </li>
 <li>
 Drive the research and development of new models and analytic products to solve cybersecurity problems.
 </li>
 <li>
 Develop models and analytics. Move from proof of concept to minimum viable product quickly and efficiently.
 </li>
 <li>
 Work closely with other engineering teams to develop scalable data pipelines, deploy models/analytics, and enact telemetry-driven model improvements over time.
 </li>
 <li>
 Communicate research results to stakeholders and the research community through documentation, white papers, peer-reviewed publications, and presentations.
 
 
 
 </li>
 </ul>
 Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .
</div>

Research Data Scientist, Cybersecurity, Google Cloud

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we&rsquo;re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain &mdash; and we&rsquo;re looking for talented people who want to help. 
 
You&rsquo;ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You&rsquo;ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you&rsquo;ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.
 
 
The Data Center Field Engineering Team is the engineering owner for the lifecycle of AWS data center mechanical and electrical infrastructure. This includes supporting new designs and innovations through data center end-of-life, with a focus on root cause analysis of failures, capacity and availability improvement, and optimization of the existing fleet. 
 
As a Senior Data Scientist on the Field Engineering Portfolio team, you will bring advanced analytical and machine learning capabilities to one of the most critical infrastructure organizations at AWS. You will develop scalable models and data-driven frameworks that measure, predict, and improve fleet performance &mdash; including data center availability, operational efficiency, and key performance indicators (KPIs) across the global AWS data center fleet. 
 
You are an exceptionally strong communicator, both written and verbally, capable of translating complex quantitative findings into clear recommendations for senior engineering and business leadership. You will work cross-functionally with Field Engineers, Operations, Commissioning, and Construction teams to ensure that data science solutions are grounded in operational reality and drive measurable impact. 
 
You will partner with engineering teams and program managers to define metrics, identify performance gaps, and build the analytical infrastructure needed to support strategic decisions at hyper-scale. You must be adept at operating in ambiguous, fast-moving environments where speed of insight can matter as much as analytical precision. 
 
The ideal candidate brings strong problem-solving skills, stakeholder communication skills, and the ability to balance technical rigor with delivery speed and customer impact. You will develop scalable analytical approaches to evaluate performance across the data center fleet to identify regional and site-specific insights, design and run experiments, and shape our development roadmap. You will build cross-functional support within the Data Center Community to assess business problems, define metrics, and support iterative scientific solutions that balance short-term delivery with long-term science roadmaps. 
 
Key job responsibilities 
<ul><li>Develop and maintain scalable models and analytical frameworks to measure and predict data center fleet performance, including availability, efficiency, and reliability KPIs across the global AWS infrastructure portfolio.</li><li>Apply advanced statistical and machine learning techniques to extract actionable insights from complex, large-scale operational datasets generated by data center systems (power, cooling, controls, etc.).</li><li>Partner with Field Engineers, Operations, and Portfolio Managers to identify high-impact opportunities for capacity and availability improvement, translating engineering domain knowledge into quantitative problem formulations.</li><li>Design and implement end-to-end data science workflows &mdash; from data acquisition and cleaning through model development, validation, and production deployment &mdash; enabling repeatable, scalable analysis.</li><li>Formalize assumptions about how data center systems are expected to perform and develop methods to systematically identify deviations, root causes, and high-ROI improvement opportunities.</li><li>Build self-service datasets, dashboards, and reporting mechanisms that provide Field Engineering leadership with real-time visibility into fleet health and portfolio performance.</li><li>Prepare narratives and data-driven recommendations for executive leadership that articulate decision points relative to fleet investment, risk trade-offs, and strategic priorities.</li><li>Collaborate with applied science, software engineering, and data engineering teams to ensure models integrate seamlessly with upstream and downstream systems.</li></ul> 
About the team 
Why AWS 
Amazon Web Services (AWS) is the world&rsquo;s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating &mdash; that&rsquo;s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. 
 
Diverse Experiences 
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn&rsquo;t followed a traditional path, or includes alternative experiences, don&rsquo;t let it stop you from applying. 
 
Work/Life Balance 
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there&rsquo;s nothing we can&rsquo;t achieve in the cloud. 
 
Inclusive Team Culture 
Here at AWS, it&rsquo;s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. 
 
Mentorship and Career Growth 
We&rsquo;re continuously raising our performance bar as we strive to become Earth&rsquo;s Best Employer. That&rsquo;s why you&rsquo;ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience</li><li>4+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience</li><li>Master's degree in a quantitative field such as Statistics, Mathematics, Data Science, Business Analytics, Economics, Engineering, or Computer Science; OR Bachelor's degree and 8+ years of professional experience in a quantitative role.</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience</li><li>Experience documenting modeling for technical and business leaders</li><li>Experience working with data engineers and business intelligence engineers collaboratively</li><li>Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue)</li><li>Experience developing operational processes and data insights</li><li>Experience with anomaly detection, predictive maintenance, or reliability modeling in industrial or infrastructure contexts.</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, CA, San Francisco - 183,000.00 - 247,600.00 USD annually 
USA, WA, Bellevue - 159,200.00 - 215,300.00 USD annually 
USA, WA, Seattle - 159,200.00 - 215,300.00 USD annually</div>

Sr. Data Scientist, Field Engineering

Genentech

<div><div><div>THE POSITION</div>
We advance science so that we all have more time with the people we love.
The Department of Cell and Tissue Genomics (CTG) is focused on developing and applying state of the art genomics technologies (e.g. single cell omics, high-content imaging, perturbations, etc) to solve key challenges in disease biology, target discovery, and translational medicine. We are seeking a highly talented, creative, and motivated computational biologist to analyze cutting-edge high-dimensional profiling and screening data, with a particular focus on high-content imaging, to decipher complex cellular circuits. The candidate will collaborate closely with members of the department to extract biological insights from diverse high dimensional data sets and support the development of new technologies, leveraging existing computational workflows and developing novel ones.
The Opportunity:
As an integral member of our dynamic team, you will be:<ul><li>
Analyzing high-content imaging data from novel technologies including optical pooled screens, spatial transcriptomics, and high-content perturbation screens, with the goal of extracting mechanistic insights into gene function and cellular phenotypes.</li><li>
Developing methods to analyze and interpret new types of perturbation data.</li><li>
Applying statistics and machine learning to investigate data and extract biological insights.</li><li>
Collaborating across diverse, cross-functional teams including experimentalists in CTG and the therapeutic areas and colleagues in the Computational Sciences Center of Excellence and the AI Biology &amp; Translation departments</li></ul>
Who You Are:<ul><li>
PhD in Computational Biology, Bioinformatics, Computer Science, or a related quantitative field. Alternatively, a PhD in molecular biology, immunology, bioengineering, etc. combined with a very strong record of data analysis, supported by publication in this area. Postdoctoral training is a plus.</li><li>
Strong publication record of biological discovery and/or methods development.</li><li>
Deep expertise in image analysis, including image processing, feature extraction, and morphological profiling. Familiarity with modern deep learning approaches (e.g., embeddings, foundation models) is a plus.</li><li>
Comfortable with the statistical principles behind current best practices in high-throughput data analysis.</li><li>
Fluent in Python and/or R.</li><li>
Excellent communication and presentation skills.</li><li>
Able to work successfully in cross-functional teams to collaboratively solve complex problems.</li><li>
Passionate about applying your analytical skills to understand health and disease.</li></ul>
Preferred Experience:<ul><li>
Experience with in situ data (FISH or ISS barcode calling).</li><li>
Familiarity with image analysis frameworks or libraries (e.g., CellProfiler).</li><li>
Experience with genomic data including single cell RNA-seq and perturbation screens is a plus.</li><li>
Experience with applying machine learning to high throughput datasets is a plus.</li></ul>
Relocation benefits are available for this posting.
The expected salary range for this position based on the primary location of California for Senior Scientist is $124,300- $230,900 and Principal Scientist is $143,200-$265,900. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
Benefits
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.</div>
<div><div>JOB FACTS
</div><div><div><ul><div>Job Sub Category
Research Informatics
</div><div>Schedule
Full time
</div><div>Job Type
Regular
</div><div>Posted Date
Apr 10th 2026
</div><div>Job ID
202604-108731</div></ul></div></div></div></div>

Computational Scientist 3 - Cell & Tissue Genomics

Connect Staffing Professional

<div><div>Founding Machine Learning Engineer - On-site - San Francisco, CA</div><div>
Location: San Francisco, CA</div><div>
Schedule: In office, five days per week</div><div>
A well-funded seed-stage AI company is building advanced agentic systems that automate complex workflows inside real enterprise software. The team is developing multimodal, vision-language, and reinforcement learning models that operate in high-stakes environments, beginning with healthcare. This is a founding-level opportunity to shape the technical direction of a company working at the frontier of applied AI.</div><div>
The engineering team is small, highly technical, and composed of builders from top research institutions and high-bar technology companies. This role is ideal for someone who wants to work on ambitious problems, ship production systems, and contribute to a platform with national-level impact.</div><div>
﻿</div><div>
Role Overview</div><div>
The Founding Machine Learning Engineer will design, train, and deploy models that power real-world autonomous agents. This includes multimodal perception, model reliability, reinforcement learning, evaluation systems, and the infrastructure required to operate AI agents safely inside enterprise environments. The work is deeply applied and requires strong engineering discipline, creativity, and comfort with first-principles problem solving.</div><div>
﻿</div><div>
What You Will Work On</div><ul>
<li>Develop and train multimodal and vision-language models for real enterprise workflows.</li>
<li>Build reinforcement learning systems that improve grounding, reliability, and recovery.</li>
<li>Design evaluation frameworks, regression detection, and error analysis pipelines.</li>
<li>Create synthetic data systems and tooling to improve model performance.</li>
<li>Collaborate with engineering to deploy model-powered systems into production.</li>
<li>Invent new infrastructure for agentic workflows and model-driven automation.</li>
<li>Contribute to a high-ownership environment where ideas move quickly into shipped products.</li>
</ul><div>﻿</div><div>
Ideal Background</div><ul>
<li>Strong experience in applied machine learning or AI engineering.</li>
<li>Hands-on experience training models, fine-tuning, or working with reinforcement learning.</li>
<li>Proficiency in Python and the ability to write production-quality code.</li>
<li>Experience with multimodal systems, perception models, or LLM-powered products.</li>
<li>Ability to design evaluation systems, analyze failure modes, and iterate quickly.</li>
<li>Comfort working in ambiguous, high-ownership environments.</li>
<li>Strong CS fundamentals and engineering rigor.</li>
</ul><div>﻿</div><div>
Preferred Qualifications</div><ul>
<li>Experience in computer vision or vision-language modeling.</li>
<li>Research publications or notable ML projects.</li>
<li>Background from a high-bar engineering organization or top academic program.</li>
<li>Strong mathematical foundation or competitive math experience.</li>
<li>Interest in entrepreneurship or building toward a future founding role.</li>
</ul><div>﻿</div><div>
Who Will Thrive Here</div><ul>
<li>Engineers who enjoy building applied AI systems that ship to production.</li>
<li>Individuals who think from first principles and can invent new approaches.</li>
<li>Builders who value reliability, safety, and disciplined engineering.</li>
<li>People who want to work on complex, meaningful problems with immediate impact.</li>
<li>Those who want to join a small, fast-moving team at a pivotal stage of growth.</li>
</ul><div>﻿</div><div>
Compensation and Benefits</div><ul>
<li>$200,000 to $250,000 base.</li>
<li>Top candidates may be considered up to $275,000.</li>
<li>Competitive equity included.</li>
<li>Highly attractive equity package at the founding team level.</li>
<li>Comprehensive medical, dental, and vision benefits. 401(k) program.</li>
<li>Significant opportunity for career growth and technical leadership.</li></ul></div><div></div>

Founding Machine Learning Engineer - San Francisco, CA (onsite)

Autopoiesis Sciences

<div>
 
 
 About The Role
 
 
 
 
 
 
 Autopoiesis Sciences is a San Francisco-based AI lab building systems that can do science autonomously. We are building the architectures, training methods, and reasoning systems that give AI the judgment to pursue discovery on its own, working the full stack from how scientific reasoning is distilled into models to how the research process itself can be made autonomous. We are backed by Informed Ventures, Alpaca VC, and VitalStage Ventures, Adam Grosser, Ally Warson, Hiro Mizushima, Mike Mahklow, Cross Atlantic Angels, and others.
 
 
 
 
 
 We are currently testing a newly trained autonomous AI system across a broad range of real-world tasks and need sharp, curious people to help us do it. Our AI reasons and plans autonomously, then relays instructions to a human operator who executes them across whatever interface the task requires. For the purposes of this research, it is the most direct way to study unconstrained autonomous behavior at the fidelity we need. You are the hands. The AI is the brain. Together, you close the loop.
 
 
 
 
 
 
 What You'll Be Doing
 
 
 
 
 
 <ul>
 <li>
 Receiving real-time instructions from an autonomous AI system and executing them accurately across whatever interface the task requires
 </li>
 <li>
 Logging outcomes, flagging ambiguities, and providing structured feedback that feeds directly into our research
 </li>
 <li>
 Working alongside ML researchers and engineers to help refine evaluation protocols as the project evolves
 </li>
 <li>
 Participating in debrief sessions where your observations shape how we understand and improve the system
 </li>
 <li>
 Occasionally supporting broader lab operations and research workflows as needed
 </li>
 </ul>
 
 
 
 
 
 Who We're Looking For
 
 
 
 
 
 <ul>
 <li>
 Curious about AI research and autonomous systems, whether through coursework, personal interest, or prior experience
 </li>
 <li>
 No degree required, but a background or active interest in STEM is a plus
 </li>
 <li>
 Comfortable following precise technical instructions quickly and accurately
 </li>
 <li>
 Detail-oriented enough to notice when something unexpected happens and articulate it clearly
 </li>
 <li>
 Interested in how autonomous AI systems actually behave outside of demos and papers
 </li>
 <li>
 Reliable, communicative, and able to work on-site at our SF office and warehouse space
 </li>
 </ul>
 
 
 
 
 
 Compensation and Benefits
 
 
 
 
 
 <ul>
 <li>
 Duration: 3 months with potential for extension
 </li>
 <li>
 Mentorship from researchers and engineers working on autonomous AI systems
 </li>
 <li>
 Collaborate in building a thoughtful, mission-driven team culture focused on autonomous scientific discovery
 </li>
 <li>
 Compensation packages are variable based on experience, expertise, and contribution potential. If your expectations fall outside our stated range, we encourage you to apply regardless. The range for this role is $25/hr-35/hr
 </li>
 </ul>
 
 
 
 
 
 Get To Know Us
 
 
 
 
 
 
 We're a dedicated team of scientists, researchers, and engineers who believe deeply in the transformative potential of our work. You'll work closely with our leadership team including Chief Executive Officer Joseph Reth (Attended University for CS at 14, former DARPA), Chief Business Officer Dr. Eike Gerhardt (University of T&uuml;bingen PhD, University of T&uuml;bingen staff), Chief Scientist Dr. Larry Callahan (University of Chicago PhD, former FDA, former NIH), and VP of Research Vincent Karpf (UC Berkeley).
 
 
 
 
 
 
 Application Process:
 
 Due to the high volume of automated applications, we only accept applications through LinkedIn as it helps us connect with genuine candidates. We have systems in place to detect automated submissions and strongly advise against using bots or automated tools in your application process. Please be human in your approach.
 
 
 
 
 
 
 Equal Opportunity:
 
 Autopoiesis Sciences, Inc. is an equal opportunity employer committed to diversity and inclusion. We welcome applications from all qualified candidates regardless of race, gender, age, religion, sexual orientation, or any other legally protected characteristics.
 
</div>

Human-AI Interface Research Assistant

Byte-Code SpA

<div>About Xaba
Xaba https://www.xaba.ai/ is at the forefront of AI-driven robotics automation, pioneering cutting-edge solutions to enhance industrial processes. Headquartered globally, with a team of collaborative scientists, engineers, and designers, Xaba operates in a remote-first and distributed environment. Join us in shaping the future of AI in robotics.
The Role
We are seeking an Applied Robotics Engineer to contribute to the development and deployment of our innovative products. As a key member of the Xaba team, you will play a pivotal role in shaping AI-powered robotics automation, while closely collaborating with the leadership team.
What you will do:<ul><li>
Collaborate with Xaba&rsquo;s cross-functional team of engineers to support the development, testing and deployment of AI models leveraging state-of-the-art DNN, CNN and GNN models to augment industrial robotics cognition, awareness and facilitate their program generation</li><li>
Conduct applied research in Robotics Welding, Inspection, Machining, and Assembling to gather data. This supports the development, training, auditing, and validation of physics-based AI models for robotics fabrication processes.</li><li>
Provide training and support for Xaba's products.</li><li>
Work closely with customers to understand their requirements and pain points, ensuring successful integration of AI-powered robotics software.</li></ul>
Technical Expertise:<ul><li>
Working experience with industrial robot manipulators: ABB, FANUC, UR, KUKA, etc.</li><li>
Demonstrated hands-on experience in designing, building and deploying robotic systems.</li><li>
Practical knowledge of robotic fabrication processes, including welding, machining, assembling, or inspection.</li><li>
Proficiency in both spoken and written English.</li></ul>
Nice to have:<ul><li>
Experience with SolidWorks, AutoCAD, CloudCompare.</li><li>
Familiarity with robotic hardware components, sensors, actuators, lasers and cameras.</li><li>
Knowledge of robotic programming languages: RAPID, URSCRIPT, KRL, etc.</li><li>
Solid understanding of key robotic aspects: forward and inverse kinematics, jacobians, collision detection, path-planning, control theory.</li></ul>
Education:<ul><li>
Background in Industrial Robotics, Automation, or degree in Mechanical Engineering.</li></ul>
Our location
While our team is remote-first and fully distributed, but for this position you must live in San Francisco, California.
Our Team and Perks<ul><li>
We are an open, collaborative, and supportive culture including skill shares and design critiques</li><li>
We believe that employees should be owners, which is why we provide stock option grants for full-time employees</li><li>
We believe in supporting the health and wellbeing of our team, which is why we offer a competitive health benefits package</li><li>
As a remote-first team, we believe in the importance of having the right set up, which is why we offer a home office budget</li><li>
Learning and development is critical to us, which is why we have a self-directed learning budget</li><li>
Stock option grants for full-time employees, promoting a sense of ownership.</li><li>
Competitive health benefits package.</li></ul>
Our Hiring Process<ul><li>
Discover: You discover the opportunity and apply to the role</li><li>
Talk: You take part in a 30-45 minute screening call with the Hiring Manager to chat about the role and the team.</li><li>
Deep dive: We have a 60 minute call to dive deep into your experience and the role.</li><li>
Meet your team: You have a video call with a few other Xaba team members.</li><li>
Offer: You receive an offer to join Xaba!</li></ul>
Accommodations and Accessibility
Inclusion and equity are the cornerstones of how we recruit, hire, and develop talent. We encourage applications from all candidates, especially those who identify as members of the BIPOC community, LGBTQ++ community, women, caregivers, immigrants, and people living with disabilities. We encourage candidates to include any accommodations you require in your application. We look forward to hearing from you.
About Byte-Code SpA
As Italian hiring partner, Byte-Code is helping Xaba finding the best candidates. You can apply through our website: https://bytecode.recruitee.com/ 
Technical Expertise:<ul><li>
Working experience with industrial robot manipulators: ABB, FANUC, UR, KUKA, etc.</li><li>
Demonstrated hands-on experience in designing, building and deploying robotic systems.</li><li>
Practical knowledge of robotic fabrication processes, including welding, machining, assembling, or inspection.</li><li>
Proficiency in both spoken and written English.</li></ul>
Nice to have:<ul><li>
Experience with SolidWorks, AutoCAD, CloudCompare.</li><li>
Familiarity with robotic hardware components, sensors, actuators, lasers and cameras.</li><li>
Knowledge of robotic programming languages: RAPID, URSCRIPT, KRL, etc.</li><li>
Solid understanding of key robotic aspects: forward and inverse kinematics, jacobians, collision detection, path-planning, control theory.</li></ul>
Education:<ul><li>
Background in Industrial Robotics, Automation, or degree in Mechanical Engineering.</li></ul></div>

Applied Robotics Engineer - San Francisco (CA)

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