Position

Are you a passionate Software Engineer looking to bring cutting-edge software solutions to drug discovery? Join our mission to bring novel therapeutics to patients and be at the forefront of driving innovation through technology. As a Software Engineer 2, you will leverage your expertise to develop and implement software solutions that drive our groundbreaking scientific initiatives.

About You

The ideal candidate for this role thrives at the intersection of software and scientific discovery. You are proficient with production-quality Python codebases and can contribute to, maintain, and extend these codebases in a robust and scalable way. At the same time, you understand the fast pace of scientific discovery, and can collaborate with scientists to clarify requirements, focus on result rather than implementation, and keep projects moving forward. You are a strong communicator, especially to non-engineers, as well as a strong team player, always ready to pitch in to help a colleague. You are a continual learner with a growth mindset, eager to learn from your colleagues and expand your talents in a supportive environment and are excited about our mission to bring drugs to patients.

What You’ll Do

• Work with scientists to understand data generated by early drug discovery projects and provide custom analyses and/or production software solutions to answer key questions about the data.
• Build, maintain, and extend tools that deliver machine-learning-based as well as classical algorithmic solutions to scientists.
• Contribute to the continuous improvement of software development processes, tools, and methodologies.
• Conduct thorough code reviews, promoting best practices and identifying opportunities for code optimization and enhancement.
• Collaborate with team members, sharing insights and fostering a culture of knowledge sharing and learning.
• Uphold ethical and data privacy standards in all software engineering activities.

Qualifications

• BS in Computer Science, Mathematics, Physics, Bioinformatics, Biophysics, or a related field, plus 2 years of relevant experience, or equivalent work experience.
• Demonstrated experience (2+ years) with Python; familiarity with scientific programming packages (pandas, numpy) and/or machine learning frameworks (TensorFlow) a plus.
• Undergraduate level biology knowledge required; experience manipulating and analyzing biologically relevant data sets strongly desired (e.g. sequencing data, cellular imaging data, etc).
• Introductory coursework on deep learning or other modern ML approaches, or equivalent work experience, a plus.
• Familiarity with basic software best practices (CI/CDD, unit testing, version control, etc.) highly preferred.
• Strong analytical and problem-solving skills, with the ability to think critically and creatively to overcome technical challenges.
• Effective communication skills to collaborate with diverse teams, both technical and non-technical, especially across disciplines.
• Demonstrated ability to thrive in a fast-paced, dynamic work environment.

At Eikon, employee compensation also includes bonus and equity compensation, in addition to several generous benefit programs, including:​

• 401k plan with company matching​
• Medical (premiums covered by Eikon at 95%), dental and vision insurance (premiums covered by Eikon at 100%)​
• Mental health and wellness benefits​
• Weeklong summer and winter holiday shutdowns​
• Generous paid time off and holiday policies​
• Life/AD&D Insurance (premiums covered by Eikon at 100%) and optional supplemental employee-paid life/AD&D policies ​
• Enhanced parental leave benefit​
• Daily subsidized lunch program when on-site​

The expected salary range for this role is $135,000 to $147,250 depending on skills, competency, and the market demand for your expertise.

10x Genomics is seeking a detail-oriented individual to join our Quality Control team. This role will bridge the gap between traditional laboratory quality control and modern data automation. As a QC Associate, you will be responsible for testing and inspection, as well as supporting automation of data workflows and analysis. If you have strong laboratory fundamentals and practical background in python or other scripting experience, you would be a great fit for the team.

Key Responsibilities

• Laboratory Execution: Follow ISO standard to conduct QC testing on raw materials, intermediates, and finished products using metrology check, PCR, NGS, and HPLC.
• Process Automation: Use Python and AI tools (Claude) to help write and maintain scripts that streamline QC inspections, data collection, and analysis.
• Quality Assurance: Initiate and follow up on nonconformance, support new product launches and investigations.
• Data Management Work with the team to identify metrics, and help build and maintain real-time data visualizations using Streamlit and Retool. 

Minimum Qualifications

• Major/Education: B.S. or M.S. in Biological Engineering, Bioinformatics, Data Science, or a related Life Science discipline. 
• Laboratory Experience: 1 year of experience in a manufacturing or QC environment (NGS or PCR experience preferred). 
• Python: Essential  for building Streamlit apps, managing Claude/AI API integrations.

Preferred Skills

• Experience with Git/GitHub for version control of scripts.
• SQL: Useful for manipulating and extracting data in Snowflake
• Snowflake: Knowledge and experience with cloud data warehousing and data architecture.
• Experience building dashboards for data automation/monitoring.
• Basic knowledge of Statistics for quality control. 
• Prompt Engineering: Capability to use Claude for complex reasoning and workflow automation.
• Prior experience in a manufacturing setting utilizing production control tools like ERP or LIMS.

#LI-onsite #LI-ES1

About the Role
We are looking for an AI Scientist to join our team at the intersection of machine learning and single-cell biology. This role will focus on developing and applying foundation models to large-scale perturb-seq and single-cell datasets to uncover new biological mechanisms and therapeutic opportunities. You will help design scalable ML architectures that can extract insight from high-dimensional perturbation data and integrate across multi-omic modalities.

Key Responsibilities

• Design, train, and refine foundation models tailored to perturb-seq and other single-cell datasets.
  Build pipelines for preprocessing, normalization, and integration of large-scale single-cell and perturbation data.
• Apply ML/AI approaches to model cellular responses to perturbations and identify causal biological insights.
• Collaborate with experimental biologists to align computational methods with experimental design and discovery goals.
• Develop multimodal integration approaches across transcriptomic, epigenomic, and proteomic single-cell readouts.
• Publish methods and results in top scientific journals and present at conferences.
  
  

Qualifications

• PhD or equivalent in Computational Biology, Computer Science, Bioinformatics, or related discipline.
• Strong expertise in single-cell data analysis, particularly perturb-seq 
• Hands-on experience with foundation models or large-scale self-supervised learning (e.g., transformers, variational autoencoders).
• Strong coding skills in Python, ML frameworks (PyTorch/TensorFlow), and single-cell analysis tools (Scanpy, Seurat).
• Experience in developing scalable ML methods for large biological datasets.
  
  

Preferred

• Background in causal inference, generative models, or representation learning for biological systems.
• Familiarity with multi-omics integration and cross-modal foundation models.
• Track record of impactful publications in computational biology, machine learning, or related fields.

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $150,000 - $240,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

The impact you'll be contributing to Moloco:
Product Analytics Data Science (PDS) is the data science team that works closely with the R&D team on our core Ads product. As a Data Scientist II, you will drive performance improvement in our product through a deep understanding of the ads ecosystem (supply, demand, bidding, ML) and customer needs, and provide the data driven insight and scientific solutions.

Here’s what you’ll be working on:

Our team is responsible for:

• Conducting deep-dive analysis to influence R&D decisions and strategies: analyzing large datasets with queries and scripts, extracting valuable signals out of noise, and producing actionable insights into how we could improve Moloco’s complex ML and bidding system to drive outcomes for customers. 
• Building the right metrics to measure campaign health: improving campaign performance monitoring by establishing the right metric framework, and understanding cause-and-effect relationships across drivers
• Evaluating ads system health: understanding changes and drivers of our complex systems, and diagnosing issues through a set of input/output metrics of each component.

Basic Qualifications

• Distinctive problem-solving skills, ability to articulate product questions, pulling data from large datasets and using statistics to arrive at a recommendation; ability to manage multiple projects at the same time. 
• Proven ability to own complex projects end-to-end, even when you have to get creative: you do more than completing delegated tasks and always pay attention to detail to translate analysis results into business recommendations. 
• Provide strategic thought partnership to cross-functional teams, leveraging data-driven insights to influence and guide product decisions, roadmap prioritization, and overall business strategy.
• Excellent verbal and written communication skills, with ability to present information and analysis results effectively.
• Statistics: strong knowledge and experience in experimental design, hypothesis testing, and various statistical analysis techniques such as regression or linear models.
• Programming: experience with Python, R or other scripting language, and database language (e.g. SQL) or data manipulation (e.g. Pandas, Dplyr).
• Ability to build positive relationships within the DS team and with Product Management, Engineering stakeholders ;work effectively with cross-functional partners in a global company.
• 3+ years of work experience (industry or postgraduate) in data science related fields or an advanced degree such as Master’s or PhD in a quantitative discipline with 4+ years of experience.
• Bachelor’s, Master’s and/or PhD in a quantitative discipline (e.g. Statistics, Operations Research, Bioinformatics, Economics, Computational Biology, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering).

Profluent is seeking a Principal Infrastructure & Security Engineer to serve as the primary owner of Profluent’s security posture across scientific systems, lab automation environments, cloud and business infrastructure, endpoints, identity systems, and core operational workflows.

This person will be accountable for the design, implementation, operation, and continuous improvement of the technical controls, security standards, and operating practices that protect Profluent’s systems and data. This includes security architecture, access controls, hardening, monitoring, incident readiness, vendor and customer security assurance, and the systems and evidence required to achieve and maintain compliance commitments.

This is not a narrow compliance-only or infrastructure-only role. It is a broad ownership role for security across Profluent’s environments, with close partnership across Operations, Machine Learning, Bioinformatics, and Lab Automation.

Responsibilities

• Own Profluent’s overall security and compliance posture across company systems, scientific computing, lab automation, endpoints, identity, SaaS, cloud infrastructure, networking, and data-handling workflows, and be accountable for the ongoing maturity of security controls and practices across those environments
• Lead the implementation and operational maturity work required for Profluent to achieve and maintain SOC 2 and related compliance certification requirements, including control operation, evidence collection, monitoring, and repeatable processes
• Serve as the primary owner for security and compliance readiness across company systems, ensuring that Profluent can meet ongoing audit, certification, and customer assurance requirements over time 
• Own the translation of customer agreements, internal policies, and compliance requirements into concrete technical and operational controls
• Standardize and harden bioinformatics, lab informatics, and machine learning environments to align with security, reliability, and compliance requirements
• Define and drive adoption of secure baseline configurations, access controls, logging, backup practices, patching standards, and change management processes
• Own and evolve how Profluent approaches security more broadly, identifying gaps, prioritizing risks, and driving improvements beyond minimum compliance scope
• Drive standardization of Windows-based lab automation environments, balancing security, uptime, vendor constraints, and usability in laboratory settings
• Collaborate with stakeholders to document controls, system boundaries, standard operating procedures, and technical evidence needed for audits, certification efforts, and customer reviews
• Support vendor and platform evaluations related to security, observability, endpoint management, and infrastructure operations
• Improve identity, access, and account lifecycle management across company systems, including onboarding, offboarding, least-privilege access, and periodic access review support 
• Monitor key systems and respond to operational issues with an emphasis on root-cause analysis and durable remediation
• Maintain asset, system, and environment documentation so that critical processes are auditable, supportable, and repeatable

Qualifications

• Experience operating with broad ownership across infrastructure, security, and compliance in regulated, audit-conscious, or security-sensitive environments
• Experience serving as the most senior or primary security owner in a startup or scaling environment, even without a large dedicated security team
• Breadth across infrastructure security, corporate security, IAM, endpoint management, logging and monitoring, vulnerability reduction, incident response, vendor risk, and compliance
• Demonstrated ability to take ownership in ambiguous environments and set direction, not just execute within a narrowly defined specialty
• Familiarity with Windows-based lab automation systems and the realities of instrument-connected or vendor-managed environments
• Experience implementing or operating against security and compliance frameworks such as SOC 2, ISO 27001, NIST CSF, or similar
• Strong understanding of identity and access management, SSO, MFA, endpoint management, logging, patching, vulnerability reduction, and system hardening
• Ability to translate compliance and contractual data-handling requirements into concrete technical and operational controls
• Strong documentation skills, with the ability to create policies, procedures, standards, and technical runbooks that others can follow
• Experience preparing organizations for, achieving, or maintaining external compliance certifications or audit readiness
• Experience with infrastructure as code and/or configuration management tools such as Terraform, Ansible, or equivalent
• Experience administering Windows environments, preferably including systems used in laboratory, automation, manufacturing, or instrument-connected settings

Preferences (but not required)

• Familiarity with audit evidence preparation, control testing, and coordination with external auditors
• Familiarity with networking fundamentals including firewalls, routing, VLANs, NAT, VPNs, and secure remote access
• Experience influencing cross-functional teams and improving organizations mature security practices without relying on rigid bureaucracy

What We Offer

• High-growth opportunity with meaningful impact on the future of protein design
• Competitive compensation package with equity participation
• 401(k) with a strong employer match
• Comprehensive benefits including health/dental/vision insurance
• Generous PTO policy and commitment to work-life balance
• Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Work Authorization Requirement

Applicants must have ongoing work authorization in the United States that does not require employer sponsorship. Sponsorship will not be provided now or at any time in the future for this position.

Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

The Opportunity:

This role represents a unique opportunity to serve as a senior scientific and strategic leader within Cancer Immunology, with primary responsibility for driving the discovery and advancement of novel immuno-oncology targets and therapeutic modalities. We are seeking an accomplished leader who combines deep scientific expertise with strong people leadership to shape strategy, guide portfolio decisions, and advance high-impact discovery programs.

The successful candidate will lead a multidisciplinary team to progress innovative immuno-oncology programs from early discovery through Development Candidate nomination, while providing senior oversight of scientific integration across Discovery and Translational Cancer Immunology. This role reports to the Vice President and Head of Cancer Immunology and partners closely with Research and Development leadership to support portfolio prioritization and governance. Key aspects of the role include:

• Discovery Program Leadership & Protfolio Oversight: Provide executive-level leadership of Cancer Immunology discovery programs from project qualification through Development Candidate nomination. Drive the identification and validation of novel immuno-oncology targets, ensuring seamless progression of programs into Translational Cancer Immunology.

• Scientific Strategy & Platform Leadership: Define and evolve the scientific vision and long-term strategy for Cancer Immunology discovery. Provide senior oversight of the development and optimization of experimental platforms, including in vitro and in vivo models, phenotypic screening, and advanced assay toolkits. Champion the exploration and implementation of new therapeutic modalities, such as TCEs, ADCs, and bispecifics.

• Scientific Integration & Operational Excellence: Provide senior oversight of scientific integration across Discovery and Translational Cancer Immunology, ensuring operational rigor, platform support, and alignment of resources. Leverage enabling functions and data-driven insights to enhance experimental design, reproducibility, and program execution. Promote the development and deployment of modern data systems and analytics to advance scientific and operational excellence, enabling the establishment of a digitally empowered Cancer Immunology team within the broader organization.

• Cross-functional Collaboration: Act as a key partner to Research Leadership to support advancement of programs from early discovery into the clinical development portfolio. Foster collaboration across multidisciplinary teams to ensure that discovery efforts, platform capabilities including data platforms, and translational priorities are coordinated and integrated.

• Team Leadership & Mentorship: Lead, mentor, and inspire a multidisciplinary team of PhD and non-PhD scientists. Cultivate a culture of scientific excellence, innovation, and collaboration.

• External Engagement: Spearhead collaborations with academic partners and external organizations. Partner with key stakeholders to define publication strategies and support advancement of the company’s scientific reputation in the field.

Required Skills, Experience, and Education:

• Education & Scientific Expertise: Ph.D. in immunology, cancer biology, or a related discipline, with deep expertise in tumor immunology, immune-evasive oncogenic signaling pathways, and/or immunotherapy. Demonstrated track record of excellence in research, evidenced by high-impact publications.

• Industry Experience: 20+ years of post-PhD experience in biomedical research and oncology drug discovery, including substantial experience in biotech or pharmaceutical settings. Demonstrated leadership in oncology drug discovery and development, including experience with antibody-directed therapies such as T cell engagers, ADCs, or bispecific antibodies, is required. Experience setting early discovery strategy is highly desirable.

• Senior Leadership & Organizational Impact: Proven ability to lead complex, multidisciplinary organizations and influence across functions and levels. Demonstrated experience in portfolio decision-making, program governance, and developing scientific leaders.

• Strategic & Analytical Thinking: Enterprise-level strategic thinker capable of prioritizing initiatives, anticipating challenges, and executing effectively in a dynamic, high-energy environment. Rigorous, quantitative, and detail-oriented experimentalist.

• Collaboration & Communication: Thrives in a collaborative, interdisciplinary team setting. Excellent written and verbal communication skills, with the ability to influence and align diverse stakeholders.

Preferred Skills:

• Experience with chemistry-based therapies, including small molecules or ADC payloads.

• Familiarity with bioinformatics-driven discovery and integrating computational insights into experimental design.

• Demonstrated proficiency with modern data platforms, machine learning approaches, and advanced analytics to support Cancer Immunology research and decision-making.

• Prior experience as a Program Team Leader, with a track record of driving cross-functional strategy and execution across discovery and development stages.

 #LI-Hybrid  #LI-LN1

We’re looking for a Senior Software Engineer to help design, build, and scale Profluent’s data platform. This platform houses data from protein engineering campaigns, including protein designs, experimental results, partner datasets, analytical outputs, and model-ready training data. It enables rapid machine learning, biological discovery, and secure collaboration across internal and external programs.

This role is ideal for an engineer who enjoys building robust data systems: secure ingestion pipelines, well-structured warehouses, reliable data models, access controls, auditability, and infrastructure that makes complex scientific data usable at scale. You will work closely with ML, bioinformatics, and program teams to ensure Profluent’s data is organized, governed, accessible, and protected.

Responsibilities

• Design, build, and maintain scalable data infrastructure for protein engineering campaigns, including ingestion, transformation, validation, storage, and retrieval of large scientific datasets
• Develop secure data pipelines for internal and partner-generated data, with strong attention to access control, data siloing, provenance, auditability, and compliance with data use restrictions
• Own core components of Profluent’s data warehouse and data platform, using Python, GCP, PostgreSQL, BigQuery, and related cloud-native technologies
• Build systems that transform raw experimental, computational, and partner data into structured, reliable, analysis-ready and model-ready datasets
• Establish best practices for data modeling, metadata management, data quality checks, schema evolution, versioning, and documentation
• Collaborate with ML engineers, computational biologists, data scientists, and program stakeholders to understand data requirements and translate them into scalable technical systems
• Improve engineering quality through thoughtful system design, code review, testing, CI/CD, observability, and maintainable development workflows
• Contribute to architectural decisions for how Profluent stores, secures, organizes, and uses data across programs and partnerships

Qualifications

• 5+ years of software engineering, data engineering, or data platform experience
• Strong proficiency in Python and modern software development practices, including git, testing, code review, CI/CD, and production deployment
• Experience designing and operating production data pipelines, data warehouses, and data models at scale
• Hands-on experience with cloud platforms, preferably GCP, and technologies such as BigQuery, PostgreSQL, object storage, workflow orchestration, and containerized services
• Strong understanding of data security, access control, data partitioning or siloing, audit logging, and managing sensitive or restricted datasets
• Experience working with complex, heterogeneous datasets and building systems that make them reliable, discoverable, and usable
• Ability to work independently, make sound technical decisions, and drive projects from ambiguous requirements to production systems
• BS, MS, or PhD in Computer Science, Engineering, Data Science, Bioinformatics, or a related technical field, or equivalent practical experience

Preferences (but not required)

• Experience with scientific, biological, clinical, genomic, laboratory, or high-throughput experimental data
• Experience managing external partner, customer, or restricted-access datasets
• Familiarity with data governance, lineage, metadata systems, schema registries, or data catalogs
• Experience with research data systems, LIMS, ELNs, Benchling, or adjacent scientific platforms
• Background working with ML, data science, computational biology, or cross-disciplinary technical teams
• Interest in learning biology, gene editing, protein design, or machine learning concepts

What We Offer

• High-growth opportunity with meaningful impact on the future of protein design
• Competitive compensation package with equity participation
• 401(k) with a strong employer match
• Comprehensive benefits including health/dental/vision insurance
• Generous PTO policy and commitment to work-life balance
• Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Work Authorization Requirement

Applicants must have ongoing work authorization in the United States that does not require employer sponsorship. Sponsorship will not be provided now or at any time in the future for this position.

Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

We’re looking for a hands-on engineering manager to lead Profluent’s Lab Informatics Platform team. This team builds the systems scientists use to design experiments, track samples, capture assay data, integrate with Benchling and lab automation, and make experimental data usable for analysis and machine learning.

The ideal candidate is both an experienced people manager and a strong technical lead. You’ll formally manage and mentor a small team while remaining deeply involved in architecture, data modeling, database design, and technical execution. You’ll work closely with wet-lab scientists, automation engineers, data scientists, and ML experts to build practical, scientist-facing tools that make complex experimental workflows scalable, traceable, and actionable.

Responsibilities 

• Lead, mentor, and grow a software engineering team focused on lab informatics systems, scientific data infrastructure, and scientist-facing applications
• Architect and deliver the roadmap for systems that support sample tracking, assay data capture, Benchling integration, lab automation, experimental metadata, and analysis workflows
• Design robust data models for protein engineering and gene editing experiments, including constructs, samples, reagents, cell systems, assay results, metadata, and experimental lineage across mammalian and bacterial workflows
• Partner closely with scientists to translate complex laboratory requirements into scalable software solutions that accelerate Profluent’s design-build-test-learn cycle
• Build and maintain backend systems, APIs, databases, data pipelines, and web applications using technologies such as Python, Django, PostgreSQL, BigQuery, GCP, and modern development workflows
• Establish strong engineering practices across architecture, code review, testing, CI/CD, documentation, and agile delivery

Qualifications 

• 7+ years of software engineering experience, including at least 2 years managing or leading engineers
• BS, MS, or PhD in Computer Science, Bioinformatics, Computational Biology, Engineering, or a related field, or equivalent experience
• Strong technical leadership skills, with a track record of architecting and delivering production-quality software systems
• Proficiency with Python, backend development, databases, APIs, and modern software engineering workflows
• Experience building lab informatics systems, scientific data platforms, LIMS/ELN integrations, research software, or scientist-facing applications
• Experience with data modeling and database design for complex scientific, operational, or experimental workflows
• Demonstrated ability to work closely with scientists and translate ambiguous laboratory workflows into reliable software systems

Preferences (but not required)

• Experience with Benchling, lab automation, instrument data ingestion, sample tracking, or high-throughput experimental data
• Experience with data generated from mammalian or bacterial cell systems, gene editing, protein engineering, or related biological workflows
• Frontend web development experience and interest in building intuitive scientist-facing user interfaces

What We Offer

• High-growth opportunity with meaningful impact on the future of protein design
• Competitive compensation package with equity participation
• 401(k) with a strong employer match
• Comprehensive benefits including health/dental/vision insurance
• Generous PTO policy and commitment to work-life balance
• Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Work Authorization Requirement

Applicants must have ongoing work authorization in the United States that does not require employer sponsorship. Sponsorship will not be provided now or at any time in the future for this position.

Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

About this opportunity:

At Freenome, we are seeking a Senior Software Engineer II to join our innovative Engineering team. The ideal candidate is an experienced backend engineer with a strong background in developing scalable and reliable software solutions. You will play a crucial role in designing, building, and maintaining backend services that support our mission to detect cancer early. This position requires a collaborative mindset, as you will work closely with an interdisciplinary team of engineers, scientists, and product managers to deliver high-quality software solutions. You are passionate about software development best practices and will have a significant impact on the continued growth of an organization dedicated to changing the entire landscape of cancer.

The role reports to our engineering management team. This role will be a Remote role. 

What you’ll do:

• Design, develop, and deploy reliable, maintainable, scalable, and fault-tolerant backend services that power both our internal and external systems.
• Collaborate with interdisciplinary teams, including scientists, product managers, and other engineers, to solve complex problems and deliver high-quality software solutions.
• Mentor and guide junior engineers, fostering their growth and enhancing the team's technical expertise.
• Lead code and design reviews, champion engineering best practices and promote a culture of quality and collaboration.
• Contribute to the development of data infrastructure for machine learning applications, ensuring efficient data processing and integration.
• Drive the implementation of engineering hygiene practices, ensuring the reliability and maintainability of our systems.
• Advocate for and implement innovative software development methodologies and tools to improve team efficiency and product quality.
  

Must haves:

• Bachelor of Science in Computer Science, Engineering, or related field or equivalent training, fellowship, and/or work experience.
• At least 8 years of experience as part of a software development team successfully shipping software products, including leading projects from end-to-end and mentoring others.
• Proficiency in Python and experience with backend development in a team production environment.
• Strong experience with containerization and orchestration technologies such as Docker and Kubernetes.
• Familiarity with cloud platforms like AWS, Azure, or Google Cloud Platform.
• Proven experience in designing and implementing scalable backend systems, with a focus on reliability and performance.
• Excellent written and verbal communication skills, with a mindful and transparent approach to collaboration.
  

Nice to haves:

• Understanding of statistical and machine learning methods, with practical experience in applying them to real-world problems.
• Expertise in developing ETL or data pipelines that run at scale, utilizing common workflow management systems like Flyte, Airflow, or similar.
• Domain-specific experience in computational biology, genomics, bioinformatics, or a related field.
• Experience working in an FDA regulated environment, with a strong understanding of compliance requirements and best practices.
  

Benefits and additional information:

The US target range of our base salary for new hires is $161,925 - $227,325. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.  Please note that individual total compensation for this position will be determined at the Company’s sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ freenome.com/job-openings/ for additional company information.  

Freenome is proud to be an equal-opportunity employer, and we value diversity. Freenome does not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

Applicants have rights under Federal Employment Laws.  

• Family & Medical Leave Act (FMLA)
• Equal Employment Opportunity (EEO)
• Employee Polygraph Protection Act (EPPA)

#LI-REMOTE

Position Summary

Alamar Biosciences is seeking a Senior Scientist, Technology Development to innovate technologies and products based on our proprietary NULISA™ platform, which enables highly sensitive, quantitative, and multiplexed biomarker measurements using qPCR and/or NGS readouts. The ideal candidate will have a strong background in assay development, immunoassays, molecular biology, biochemistry, and data analysis, along with a passion for translating novel technologies into robust products. This role will involve close collaboration with product development, bioinformatics, manufacturing, and software teams. The fast-paced nature of this position requires excellent attention to detail, strong communication skills, the ability to multitask and work independently, and flexibility with evolving priorities and schedules. This is a full-time, onsite role based in Fremont.

Duties and Responsibilities

• Lead development of novel multiplex immunoassays utilizing Alamar’s proprietary NULISA technology
• Design, execute, and troubleshoot experiments to optimize assay performance
• Perform rigorous data analysis and interpretation to guide technology and assay development decisions
• Identify key variables impacting assay sensitivity, specificity, robustness, and reproducibility, and drive systematic optimization
• Participate and present data in technical discussions and project meetings.
• Collaborate closely with bioinformatics, product development, manufacturing, engineering, and software teams to enable end-to-end workflow integration
• Support assay transfer, automation, and system-level integration onto Alamar’s proprietary instrument platform
• Mentor and provide technical guidance to junior scientists and contribute to team-level scientific excellence
• Contribute to building and maintaining a strong, collaborative team culture

Qualifications

• PhD with 5+ years of experience in Molecular Biology, Biochemistry or a related field
• Demonstrated experience in single-plex and multiplex immunoassay development
• Hands-on experience with reagent optimization for immunoassays and qPCR/NGS
• Experience with qPCR /NGS assay optimization
• Ability to maintain cooperative working relationships with a broad range of stakeholders, including team members and cross functional teams
• Strong organizational skills with the ability to set priorities and balance laboratory and cross-functional needs
• Highly detail-oriented with a strong focus on quality
• Consistent, positive, and can-do attitude

Preferred Qualifications

• Preferably PhD with 5+ years of industry experience, MS with 8+ years of industry experience or BS with 10+ years of industry experience.
• Experience with immunoassay technologies such as NULISA, SIMOA, PEA, or similar technologies
• Experience with optimizing multi-color qPCR or NGS assays
• Experience with calibration curve–based sample quantification
• Prior experience leading or managing direct reports, including mentoring junior scientists or associates
• Familiarity with data and record management platforms such as Benchling or SciNote
• Experience with reagent and inventory management
• Excellent written and verbal communication skills, with the ability to present technical information to diverse audiences

The base salary range for this full-time position is $140,000 - $165,000 + bonus + equity + benefits. Our salary ranges are determined by work location, job-related skills, experience, and relevant education or training. The ranges displayed on each job posting reflect the minimum and maximum target for new hire salaries but are subject to change if the leveling of the role is adjusted. Your recruiter can share more about the specific salary range during the hiring process. 

Position Summary

We are seeking a highly motivated Scientist I to join the Content Development team. In this role, you will support the development, optimization, and characterization of NULISA-based immunoassays and multiplex proteomic panels across diverse disease areas. You will work closely with cross-functional partners including R&D, Manufacturing, Bioinformatics, and related teams to ensure robust assay performance and high-quality deliverables.

The ideal candidate will bring strong hands-on immunoassay execution skills, a solid foundation in data analysis, and the ability to contribute effectively in a fast-paced, collaborative product development environment.

Duties and Responsibilities

• Design, development, and optimization of multiplex proteomic panels across various disease areas to support biomarker discovery, validation, and translational research.
• Develop and optimize the high-plex panels to ensure high specificity, sensitivity, and reproducibility of the product.
• Perform multivariate analysis to optimize assay performance, minimize cross-reactivity and mitigate matrix effect.
• Troubleshoot technical challenges via root-cause analysis and implement corrective strategies.
• Develop and maintain critical documentation, including SOPs, PRDs, and assay transfer documents to support product development and regulatory compliance.
• Collaborate cross-functionally to advance projects and contribute to strategic discussions.

Qualifications

• Ph.D. in Biochemistry, Molecular Biology, or a related discipline with 0–3 years of relevant industry experience; M.S. with 2–5 years of experience will also be considered.
• Hands-on experience with immunoassays or multiplex assay platforms (e.g., Luminex, MSD, Olink, Ella, SomaLogic, etc.).
• Familiarity with molecular biology methods (e.g., qPCR, ddPCR, or NGS) is a plus.
• Strong problem-solving and analytical skills with attention to detail in experimental execution.
• Ability to manage time effectively, work collaboratively, and adapt in a fast-paced environment.
• Strong communication skills, including data presentation and technical documentation.
• Knowledge of biomarker research, assay validation, or clinical sample testing is desirable.

The base salary range for this full-time position is $120,000 - $140,000 + bonus + equity + benefits. Our salary ranges are determined by work location, job-related skills, experience, and relevant education or training. The ranges displayed on each job posting reflect the minimum and maximum target for new hire salaries but are subject to change if the leveling of the role is adjusted. Your recruiter can share more about the specific salary range during the hiring process. 

About The Role

10x Genomics is establishing a diagnostics effort, translating our leading single-cell and spatial assay technologies into impactful clinical applications. We are seeking a Scientist II to join the clinical bioinformatics team. The ideal candidate excels at distilling complex biological questions into actionable computational strategies, implementing computational/statistical methods and applying them to large-scale single-cell or spatial transcriptomics datasets to derive clinically meaningful insights.

The role requires a biology-first mindset, proficiency with large-scale bioinformatics analyses, strong scientific acumen and statistical rigor. The successful candidate will have an opportunity to work with some of the largest biomedical datasets assayed using cutting-edge 10x Genomics technologies, deriving clinical insights that power the next generation of clinical diagnostics.

What You Will Be Doing:

• Implement rigorous computational/statistical methods for single-cell and spatial transcriptomics data analysis.
• Derive actionable insights from clinical/translational single-cell or in-situ spatial datasets.
• Design, implement and validate biomarkers for diagnostic applications.
• Implement and maintain bioinformatics pipelines for reproducible, large-scale data processing.
• Process and analyze single-cell or in-situ spatial transcriptomics datasets spanning hundreds to thousands of samples.

To Be Successful, You Will Need:

• Ph.D. in bioinformatics, computational biology, genomics or a related discipline with extensive hands-on experience in single-cell NGS data analysis.
• A minimum of 2 years of industry experience post Ph.D.
• Experience analyzing large-scale single-cell or spatial transcriptomics datasets to derive biologically meaningful insights and/or diagnostic biomarkers.
• In-depth understanding of the assumptions, limitations and caveats of statistical methods.
• Experience developing and optimizing high-performance, scalable code.
• Proficiency working in a Linux environment.
• Goal-oriented, self-motivated and an independent problem solver.
• Meticulous attention to detail and a conscientious work ethic.

Preferred Skills

• Hands-on experience with 10x Genomics single-cell and in-situ transcriptomics technologies is a strong preference
• Hands-on research experience in cancer or autoimmune diseases is a strong preference
• Knowledge of clinical genomics, biomarker discovery and diagnostics
• Development of statistical models and algorithms for single-cell or spatial transcriptomics data
• Application of machine learning, particularly in the context of genomics
• Proficiency with workflow orchestration frameworks such as Snakemake, Nextflow or Martian
• Programming best practices including data analysis reproducibility, version control, design patterns, testing, debugging and profiling
• Track record of writing production-level code or maintaining published software packages
• High-throughput computing infrastructure such as HPCs or cloud computing

The Opportunity:

We are seeking a Principal Machine Learning Scientist to lead the development of advanced machine learning approaches that accelerate small-molecule drug discovery. This role sits at the intersection of data science, chemistry, and biology, transforming complex scientific datasets into predictive models that guide target discovery, compound design, and translational hypotheses.

Working closely with experimental scientists, the Principal ML Scientist will develop cutting-edge modeling approaches that integrate chemical, biological, and phenotypic data. The successful candidate will play a key role in advancing a data-driven discovery strategy by designing predictive models, deploying innovative algorithms, and translating insights into actionable decisions that improve the speed and success of the discovery of medicines for patients with RAS-driven cancers.

Key responsibilities include:

Scientific Leadership:

• Define and lead machine learning strategies that accelerate early-stage drug discovery.

• Identify opportunities where AI and advanced analytics can meaningfully improve scientific decision-making.

• Drive the adoption of innovative modeling approaches within multidisciplinary discovery teams.

Model Development:

• Develop predictive models for:

  • Compound activity, selectivity, ADME/Tox, and developability properties.

  • Target engagement, mechanism-of-action, and phenotypic datasets.

Apply modern ML techniques such as:

• Graph neural networks.

• Deep learning for molecular representation.

• Generative chemistry models.

• Active learning frameworks for experimental design.

Cross-Functional Collaboration:

• Partner with medicinal chemists to guide compound design and optimization.

• Work with biologists to interpret complex experimental datasets and generate mechanistic hypotheses.

• Collaborate with data scientists and engineers and ML engineers to deploy models into scalable discovery workflows.

Data Integration:

• Integrate heterogeneous datasets including:

• Chemical structure and screening data.

• Imaging and phenotypic screening data.

• Structural biology and molecular simulation outputs.

Required Skills, Experience and Education:

• PhD in machine learning, computational chemistry, computational biology, computer science, or a related quantitative discipline.

• 8+ years experience applying machine learning or advanced analytics to scientific problems.

• Demonstrated experience working with chemical or biological datasets in drug discovery or related domains.

• Strong expertise in:

  • Python-based ML ecosystems (PyTorch, TensorFlow, scikit-learn).

  • Data analysis and scientific computing (NumPy, Pandas).

  • Deep learning and representation learning techniques.

• Strong understanding of early-stage drug discovery workflows.

• Ability to translate biological or chemical questions into computational frameworks and predictive models.

• Proven ability to communicate complex computational insights to.

• Passion for scientific innovation and a relentless commitment to improving patient outcomes.

Preferred Skills:

• Proven track record of applying advanced AI/ML approaches (deep learning, generative modeling, structure-based ML) to drug discovery or related life sciences domains.

• Experience with cheminformatics or bioinformatics toolkits is highly desirable.

• Familiarity with cloud computing and scalable ML workflows is a plus

• Ability to work at the interface of computational and experimental science. 

  #LI-Hybrid  #LI-LN1

The Opportunity:

As an Executive Director and Head of Research Computational Biology within our Biology Function, the individual will oversee the scientific and strategic direction of systems biology research and preclinical computational biology initiatives. The individual will lead a team of computational biologists and bioinformaticians focused on acquisition, organization, and analysis of large multi-omics data sets, using both public and proprietary data sources, that will help inform treatment strategies and guide patient stratification for a growing pipeline of RAS(ON) and targeted oncology therapeutics. We are looking for an experienced leader with strong interpersonal skills and an ability to lead a strong and diverse computational biology team. Key aspects of the role include:

• Strategic vision and leadership: Develop and implement a long-term strategy for research systems biology and bioinformatic activities to support a growing pipeline of RAS(ON) and novel targeted inhibitors. Lead and supervise a team of experienced computational biologists and bioinformaticians to generate, organize, and interpret large data sets to inform therapeutic and combination strategies for patients with cancer.

• Cross-functional collaboration across research, translational, development and medical affairs groups: Work across functions to support advancement of programs from early discovery into clinical development using biological insights derived from computational approaches. Additionally, leverage clinical data from RVMD investigational agents to generate proprietary insights into RAS mutant tumor biology and RVMD RAS(ON) inhibitor mechanisms of action.

• Technical leadership and innovation: Lead a team analyzing large, high-dimensional datasets. Work with colleagues in Information Sciences and Information Systems to oversee data integration, analysis and visualization using cloud-based platforms (AWS, Azure, GCP). Direct the development and application of cutting-edge statistical analysis, AI/ML methods, generative AI models, and MLOps principles to elucidate findings and generate new insights related to biomarker discovery, drug target identification, and predictive modeling. Establish and implement modern workflow management systems (Snakemake, Nextflow) and reproducible research practices.

• External collaboration: Cultivate and manage academic and industry collaborations, including CRO partnerships. Represent the company at scientific conferences through presentations and thought leadership. Maintain an active publication record in high-impact, peer reviewed journals. Drive intellectual property strategy and patent filings related to computational discoveries.

Required Skills, Experience and Education:

• Education: A Ph.D. in systems biology, computational biology, bioinformatics, or a related biological or biomedical discipline.

• Experience: Minimum of 15+ years total experience with significant pharmaceutical/biotechnology industry and management experience.

• Scientific knowledge: Deep expertise in systems biology, computational biology, and bioinformatics, including proficiency with multi-omics data integration, modeling, and analysis. Experience with single-cell technologies, spatial transcriptomics, proteomics, and epigenomics. Oncology research experience preferred but not required.

• Technical: Advanced programming skills in R, Python, and at least one additional language (Perl, C/C++, Java). Proficiency with high-performance computing (HPC) and cloud platforms (AWS, Azure, or GCP). Knowledge of workflow management tools and version control systems. Understanding of MLOps principles, model deployment, and generative AI applications in drug discovery.

• Leadership and management: Demonstrated ability to lead, mentor, and inspire interdisciplinary teams while fostering a collaborative culture. Experience managing budgets and strategic planning at the department level. Proven track record of advancing research programs from discovery through development.

• Strategic thinking: Proven strategic thinker who can align research and drug development objectives and leverage innovative technologies effectively.

• Communication: Excellent communication and presentation skills for interacting with technical teams, senior leadership, and external partners. #LI-Hybrid  #LI-GL1

The Opportunity:

As a Director, Molecular Pathology, you will be a key member of a cross-functional Translational Sciences Team, reporting to the Senior Director and Head of Translational Sciences within Translational Research and will:

• Biomarker Strategy: Define and execute molecular and digital pathology-driven biomarker strategies.

• Integration of Advanced Modalities: Lead adoption of molecular pathology and spatial technologies (to support translational research and broader BDR needs.

• Digital & Computational Pathology: Drive implementation of whole-slide imaging, AI/ML-based image analysis, and integration of spatial biomarker analytics into decision-making.

• Data Interpretation & Reporting: Provide expert interpretation of pathology data, ensuring robust correlation with clinical outcomes and mechanistic insights.

• Cross-functional Leadership: Collaborate with Translational Medicine, Bioinformatics, and Clinical Development colleagues to implement candidate biomarkers into Translational Biomarker plans for RAS(ON) inhibitors in alignment with overarching clinical development strategies.

Responsibilities

• Scientific Leadership & Execution: Perform and interpret multiplex spatial biomarker datasets to inform Translational hypotheses and clinical strategies. Establish QC standards for data acquisition and analysis.

• Cross-Functional Collaboration: Partner within Research and Clinical teams to integrate spatial biomarker findings into translational plans. Collaborate with Systems Biology and Information Sciences teams to enable visualization tools

• External Partnership Management: Serve as primary scientific liaison to CROs for spatial biomarker workflows; review deliverables, troubleshoot issues, and drive continuous improvement.

• Capability Building: Document best practices and SOPs for spatial biomarker workflows; recommend platform upgrades and pilot evaluations.

Required Skills, Experience & Education:

• 10+ years in digital pathology/spatial biology within pharma, biotech, or CRO settings.

• Scientific Expertise: Deep knowledge of spatial biology (e.g. spatial transcriptomics, Visium, Xenium, GeoMx, MerFish, etc.); ability to translate complex data into actionable insights

• Execution Excellence: Bias for action; delivers high-quality analyses under tight timelines

• Collaboration & Influence: Builds strong relationships across functions and with external partners; communicates clearly and persuasively.

• Innovation & Continuous Improvement: Identifies opportunities to enhance workflows and adopt emerging technologies.

• PhD/MD or equivalent in Cancer Biology, Translational Sciences, Pathology or related discipline.

Preferred Skills:

• Hands-on experience with spatial pathology workloads.

• Familiarity with AI/ML-assisted pathology workflows and spatial statistics.

• Proven ability to manage CRO relationships and deliver time-sensitive biomarker analyses.

#LI-Hybrid  #LI-LN1

The Opportunity:

The Translational Sciences Intern will support the Translational Sciences team in advancing programs that connect preclinical discovery with clinical development. This role provides exposure to how Translational Research integrates molecular biology, pharmacology, biomarker discovery, and clinical data to inform therapeutic development in precision oncology. The intern will gain insight into how translational strategies are developed to understand drug mechanisms, identify biomarkers of response and resistance, and guide clinical trial design. This position is ideal for a student interested in translational cancer research and the interface between laboratory science and clinical application. The role focuses on learning, analysis, and cross-functional collaboration within a multidisciplinary drug development environment.

This role provides the opportunity to learn some or all the following, depending on project assignments and team needs.

• How translational research supports the development of targeted therapies in oncology.

• How biomarker strategies are developed to support clinical trials and precision medicine approaches. • How preclinical data are integrated with clinical observations to understand mechanisms of response and resistance.

• How cross-functional teams across discovery biology, pharmacology, clinical development, and bioinformatics collaborate in drug development.

• How experimental and clinical datasets are analyzed and interpreted to generate translational insights.

• How translational scientists communicate complex scientific findings to multidisciplinary teams.

Required Skills, Experience and Education:

• Strong analytical, critical-thinking, and problem-solving skills.

• Ability to interpret scientific literature and synthesize complex scientific information.

• Strong written and verbal communication skills.

• Interest in oncology, molecular biology, or translational research.

• Organized, detail-oriented, and able to work independently with guidance.

• Professional curiosity and willingness to learn new concepts.

• Pursuing a bachelor’s or master’s degree in a STEM field (e.g., biology, biochemistry, molecular biology, biomedical engineering, or related discipline).

Preferred Skills:

• Coursework or research experience in cancer biology, molecular biology, or pharmacology.

• Familiarity with biomarker concepts or translational research approaches.

• Experience with basic laboratory techniques or biological data analysis.

• Experience preparing scientific presentations or summarizing research findings.

• Interest in precision medicine and targeted cancer therapies. 

  #LI-Hybrid  #LI-AP1

About this opportunity:

At Freenome, we are seeking a Director, Technical Product Management to help grow the Freenome Product Management team. The ideal candidate is a seasoned leader who bridges the gap between complex molecular biology and scalable software products in a regulated environment. This person is responsible for the technical roadmaps, feature prioritization, software requirements, and specification definition related to Lab Information Management Systems (LIMS), laboratory automation, and software managing sample processing-to-result generation. You are passionate about building seamless, high-throughput clinical workflows that ensure data integrity and regulatory compliance, and you will have a significant impact on the continued growth of an organization dedicated to changing the entire landscape of cancer. 

The role reports to the Director, Product Management. This role will be a Hybrid (based in our Brisbane, California headquarters) or Remote role. 

What you’ll do:

• Define and execute the multi-year technical roadmap for IVD/LDT software platforms, ensuring alignment with clinical needs and regulatory requirements.
• Lead feature prioritization and software requirements definition of LIMS, lab automation, and software managing the sample processing-to-result generation to optimize high-throughput sample processing and data integrity.
• Direct the integration of complex diagnostic hardware with cloud-based or on-premise processing software, focusing on seamless end-to-end workflows.
• Ensure all software products comply with global regulatory standards, including FDA, CLIA/CAP, ISO 13485, and HIPAA/GDPR data privacy requirements.
• Collaborate with R&D, Molecular Biology, Clinical Lab, Lab Automation, and Engineering teams to translate complex assay protocols into automated, scalable software requirements.
• Ensure compliance to Software Development Life Cycle (SDLC) for diagnostic products, from initial concept to commercial launch for deliverables owned by Technical Product Management.
• Manage cross-functional dependencies between wet-lab operations, bioinformatics pipelines, and software engineering teams to ensure timely product delivery.
• Establish and monitor key performance indicators (KPIs) for software reliability, processing speed, and diagnostic accuracy in a clinical laboratory environment. 

Must haves:

• 8+ years in Technical Product Management, with at least 4 years specifically in IVD, Medical Devices, or Clinical SaaS.
• Proven experience with LIMS/LIS and laboratory automation workflows.
• Deep familiarity with FDA software guidelines and CLIA regulations.
• BS/MS in Computer Science, Bioengineering, Molecular Biology, or a related field.
• Demonstrated experience managing and scaling technical product teams in a regulated environment.
  

Nice to haves:

• MS or PhD in a technical or scientific field.
• Experience with Next-Generation Sequencing (NGS) data pipelines.
• Hands-on experience with cloud infrastructure (AWS/Azure/GCP) in a GxP environment.

Benefits and additional information:

The US target range of our base salary for new hires is $220,400 - $281,400. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.  Please note that individual total compensation for this position will be determined at the Company’s sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ freenome.com/job-openings/ for additional company information.  

Freenome is proud to be an equal-opportunity employer, and we value diversity. Freenome does not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

Applicants have rights under Federal Employment Laws.  

• Family & Medical Leave Act (FMLA)
• Equal Employment Opportunity (EEO)
• Employee Polygraph Protection Act (EPPA)

#LI-REMOTE

We're looking for a Protein Design Scientist to own the development and deployment of agentic workflows for protein design. In this role, you will build systems that orchestrate protein language models, structure predictors, fitness scoring tools, and experimental feedback into automated or semi-automated design pipelines - closing the loop between computation and the wet lab.

This is a hands-on, high-ownership role. You'll work across the full stack of a design workflow: selecting and integrating models, defining agent logic and iteration strategies, building robust infrastructure for deployment, and collaborating closely with ML scientists, protein design scientists, and biologists to ensure your systems produce experimentally actionable results.

As an early employee, you will shape how Profluent approaches workflow automation and help define best practices for agentic systems in protein engineering.

Responsibilities

• Design, build, and deploy end-to-end agentic workflows that take protein function specifications and produce ranked candidate sequences for experimental validation
• Integrate protein language models, structure prediction tools, and scoring functions into multi-step pipelines with iteration, feedback loops, and human-in-the-loop checkpoints
• Own the full lifecycle of workflow systems: architecture, implementation, testing, deployment, monitoring, and iteration based on experimental outcomes
• Collaborate with ML scientists to evaluate and integrate new models into workflows, and with protein design scientists and biologists to translate scientific goals into computational specifications and ensure workflows align with experimental realities
• Develop tooling for experiment tracking, logging, reproducibility, and versioning of design campaigns
• Evaluate and benchmark workflow performance against experimental results, using outcomes to improve agent strategies and model selection
• Partner with ML scientists to identify where existing models fall short in agentic contexts and inform priorities for model development, fine-tuning, and evaluation

Qualifications

• PhD (or equivalent industry experience) in Computational Biology, Bioinformatics, Computer Science, Machine Learning, Biochemistry, or a related field
• Minimum of 3+ years of experience as a protein design scientist
• Strong software engineering skills: you write clean, modular, production-quality code (Python required; experience with workflow orchestration frameworks is a plus)
• Hands-on experience with protein language models (e.g., ESM, ProGen, ProtTrans) for sequence generation, scoring, or representation
• Demonstrated understanding of protein engineering principles: structure-function relationships, fitness landscapes, and how computational predictions connect to wet-lab validation
• Experience building multi-component systems that chain model inference with data processing, filtering, and decision logic

Preferences (but not required)

• Experience with agentic AI systems, LLM tool-use patterns, or multi-step reasoning pipelines
• Familiarity with structure prediction tools (AlphaFold, RoseTTAFold, ESMFold) and inverse folding methods (ProteinMPNN, LigandMPNN)
• Track record of computational designs that were experimentally validated
• Experience with cloud compute platforms (GCP, AWS, Azure) and containerized deployment (Docker, Kubernetes)
• Publications in protein design, protein engineering, or ML for biology at major conferences or journals
• Familiarity with directed evolution, rational design, or de novo protein design strategies

What We Offer 

• High-growth opportunity with meaningful impact on the future of protein design
• Competitive compensation package with equity participation
• 401(k) with a strong employer match
• Comprehensive benefits including health/dental/vision insurance
• Generous PTO policy and commitment to work-life balance
• Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

About The Role:
10x Genomics is establishing a diagnostics effort to translate our leading single-cell and spatial genomics technologies into impactful clinical applications. This Clinical Laboratory Scientist/General Supervisor position is responsible for the day-to-day execution and oversight of high complexity next-generation sequencing (NGS) testing within a CLIA-certified laboratory. This role ensures the accuracy, reliability, and timeliness of test results while maintaining full compliance with regulatory and quality standards. The General Supervisor provides technical leadership, staff supervision, and operational support to ensure efficient laboratory performance.

What You Will Be Doing:

• Perform and oversee daily laboratory operations for high complexity NGS assays, ensuring adherence to established protocols and quality standards.
• Supervise and provide guidance to laboratory personnel, including training, competency assessment, and performance management.
• Ensure the accuracy and validity of test results through review of quality control, quality assurance, and assay performance metrics.
• Maintain compliance with CLIA, CAP, and other applicable regulatory requirements.
• Assist in the development, validation, implementation, and optimization of NGS assays and workflows.
• Monitor laboratory workflow, turnaround times, and resource utilization to ensure operational efficiency.
• Troubleshoot technical issues related to instrumentation, assays, and data analysis.
• Review and maintain laboratory documentation, including SOPs, validation reports, and quality records.
• Collaborate with laboratory leadership to support continuous quality improvement initiatives.
• Ensure proper maintenance and calibration of laboratory equipment.
  
  

To Be Successful in the Role, You Will Need:

• Active California Clinical Laboratory Scientist (CLS) license (or CGMBS/generalist license) meeting CLIA requirements for high-complexity testing
• Bachelor’s degree in chemical, biological, physical, clinical laboratory science, or a related field
• Meets CLIA General Supervisor qualifications under 42 CFR 493.1461, including appropriate education, training, and experience
• Minimum of 2–4 years of experience in high complexity CLIA testing, with demonstrated expertise and experience in NGS technologies.
  Prior supervisory or leadership experience preferred.
• Strong knowledge of CLIA regulations and quality systems.
• Experience with NGS platforms, library preparation, sequencing, and bioinformatics pipelines.

Additional Attributes

• Prior experience serving as CLIA General Supervisor
• Startup or high growth laboratory experience
• Background in medical or oncology diagnostics
• Excellent organizational, analytical, and problem-solving skills.
• Strong communication and leadership abilities.

About The Role:
10x Genomics is establishing a diagnostics effort to translate our leading single-cell and spatial genomics technologies into impactful clinical applications. This Clinical Laboratory Scientist/Technical Supervisor position performs and provides scientific and technical oversight for high complexity next-generation sequencing (NGS) assays within a CLIA-certified laboratory. This role is accountable for ensuring the operational execution, analytical validity, performance, and regulatory compliance of all NGS testing. The Technical Supervisor serves as the subject matter expert for assay validation, quality systems, and troubleshooting, and partners closely with laboratory leadership to maintain operational excellence and continuous improvement.

What You Will Be Doing:

• Provide operational execution and technical oversight of high complexity NGS assays, ensuring analytical accuracy and reliability of test results.
• Validate, and implement NGS assays in accordance with CLIA, CAP, and applicable regulatory standards.
• Establish and monitor quality control (QC) and quality assurance (QA) programs, including review of performance metrics, trends, and corrective actions.
• Author, review, and approve technical documentation, including standard operating procedures (SOPs), validation protocols/reports, and test methods.
• Ensure compliance with all regulatory requirements and support internal and external audits and inspections.
• Serve as the primary technical resource for troubleshooting complex assay, instrumentation, and bioinformatics issues.
• Evaluate and approve changes to assays, workflows, instrumentation, and software, including revalidation as required.
• Oversee proficiency testing, method comparisons, and ongoing assay performance monitoring.
• Provide technical training and competency assessment for laboratory personnel.
• Collaborate with cross-functional teams (bioinformatics, R&D, quality, and operations) to support assay optimization and innovation.
• Stay current with emerging technologies, regulatory updates, and best practices in NGS and molecular diagnostics.
  
  

To Be Successful in this Role, You Will Need:

• Active California Clinical Laboratory Scientist (CLS) license meeting CLIA requirements for Technical Supervisor of high complexity testing.
• Meets CLIA Technical Supervisor qualifications under 42 CFR 493.1449, including appropriate education, training, and experience
• Bachelor’s degree in chemical, biological, physical, clinical laboratory science, or a related field.
• Minimum of 4–6 years of experience in CLIA lab molecular diagnostics, with significant experience in NGS assay validation, implementation, and operation
• Demonstrated expertise and experience in NGS technologies, including library preparation, sequencing platforms, and bioinformatics analysis pipelines
• Strong knowledge of CLIA, CAP, NYS, and other regulatory frameworks governing high complexity testing.
• Proven experience with assay validation, QC/QA systems, and regulatory inspections.

Additional attributes

• Prior experience serving as CLIA Technical Supervisor
• Startup or high growth laboratory experience
• Background in medical or oncology diagnostics
• Excellent analytical, problem-solving, and decision-making skills.
• Strong written and verbal communication skills, with the ability to convey complex technical concepts clearly.

We are seeking an energetic, highly organized, and adaptable Operations Associate I/II to serve as the backbone of our office and laboratory environment. This is a dynamic role where you will manage the daily pulse of our workspace while supporting our technical teams in facility expansion and lab maintenance.

The ideal candidate thrives in a startup atmosphere - moving seamlessly from coordinating a team social to assisting with lab safety protocols or assembling furniture for the office.

Responsibilities

Primary Operations & Office Management 

• Act as the primary stakeholder for reception, greeting and managing all incoming vendors, visitors, and deliveries
• Oversee all shipping/receiving, mail sorting, and courier pickups
• Maintain a high standard for the pantry, fridge, and stationery stock; ensure general kitchen and office cleanliness
• Manage room bookings, food orders for meetings, and desk/office setups for new hires; fulfill other administrative responsibilities assigned as needed
• Assist in planning and executing monthly team activities and quarterly off-site vendor visits
• Lead purchasing for office supplies, IT equipment, and social events

Lab & Facility Support

• Assist the Lab and Operations Manager in setting up new office and lab spaces, including furniture assembly and equipment placement
• Support the wet lab through inventory management, specialized waste management, and routine equipment maintenance
• Maintain in-depth knowledge of safety/emergency protocols; ensure the site remains compliant and safe for all staff
• Act as a buyer for the Bioinformatics, Machine Learning, and Biology teams, managing Purchase Orders (POs) and maintaining current vendor information
• Assist with account reconciliation and maintaining up-to-date vendor records
• Fulfill additional support on projects assigned as needed

Qualifications

• BA or BS or AA/AS +2 years relevant work experience
• Must be able to lift at least 25 lbs
• Previous experience managing Purchase Orders (POs) 
• Previous customer service experience or prior public-facing roles
• Exceptional interpersonal communication, excellent customer-facing skills, elite time management, and a high degree of organizational efficiency
• Ability to be adaptable/flexible in the day-to-day

Preferences (but not required)

• BS in STEM  
• 1+ years of experience in a wet lab environment
• Familiarity with BSL2 safety standards and hazardous waste protocols
• Proficiency with Rippling, Ramp, Google Drive, and Notion
• Ability to lift 40 lbs
• Desire to learn new skills and initiate and own new tasks or projects 

What We Offer

• High-growth opportunity with meaningful impact on the future of protein design
• Competitive compensation package with equity participation
• 401(k) with a strong employer match
• Comprehensive benefits including health/dental/vision insurance
• Generous PTO policy and commitment to work-life balance
• Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Work Authorization Requirement

Applicants must have ongoing work authorization in the United States that does not require employer sponsorship. Sponsorship will not be provided now or at any time in the future for this position.

Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

We're looking for a motivated and creative Machine Learning (ML) Scientist to drive research into new technologies for biomolecular design. This position offers an opportunity to work at the forefront of generative modeling research across language processing, representation learning, and protein engineering. You should be a self-directed researcher who has the ability to rapidly prototype and evaluate new models and algorithms in the biomolecular domain. 

As an early employee, you will proactively shape the direction of our machine learning efforts and collaborate across diverse teams of computational and experimental scientists.

Responsibilities

• Design and develop state-of-the-art deep learning methods for protein sequence, structure, and function prediction and apply them to protein design
• Curate relevant datasets and design tasks for rigorous evaluation of generative models 
• Collaborate with Biology team to design and characterize novel designed biomolecules
• Implement, analyze, and interpret multiple computational approaches and present results to colleagues in regular update meetings
• Work within a collaborative, fast-paced, interdisciplinary team across biology and machine learning to help shape the scientific and strategic vision of the company

Qualifications

• PhD (or equivalent industry experience) in Computer Science, Machine Learning, Natural Language Processing, Applied Math, Computational Biology, Statistics, or a related field
• Experience with conceiving of, implementing, and evaluating novel machine learning techniques
• Publications at major machine learning conferences (NeurIPS, ICML, ICLR) or scientific journals (Nature, Science, Nature Biotech, Nature Methods, PNAS)
• Experience with modern deep learning frameworks such as Pytorch or Jax

Preferences (but not required)

• Familiarity with foundational biology of proteins and nucleic acids
• Experience developing machine learning models for proteins (language models, structure prediction, design)
• Previous experience in data extraction and curation from bioinformatics data sources
• Familiarity with wet lab experimental assays and associated limitations
• Experience with cloud compute platforms (GCP, AWS, Azure)

What We Offer

• High-growth opportunity with meaningful impact on the future of protein design
• Competitive compensation package with equity participation
• 401(k) with a strong employer match
• Comprehensive benefits including health/dental/vision insurance
• Generous PTO policy and commitment to work-life balance
• Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

We’re seeking an experienced computational scientist to lead the design, development, and operation of the NGS analysis platform that powers Profluent’s gene editing and protein design programs. You’ll work at the intersection of computational biology, software engineering, and experimental biology to build scalable systems that extract clear, actionable insights from large-scale sequencing data.

In this role, you’ll architect core bioinformatics infrastructure, define analytical strategy, and collaborate closely with experimental and ML teams to accelerate design-build-test-learn cycles. You’ll also mentor team members, promote software engineering best practices, and help shape the future of Profluent’s computational biology capabilities.

Responsibilities 

• Lead design and implementation of scalable NGS analysis pipelines supporting gene editing and protein engineering workflows
• Develop clear, intuitive visualizations and reports to communicate sequencing results and biological insights
• Manage cloud-based compute environments and data systems for large-scale datasets
• Partner with biology teams to analyze results, troubleshoot, and optimize experimental design
• Collaborate with machine learning teams to curate data for model training
• Establish best practices for code review, testing, and CI/CD in computational workflows
• Mentor junior scientists and foster a culture of rigor, reproducibility, and innovation

Qualifications

• PhD or MS in Bioinformatics, Computational Biology, Computer Science, or a related quantitative field
• 5+ years of experience analyzing NGS datasets (e.g., amplicon sequencing, high-throughput editing, or screening experiments)
• Strong programming skills in Python (pandas, numpy, biopython, etc.)
• Expertise with workflow orchestration tools (Nextflow, Snakemake) and cloud environments (GCP, AWS)
• Experience with containerization (Docker, Kubernetes) and scalable compute infrastructure
• Deep understanding of Linux, git-based version control, and software engineering best practices
• Proven ability to transform complex sequencing data into actionable biological insights

Preferences (but not required)

• Experience with gene editing technologies (CRISPR, base or prime editing; strongly preferred)
• Familiarity with SQL and data modeling for biological or experimental data
• Experience with LIMS platforms (e.g., Benchling) and lab data integration
• Track record of developing production-quality scientific software or open-source bioinformatics tools

What We Offer

• High-growth opportunity with meaningful impact on the future of protein design
• Competitive compensation package with equity participation
• 401(k) with a strong employer match
• Comprehensive benefits including health/dental/vision insurance
• Generous PTO policy and commitment to work-life balance
• Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Work Authorization Requirement

Applicants must have ongoing work authorization in the United States that does not require employer sponsorship. Sponsorship will not be provided now or at any time in the future for this position.

Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

Please note that this position can be based in San Diego, CA OR San Francisco, CA OR Princeton, NJ. Acadia's hybrid model requires this role to work in our office three days per week on average.

Position Summary

The Executive Director will lead the design and implementation of disease and drug mechanism of action (MoA) studies to advance therapeutics into and through clinical development. The position requires deep experience in translational sciences, proven leadership and mentoring skills, hands-on rare disease experience, strong understanding of clinical biomarker development, and a deep understanding of drug development from discovery through late-stage clinical studies.  The ability to synthesize complex biological concepts and data into clearly communicated actionable insights is critical, as is a track record of successful partnering with functions across the drug development paradigm. 

Primary Responsibilities

• Develop translational biology strategies to interrogate disease and drug MoA, implement and drive execution for candidate targets and therapeutics

• Lead nonclinical sciences function, mentor scientists across translational sciences

• Partners with colleagues across the drug development paradigm to develop and test hypotheses designed to advance target and candidate molecule evaluation through various stages of development

• Partner with Translational Science colleagues to develop preclinical strategies supporting indication selection, PK/PD analyses, and mechanistic development for successful IND filing and clinical development

• Synthesize, analyze and integrate complex biological data, providing clear and actionable insights to drive drug development decisions

• Identify, evaluate and leverage cutting-edge technologies to expedite early-stage program development & success

• Identify and manage CROs and build strong collaborative relationships with Acadia partners to maximize the application of complementary areas of expertise

• Present programs and data for asset team, governance and senior / executive management review

• Contribute, as author and strategist, to document generation for preclinical studies & clinical protocols, clinical study reports, statistical analysis plans, research partnerships, regulatory materials (IB, IND, NDA, etc.) and publications

• Perform other responsibilities as assigned

Education/Experience/Skills

PhD in life science or related field.  Targeting 15 years of progressively responsible experience in drug development within the pharmaceutical or biotech industry.  An equivalent combination of relevant education and experience may be considered.

Key Skills:

• Strong cross-functional leadership with a proven ability to build collaborative, high-performing teams and represent nonclinical sciences across Translational Sciences and program teams
  
  
• Hands-on experience across drug discovery, preclinical development, and clinical-stage programs (Phase 1–3), including rare disease
  
  
• Demonstrated success leading programs through IND filing, with deep expertise in small molecule INDs and regulatory submissions (IND, NDA, BLA)
  
  
• Expertise in preclinical  (MoA) analysis, indication selection, and supporting clinical development strategies
  
  
• Strong understanding of clinical biomarker strategy and development
  
  
• Ability to analyze complex, multifactorial datasets, with computational literacy and collaboration with computational biology; bioinformatics integration experience is a plus
  
  
• Effective communicator with high emotional intelligence; skilled in presenting complex data to senior leadership and influencing stakeholders
  
  
• Proven ability to make decisions under uncertainty, aligning with timelines and organizational objectives
  
  
• Track record of driving performance through goal-setting, accountability, continuous improvement, and leading change across teams
  
  
• Able to manage multiple priorities in fast-paced environments, with flexibility for domestic and international travel; experience in neurology and across modalities (e.g., ASO, mRNA) is a plus

Physical Requirements

This role involves regular standing, walking, sitting, and the use of hands for handling or operating equipment. The employee may also need to reach, climb, balance, stoop, kneel, crouch, and maintain visual, verbal, and auditory communication in a standard office environment and while working independently from remote locations. The employee must occasionally lift and/or move up to 20 pounds.  This position requires the ability to travel independently overnight and/or work after hours as required by travel schedules or business needs.

LI #SL-1

Our generative models learn the blueprint of life by modeling large-scale evolutionary data, enabling us to engineer and write biology in unprecedented ways. We are seeking a passionate Computational Research Intern to join moonshot projects at the intersection of bioinformatics and machine learning.

This is a rare opportunity to tackle open-ended scientific and engineering challenges with direct potential for high-impact publications and real-world applications in synthetic biology and protein engineering.

Responsibilities

• Design and implement computational approaches to advance cutting-edge research in bioinformatics and machine learning
• Analyze large-scale genomic and protein datasets to uncover new biological insights and capabilities
• Collaborate closely with scientists and engineers across machine learning, protein engineering, and biology teams
• Document and present research findings internally, with the potential to publish in leading journals and conferences

Qualifications 

• Enrolled in a BS, MS, or PhD program in Bioinformatics, Computational Biology, Computer Science, Statistics, or a related quantitative field
• Strong programming skills in Python and familiarity with scientific computing libraries (e.g., NumPy, pandas, Jupyter)
• Experience in one or more of the following: machine learning, large-scale data analysis, genomics, or protein bioinformatics
• Excellent problem-solving skills, scientific curiosity, and ability to work both independently and collaboratively

Internship Details

• Typical duration: 12 weeks, with flexible start dates
• Hybrid: 2 - 3 days on-site per week in our Emeryville, CA headquarters
• Salary: $1,667 per week
• Opportunity to publish your work and make a lasting impact in computational biology and AI-driven protein design

What We Offer

• Work on moonshot projects at the frontier of AI and biology
• Mentorship from leading experts in bioinformatics, machine learning, and synthetic biology
• A dynamic, mission-driven environment with the resources of a fast-growing, well-funded startup
• Competitive internship compensation and benefits

COMPANY

Octant is pioneering a new generation of precision medicines by combining synthetic biology, chemistry, and AI/ML to tackle complex cellular mechanisms driving human disease. We are a small molecule therapeutics company scaling drug discovery to unlock therapies for genetically defined and historically intractable diseases.

JOB DESCRIPTION

We're looking for a computational drug discovery intern to join Octant this summer in a program funded by the Gates Foundation to identify small-molecule drugs targeting HPV-driven cancers. In this role, you'll work alongside our computational and experimental teams to build and iterate on machine learning models, explore molecular representations and structure-activity relationships, and help drive compound design and prioritization from data to decision.

THIS INTERNSHIP MIGHT BE GREAT FOR YOU IF YOU ARE/HAVE:

• Currently enrolled in or recently completed a BS or MS in a quantitative field (CS, bioinformatics, applied math, data science, computational biology, or adjacent)
• Proficient in Python for data analysis and scripting (pandas, numpy, scikit-learn at minimum)
• Experience building or training ML models on real datasets, not just coursework exercises
• At least one substantive research experience (academic lab, industry internship, or independent project) where you drove a project from question to result
• Familiarity with version control (git) and working in shared codebases
• Coursework or research exposure in at least one biological science area
• Ability to communicate results to both computational and experimental audiences
• Comfort with ambiguity and fast iteration. The project work is on a weekly cadence, which means making judgment calls with incomplete data, not waiting for perfect information

EVEN BETTER IF YOU HAVE:

• Hands-on experience with molecular representations (SMILES, fingerprints) or cheminformatics toolkits (RDKit, DeepChem)
• Experience with cloud/distributed compute environments (Databricks, Spark, or similar)
• Understanding of structure-activity relationships, compound libraries, or hit expansion concepts
• Demonstrated ability to work across the computational-experimental boundary (e.g., designed an analysis that informed a wet-lab decision, or interpreted assay data to guide a model)
• Familiarity with active learning or Bayesian optimization frameworks
• Experience building or working with agentic systems, LLM tool-use pipelines, or multi-step automated workflows
• Familiarity with prompt engineering and structured output parsing from language models
• Experience with workflow orchestration or pipeline tools (Databricks, Airflow, or similar)
• Comfort designing and consuming APIs or integrating across multiple tools/platforms programmatically
• Experience with software engineering best practices beyond scripting (testing, error handling, logging, modular code design)
• Familiarity with database interactions (SQL, querying structured data stores) in a production or semi-production context

Optional: Along with your application, please share a paper/preprint/software repo that best highlights your strengths so we can better understand the work you've led. If there is nothing public, please summarize that work in a few paragraphs. 

The pay range for this role is $1,400 to $1,500 per week, depending on experience. The duration of the internship is up to 10 weeks.

Octant is located in Emeryville, California and we work onsite.

Octant is an equal opportunity company that values applicants of all backgrounds. We’re committed to fostering an inclusive and supportive work environment. We value less traditional backgrounds, and may consider an equivalent combination of knowledge, skills, education, and experience to meet minimum qualifications. We know that confidence-gap and imposter syndrome can get in the way of meeting spectacular candidates, so please don’t hesitate to apply — we’d love to hear from you.

What You Will Contribute To Altos

As part of our team, you will help to accelerate and optimize our progress in agentic AI methods for biological and clinical data curation and analysis.

In this role, you will be an integral part of our multidisciplinary teams building the computational platforms that will enable Altos to achieve its mission. You will collaborate with biomedical research experts as well as other machine learning scientists and engineers across the Institute of Computation to contribute to the Altos research and translation ecosystem, focusing on designing and building state-of-the-art agentic AI systems and workflows that tackle biological questions, accelerate clinical data analysis, and aid in the discovery of novel interventions for aging and disease.

The successful candidate will combine deep expertise in agentic AI methods with a strong foundation in bioinformatics and/or clinical R&D. You will work closely with domain experts to translate complex biological and clinical data challenges into intelligent, automated solutions. You will thrive in a fast-paced environment that stresses teamwork, transparency, scientific excellence, originality, and integrity.

Responsibilities

• Design and develop agentic AI workflows for biological and clinical data curation tasks
• Research and implement advanced context engineering techniques (RAG, agentic RAG, graph RAG) tailored to biomedical data
• Develop and optimize prompts and agent architectures for reliability, accuracy, and scientific rigor
• Build LLM-based tool-use systems and integrations relevant to bioinformatics and clinical R&D pipelines
• Collaborate with bioinformatics scientists, clinical researchers, and domain experts to identify automation opportunities and translate them into agentic solutions
• Evaluate and benchmark agentic systems, establishing rigorous metrics for performance and correctness in scientific contexts
• Stay current with the rapidly evolving landscape of agentic AI methods and contribute to internal best practices

Who You Are 

• Proven track record leveraging machine learning and AI to solve real-world problems
• Expertise in agentic AI methods development, including prompt optimization, LLM-based tool use, context engineering (RAG, agentic RAG, graph RAG), and agent evaluation
• Experience writing production-quality code with agentic frameworks (e.g., LangGraph, Pydantic-AI, DSPy, or similar)
• Deep familiarity with bioinformatics and/or clinical R&D, with the ability to engage meaningfully with domain experts on biological and clinical questions
• Proficiency with AI-assisted development tools (e.g., Claude Code, Cursor) to iterate rapidly
• A team player who thrives in collaborative environments and is committed to enabling colleagues to reach their full potential through giving and requesting feedback focused on professional growth
• Able to advise others across the wider function / company on cutting edge agentic AI practices and approaches to enable the science / research. Desire to constantly expand your skillset and knowledge. Keen to learn more about biology, machine learning, and medicine
• Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities

Minimum Qualifications

• PhD in Computer Science, Machine Learning, Bioinformatics, or a related field
• Demonstrated experience developing agentic AI systems, including LLM-based tool use, prompt engineering, and context engineering techniques
• Strong foundation in machine learning principles and their application to real-world problems
• Strong background in bioinformatics, computational biology, or clinical R&D
• Familiarity with MCP server development and agent skill creation
• Very strong programming skills in Python, with experience writing production-quality, well-documented code
• Strong track record of published peer-reviewed research in AI/ML and/or computational biology

Preferred Qualifications

• Experience with AWS services (S3, Bedrock, Lambda) in the context of AI/ML workflows
• Experience with clinical trial data, regulatory data curation, or biomedical ontologies (e.g., CDISC, SNOMED, MedDRA)
• Track record working with NGS data (e.g., RNA-seq, ATAC-seq, DNA methylation) or other biological data modalities
• Experience designing evaluation frameworks and benchmarks for agentic AI systems
• Familiarity with knowledge graph construction and graph-based retrieval methods

The salary range for Redwood City:

• Senior Scientist I, Machine Learning: $257,400 - $330,000

The salary range for San Diego:

• Senior Scientist I, Machine Learning: $239,500 - $307,000

Exact compensation may vary based on skills, experience, and location.

#LI-NN1

For UK applicants, before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

Quantum computing holds the promise of humanity’s mastery over the natural world, but only if we can build a real quantum computer. PsiQuantum is on a mission to build the first real, useful quantum computers, capable of delivering the world-changing applications that the technology has long promised.  We know that means we will need to build a system with roughly 1 million qubits that supports fault tolerant error correction within a scalable architecture, and a data center footprint.

By harnessing the laws of quantum physics, quantum computers can provide exponential performance increases over today’s most powerful supercomputers, offering the potential for extraordinary advances across a broad range of industries including climate, energy, healthcare, pharmaceuticals, finance, agriculture, transportation, materials design, and many more.

PsiQuantum has determined the fastest path to delivering a useful quantum computer, years earlier than the rest of the industry. Our architecture is based on silicon photonics which gives us the ability to produce our components at Tier-1 semiconductor fabs such as GlobalFoundries where we leverage high-volume semiconductor manufacturing processes, the same processes that are already producing billions of chips for telecom and consumer electronics applications. We also benefit from the quantum mechanics reality that photons don’t feel heat or electromagnetic interference, allowing us to take advantage of existing cryogenic cooling systems and industry standard fiber connectivity.

In 2024, PsiQuantum announced two government-funded projects to support the build-out of our first Quantum Data Centers and utility-scale quantum computers in Brisbane, Australia and Chicago, Illinois. Both projects are backed by nations that understand quantum computing’s potential impact and the need to scale this technology to unlock that potential. And we won’t just be building the hardware, but also the fault tolerant quantum applications that will provide industry-transforming results.

Quantum computing is not just an evolution of the decades-old advancement in compute power. It provides the key to mastering our future, not merely discovering it. The potential is enormous, and we have the plan to make it real. Come join us.

There’s much more work to be done and we are looking for exceptional talent to join us on this extraordinary journey!

Job Summary:

Are you eager to revolutionize life sciences using the transformative power of quantum computing? As a Quantum Life Sciences Chemist, you will lead efforts at the intersection of quantum computing, computational chemistry, and biology, solving critical challenges in drug design, biomolecular modeling, and biological systems simulation. By integrating quantum algorithms with established life sciences methodologies, you will pioneer new approaches to address complex problems in pharmaceuticals, biomaterials, and bioinformatics. Join our interdisciplinary team to advance quantum-enabled innovations and shape the future of life sciences.

At PsiQuantum’s Quantum Solutions team, your role will focus on bridging the gap between fault-tolerant quantum computing (FTQC) and established computational chemistry and life sciences tools. You will integrate these approaches with machine learning to explore novel workflows for quantum-informed drug discovery and biomolecular modeling. Your expertise in theoretical and computational chemistry will enable you to connect quantum-computed molecular insights with complex biological systems, driving advancements in drug design, biomaterials, and other critical areas within the life sciences.

This position requires a PhD in computational chemistry, biophysics, or a closely related field, preferably with postdoctoral research experience (although postdoc experience is not mandatory). We are looking for a curious, creative, and interdisciplinary thinker with a strong foundation in computational methodologies applicable to life sciences. The ideal candidate should be an avid reader of scientific literature, possess expert-level hands-on coding experience (e.g., Python, Fortran, C++), and have demonstrated skills in developing and applying computational techniques. Experience contributing to scientific software or modeling workflows is a plus. While prior knowledge of quantum information and fault-tolerant quantum computing is highly preferred, it is not required.

Responsibilities:

• Conduct innovative research, literature analysis, problem solving, and quantum workflow design in the areas of quantum-informed biomolecular modeling, drug discovery, and computational chemistry.
• Collaborate with quantum algorithm experts to identify areas where quantum computing can have the greatest impact in computational chemistry, biology, and life sciences.
• Contribute expertise in conventional (non-quantum-computing) algorithms to the development of in-house quantum algorithms. Serve as a technical lead in customer projects by collaborating with customers’ teams to integrate quantum computing-produced computational outputs into conventional life sciences workflows.
• Serve as a liaison between partner teams and PsiQuantum’s quantum information experts for innovative algorithm selection, development, and prioritization relevant to life sciences.
• Develop computational workflows that combine best-in-class conventional approaches (e.g., through high-performance computing (HPC)) with the breakthrough computational abilities of FTQC to reshape how quantum workflows are designed for life sciences applications.
• Serve as a subject matter expert in computational quantum chemistry and biomolecular modeling for PsiQuantum’s Quantum Solutions team, staying updated on recent academic literature, trends, and tools in life sciences.
• Foster collaboration across teams to maximize the impact of quantum algorithms and quantum computing-generated data in life sciences applications.
• Help shape external-facing materials that champion the applications of FTQC in the pharmaceutical, biotechnology, and life sciences industries (for key opinion leaders, media, and partners).
• Build and maintain external partnerships and collaborations on the topic, which can include meetings, group problem-solving sessions, or drafting research proposals, among others.
• Create organized internal reports and thoroughly document progress on assigned tasks.

Experience/Qualifications:

Required:

• Ph.D. in computational chemistry, biophysics, bioinformatics, or a closely related field, with a strong focus on computational methodology development, and 0 to 6 years of post-PhD (postdoctoral or industrial) experience.
• Hands-on experience with modeling and simulation of biological systems, such as protein-ligand interactions, enzymatic reactions, or biomolecular dynamics.
• Enthusiasm for working in a collaborative, interdisciplinary, and dynamic team environment.
• Expert-level Python coding skills with experience in scientific libraries relevant to life sciences.
• Proven ability to stay updated on recent academic literature and trends in computational chemistry and biomolecular modeling.

Preferred:

• Strong foundational knowledge of quantum chemistry methods (e.g., DFT, coupled cluster theory, or wavefunction-based approaches) and molecular simulation techniques as applied to biomolecular systems.
• Experience with free energy perturbation (FEP), molecular docking, or similar computational techniques for drug discovery.
• Experience with machine learning (ML) techniques in computational drug discovery, biomolecular modeling, or structural biology.
• Experience with coding GPU-accelerated molecular simulations.
• Familiarity with hybrid quantum-classical methodologies, such as QM/MM, applied to biomolecular systems.
• Knowledge of quantum embedding theories (e.g., DMET, embedded correlated wavefunctions) and their application to large, complex biomolecular systems.
• Hands-on experience with quantum computing or quantum algorithms, especially as applied to biological or chemical systems.
• General understanding of light-matter interactions or electronic excitations relevant to biological or chemical systems, such as energy transfer or photochemical processes.
• Familiarity with advanced quantum mechanical methods (e.g., CASCI, CASSCF) and their relevance to modeling enzymatic reactions or metal-containing biomolecules.
• Demonstrated scientific communication skills through peer-reviewed publications, conference presentations, or collaboration with industry partners.
• Expert-level C++ or Fortran coding skills.

PsiQuantum provides equal employment opportunity for all applicants and employees. PsiQuantum does not unlawfully discriminate on the basis of race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), gender identity, gender expression, national origin, ancestry, citizenship, age, physical or mental disability, military or veteran status, marital status, domestic partner status, sexual orientation, genetic information, or any other basis protected by applicable laws.

Note: PsiQuantum will only reach out to you using an official PsiQuantum email address and will never ask you for bank account information as part of the interview process. Please report any suspicious activity to recruiting@psiquantum.com.

We are not accepting unsolicited resumes from employment agencies.

About this opportunity:

At Freenome, we are seeking a Senior Machine Learning Scientist to help grow the Machine Learning Science team, within the Computational Science department. The ideal candidate has a strong knowledge of artificial intelligence (AI), including machine learning (ML) fundamentals and extensive experience with deep learning (DL) methods, a track record of successfully using these methods to answer complex research questions, and the ability to thrive in a highly cross-functional environment.

They will be responsible for the development of algorithms for early, blood-based detection tests for cancer. They will build on a foundation of ML/DL and statistical skills to develop models for identifying molecular signals from blood. They will also work with computational biologists, molecular biologists and ML engineers to design and drive research experiments, and will have a significant impact on the continued growth of an organization dedicated to changing the entire landscape of cancer.

The role reports to the Director, Machine Learning Science. This role can be a Hybrid role based in our Brisbane, California headquarters (2-3 days per week in office), or remote.

What you’ll do:

• Independently pursue cutting edge research in AI applied to biological problems (including cancer research, genomics, computational biology, immunology, etc.).
• Build new models or fine-tune existing models to identify biological changes resulting from disease.
• Build models that achieve high accuracy and that generalize robustly to new data.
• Apply contemporary interpretability techniques to provide a deeper understanding of the underlying signal identified by the model, ideally suggesting potential biological mechanisms.
• Work closely with ML Engineering partners to ensure that Freenome’s computational infrastructure supports optimal model training and iteration.
• Take a mindful, transparent, and humane approach to your work.

Must haves:

• PhD or equivalent research experience with an AI emphasis and in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, Engineering, Computational Biology, or Bioinformatics.
• 3+ years of postdoc or post-PhD industry experience achieving impactful results using relevant modeling techniques.
• Expertise, demonstrated by research publications or industry achievements, in applied machine learning, deep learning and complex data modeling.
• Practical and theoretical understanding of fundamental ML models like generalized linear models, kernel machines, decision trees and forests, neural networks.
• Practical and theoretical understanding of DL models like large language models or other foundation models.
• Extensive experience with training paradigms like supervised learning, self-supervised learning, and contrastive learning.
• Proficient in current state of the art in ML/DL approaches in different domains, with an ability to envision their applications in biological data.
• Proficiency in a general-purpose programming language: Python, R, Java, C, C++, etc.
• Proficiency in one or more ML frameworks such as; Pytorch, Tensorflow and Jax; and ML platforms like Hugging Face.
• Experience in ML analysis and developer tools like TensorBoard, MLflow or Weights & Biases.
• Excellent ability to communicate across disciplines, work collaboratively, and make progress in smaller steps via experimental iterations.
• A passion for innovation and demonstrated initiative in tackling new areas of research.

Nice to haves:

• Deep domain-specific experience in computational biology, genomics, proteomics or a related field.
• Experience in building DL models for genomic data, with knowledge of state-of-the-art DNA foundation models.
• Experience in NGS data analysis and bioinformatic pipelines.
• Experience with containerized cloud computing environments such as Docker in GCP, Azure, or AWS.
• Experience in a production software engineering environment, including the use of automated regression testing, version control, and deployment systems.

Benefits and additional information:

The US target range of our base salary/hourly rate for new hires is $173,775 - $246,750. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.  Please note that individual total compensation for this position will be determined at the Company’s sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ freenome.com/job-openings/ for additional company information.  

Freenome is proud to be an equal-opportunity employer, and we value diversity. Freenome does not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

Applicants have rights under Federal Employment Laws.  

• Family & Medical Leave Act (FMLA)
• Equal Employment Opportunity (EEO)
• Employee Polygraph Protection Act (EPPA)

#LI-HYBRID

About this opportunity:

At Freenome, we are seeking a Staff Machine Learning Scientist to help grow the Machine Learning Science team, within the Computational Science department. The ideal candidate has a strong knowledge of artificial intelligence (AI), including machine learning (ML) fundamentals and extensive experience with deep learning (DL) methods, a track record of successfully using these methods to answer complex research questions, the ability to drive independent research and thrive in a highly cross-functional environment.

They will be responsible for the development of algorithms for early, blood-based detection tests for cancer. They will build on a foundation of ML/DL and statistical skills to develop models for identifying molecular signals from blood. They will also work with computational biologists, molecular biologists and ML engineers to design and drive research experiments, and will have a significant impact on the continued growth of an organization dedicated to changing the entire landscape of cancer.

The role reports to the Director, Machine Learning Science. This role can be a Hybrid role based in our Brisbane, California headquarters (2-3 days per week in office), or remote.

What you’ll do:

• Independently pursue cutting edge research in AI applied to biological problems (including cancer research, genomics, computational biology, immunology, etc.).
  
• Build new models or fine-tune existing models to identify biological changes resulting from disease.
  
• Build models that achieve high accuracy and that generalize robustly to new data.
  
• Apply contemporary interpretability techniques to provide a deeper understanding of the underlying signal identified by the model, ideally suggesting potential biological mechanisms.
  
• Work closely with ML Engineering partners to ensure that Freenome’s computational infrastructure supports optimal model training and iteration.
  
• Take a mindful, transparent, and humane approach to your work.
  

Must haves:

• PhD or equivalent research experience with an AI emphasis and in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, Engineering, Computational Biology, or Bioinformatics.
• 6+ years of postdoc or post-PhD industry experience achieving impactful results using relevant modeling techniques.
• Expertise demonstrated by research publications or industry achievements, in driving independent research in applied machine learning, deep learning and complex data modeling.
• Practical and theoretical understanding of fundamental ML models like generalized linear models, kernel machines, decision trees and forests, neural networks, boosting and model aggregation.
• Practical and theoretical understanding of DL models like large language models or other foundation models.
• Extensive experience with training paradigms like supervised learning, self-supervised learning, and contrastive learning.
• Proficient in current state of the art in ML/DL approaches in different domains, with an ability to envision their applications in biological data.
• Proficiency in a general-purpose programming language: Python, R, Java, C, C++, etc.
• Proficiency in one or more ML frameworks such as; Pytorch, Tensorflow and Jax; and ML platforms like Hugging Face.
• Experience in ML analysis and developer tools like TensorBoard, MLflow or Weights & Biases.
• Excellent ability to communicate across disciplines, work collaboratively, and make progress in smaller steps via experimental iterations.
• Proficient at productive cross-functional scientific communication and collaboration with software engineers and computational biologists.
• A passion for innovation and demonstrated initiative in tackling new areas of research.

Nice to haves:

• Deep domain-specific experience in computational biology, genomics, proteomics or a related field.
  
• Experience in building DL models for genomic data, with knowledge of state-of-the-art DNA foundation models.
  
• Experience in NGS data analysis and bioinformatic pipelines.
  
• Experience with containerized cloud computing environments such as Docker in GCP, Azure, or AWS.
  
• Experience in a production software engineering environment, including the use of automated regression testing, version control, and deployment systems.
  

Benefits and additional information:

The US target range of our base salary for new hires is $199,675.00 - $283,500.00. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.  Please note that individual total compensation for this position will be determined at the Company’s sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ freenome.com/job-openings/ for additional company information.  

Freenome is proud to be an equal-opportunity employer, and we value diversity. Freenome does not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

Applicants have rights under Federal Employment Laws.  

• Family & Medical Leave Act (FMLA)
• Equal Employment Opportunity (EEO)
• Employee Polygraph Protection Act (EPPA)

#LI-HYBRID

About the Role

10x Genomics is establishing its first CLIA/CAP-certified laboratory to bring cutting-edge single-cell and spatial genomic technologies into clinical practice. Reporting to the Head of Quality and Regulatory, the Quality Assurance Manager will play a pivotal role in defining, developing and implementing the lab’s quality infrastructure, ensuring compliance with CLIA, CAP, and state (including California and New York) requirements. This is a hands-on leadership role suited for a quality professional who can independently execute quality assurance (QA) responsibilities during the lab’s early buildout phase and later lead a small QA team as clinical operations scale. The ideal candidate combines deep knowledge of clinical laboratory quality systems with practical, solution-oriented execution in a fast-paced and collaborative environment.

What you will be Doing:

Clinical Quality Framework Establishment and Oversight

• Implement document control, deviation/CAPA systems, training programs, and internal audit processes compliant with CLIA, CAP, and applicable state and federal regulations.
• Collaborate closely with CLIA and assay development teams to develop and manage SOPs and work instructions
• Partner with the broader Quality/Regulatory team to  integrate the CLIA lab’s quality infrastructure into 10x’s enterprise-wide quality management system (QMS).
• Establish and track key quality metrics for laboratory operations (e.g., deviations, nonconformances, complaint handling, audit findings, proficiency testing).
• In partnership with CLIA Lab Director, ensure inspection readiness and execute regulatory submissions (CLIA, CAP, and state licensure).

Operational Quality Support

• Provide day-to-day quality oversight of clinical laboratory operations, including review and approval of validation plans, QC data, and reports.
• Serve as QA reviewer/approver for method validation, verification, and change control documentation for both laboratory methods and assay software components
• Ensure effective management of reagents, instruments, and workflow changes per CLIA/CAP requirements.
• Support onboarding and verification of LDTs transferred from Diagnostic Assay Development teams
• Act as quality liaison with external auditors and partners.

Team Leadership and Growth

• Initially serve as an individual contributor responsible for implementing and maintaining quality processes.
• As sample volume and operations expand, recruit, train, and manage a small team of QA specialists or analysts supporting lab quality activities.
• Foster a culture of compliance, continuous improvement, and scientific rigor.

Cross-Functional Collaboration

• Partner closely with Laboratory Operations, Diagnostic Assay Development, Clinical Bioinformatics, and IT teams to ensure compliant workflows and data integrity.
• Work with Quality and Regulatory leadership to align CLIA/CAP quality practices with 10x’s broader corporate systems and standards.
• Contribute to strategic planning for quality-related resources, tools, and training across diagnostic programs.

To be successful, you will Need:

• Bachelor’s or Master’s degree in Life Sciences, Medical Laboratory Science, Quality Management, or related field.
• 10+ years of experience in quality assurance within a regulated clinical laboratory (CLIA/CAP environment).
• Demonstrated experience building or expanding quality systems in a CLIA lab setting.
• Strong working knowledge of CLIA / CAP quality and documentation requirements
• Additional knowledge of  FDA 21 CFR Part 820 and ISO 13485 strongly preferred.
• Experience preparing for and leading CAP inspections and CLIA audits.
• Excellent written and verbal communication skills, with an ability to collaborate across scientific, operational, and regulatory functions.
• Hands-on, proactive, and adaptable, capable of working effectively in an early-stage, fast-growing diagnostic environment.
• Experience with LIMS, electronic QMS tools, and training management systems is required.

It would be advantageous if you Have:

• A Builder mentality – motivated by creating compliant, fit-for-purpose systems from the ground up.
• Hands-on and detail-oriented, with strong follow-through and accountability.
• Collaborative and pragmatic, balancing regulatory rigor with operational needs.
• Leadership-ready, with the ability to grow into managing a small, high-performing team.
• Mission-driven, passionate about enabling genomic technologies to transform patient care.

Impact:

The Quality Assurance Manager - CLIA/CAP Laboratory, will be instrumental in establishing 10x Genomics’ diagnostic quality foundation. This role ensures that every assay and clinical result produced under the CLIA/CAP framework meets the highest standards of accuracy, reliability, and compliance—paving the way for 10x to deliver transformative precision medicine insights.

At Atomic AI, we build artificial intelligence to pioneer new frontiers in drug discovery. Our unique R&D platform, an early version of which was featured on the cover of Science, provides new strategies to treat previously undruggable diseases by targeting RNA. We continue to advance this platform by developing new machine learning methods and unique foundation models fueled by our large-scale, in-house experimental data collection. We are an interdisciplinary team of scientists and engineers and believe our people are our greatest strength and the key to our success.

The opportunity

As a full-time Data Scientist on the Machine Learning team, you will work closely with scientists and engineers to apply and advance our technology platform for RNA structure prediction, target identification, and early-stage drug discovery. You will lead the curation of RNA-focused datasets for ML training and validation, discover statistical patterns in our large-scale datasets evaluating RNA structure and RNA-small molecule interactions, and devise and implement new strategies to test the accuracy of our ML models. Your analysis will guide the development of improved ML models and the targeted acquisition of new experimental data.

This is a hybrid position with three days in-person at our South San Francisco office.

Responsibilities:

• Provide RNA biology and RNA structure expertise on the ML team.
• Enable and apply our RNA-structure platform to prioritize RNA targets for small-molecule therapies and advance structure-based drug discovery.
• Generate insights from datasets on RNA structures and small molecule interactions (e.g. chemical probing, RNA-SM screens) by conducting statistical analyses, interpreting biological noise, and applying RNA domain expertise.
• Curate RNA datasets for training of ML models, help evaluate model performance, and provide directions for improvement.
• Inform scientific questions and ML model development in early-stage RNA drug discovery.
• Collaborate with the internal wetlab team and shape the design of experimental assays on RNA structure and RNA-SM interactions.
  
  

About you:

• Ph.D. in Computational Biology, Bioinformatics, Statistics, Biophysics, or related field, or equivalent experience.
• Expertise in RNA biology and biochemistry, RNA-protein interactions, and RNA structure.
• Proficiency in Python for data curation and analysis at scale, and fluency with libraries for data analysis (NumPy, pandas) and applied ML (scikit-learn).
• Strong programming background, familiarity with Unix and comfort with using external software packages.
• Strong foundation in statistics and experience with conducting statistical analysis of large-scale datasets.
• Excellent presentation and writing skills, able to clearly communicate technical information to colleagues.
  
  

Pluses:

• History of scientific achievement, e.g. as evidenced by publication of impactful papers.
• Conceptual understanding of ML model development and evaluation, and experience using ML models.
• Experience with computational structural biology tools for modeling RNA secondary and tertiary structure (e.g. Rosetta, AlphaFold, RNAfold).
• Understanding of RNA-SM interactions, including familiarity with structural properties of binding sites and experimental methods for evaluating binding.
• Proficiency with pipelines for next-generation sequencing dataset processing.
• Exposure to high throughput experimental assays for evaluating RNA structure and screening RNA-SM interactions.
  
  

Salary Range: $135,000/year to $180,000/year + equity + benefits. This range reflects variations in seniority, expertise, and skills.