Environmental Scientist/Industrial Hygienist 

Locations: Los Angeles or Orange County | ~50% field / 50% remote

Apex is seeking an environmental professional with experience in industrial hygiene to perform asbestos, lead-paint, mold/moisture intrusion, exposure assessment, abatement monitoring, and related industrial hygiene and EHS compliance projects across Southern California. 

Employee Benefits
This role offers competitive compensation and a robust benefits package, a balanced mix of fieldwork and report writing, company sponsorship for professional and vocational training, work from home opportunity, collaboration with other industrial hygiene, EHS and other experts, and continued  professional development and growth afforded by a rapidly growing national environmental consulting company.

Key Responsibilities

• Perform asbestos, lead-based paint (LBP), and microbial/moisture intrusion assessments, along with abatement oversight, with an approximate 50/50 split between field and office work
• Conduct safety and compliance assessments in accordance with regulatory standards and client requirements
• Support additional environmental services through cross-training, including:
  • Exposure assessments
  • Workplace safety evaluations
  • Stormwater compliance inspections
  • Soil and groundwater sampling
  • Noise and air monitoring
  • Aboveground Storage Tank (AST) inspections
• Execute work in alignment with project work plans, standard operating procedures (SOPs), and direction from project managers
• Manage scheduling and logistics across all project phases, from coordination and fieldwork through reporting
• Prepare clear, accurate, and technically sound client-ready reports using project-specific templates
• Collaborate with internal teams to support project delivery and ongoing professional development
• Maintain and proactively pursue relevant certifications, including 40-Hour HAZWOPER, CAC, and/or CSST

Qualifications

• 2+ years of professional experience conducting asbestos surveys and mold/moisture intrusion inspections as an AHERA-accredited inspector (in any state)
• Current AHERA certification required
• California Certified Asbestos Consultant (CAC) and/or Certified Site Surveillance Technician (CSST) preferred
• Bachelor’s degree in Environmental Science, Industrial Hygiene, Microbiology, or a related field

What We’re Looking For

• Self-motivated and dependable professional who can work effectively with limited supervision
• Strong technical writing and critical thinking skills
• Solid analytical and math skills for interpreting laboratory data and preparing reports
• Excellent attention to detail with the ability to manage multiple projects and deadlines
• Strong interpersonal skills and ability to collaborate in a team-oriented environment
• Physically capable of performing fieldwork and comfortable working in both field and office settings
• Commitment to safety and a strong understanding of safe work practices
• Interest in growing within industrial hygiene and expanding into broader environmental consulting services

Why you'll love working for us:

• Company-subsidized medical and dental.
• Company-paid life, short, and long-term disability.
• 401k match, tuition assistance, and more.
• Cross-training and the ability to work on a variety of projects.
• Performance-based bonuses or other incentives.
• Working with the best and brightest in the industry.
• 2,000+ employee national firm with 70+ locations across the US.

Req ID: 11507

Senior Data Scientist -  Experimentation & Measurement

San Diego, CA

Overview:

As a Senior Data Scientist on the Decision Science team within the Data Science, Analytics, & Enablement (DSAE) organization at PlayStation, you will take a leading role in designing and interpreting experiments that evaluate the impact of PS4 to PS5 user migration initiatives, growth marketing strategies, and broader campaign performance. This role is focused on advancing our experimentation practices—bringing statistical rigor, clear measurement strategies, and deep causal inference expertise to some of the most critical initiatives across PlayStation.

What You’ll Be Doing:

• Lead the design, execution, and interpretation of A/B tests and quasi-experiments to evaluate the impact of user migration initiatives (PS4 to PS5), growth marketing strategies, and campaign performance.
   
• Partner with cross-functional teams (product, engineering, marketing) to embed experimentation into development and iteration cycles.
   
• Serve as a thought leader on best practices for hypothesis development, metric selection, test structure, and results communication.
   
• Apply advanced causal inference methods when experimentation isn’t feasible or to inform test design and prioritization.
   
• Help define and contribute to centralized experimentation frameworks, tools, and documentation to scale best practices across the company.
   
• Independently extract, transform, and analyze data from complex systems using SQL, Python, and other analytics tools.
   
• Communicate findings clearly to technical and non-technical stakeholders, helping drive business decisions with rigor and clarity.
   
• Stay current on new methodologies in experimentation and causal analysis, and bring fresh perspectives to the team’s work.

Basic Requirements:
 

• Bachelor’s degree or equivalent.
   

• 5+ years of experience in a data science experimentation-focused role (3+ with PhD).
   

• Deep expertise in A/B testing and causal inference, including quasi-experimental methods.
   

• Proficiency in SQL for data extraction and transformation.
   

• Proficiency in Python, including statistical and data science libraries.
   

• Broad and applied knowledge of statistical techniques and machine learning modeling methods.
   

• Proven ability to influence product and business decisions through clear, actionable insights.
   

• Experience contributing to or developing experimentation frameworks, best practices, or internal tooling.
  

  Preferred Requirements:

• Master’s or PhD in Statistics, Economics, or Econometrics. Other degrees in quantitative disciplines may be considered.
   

• Bonus: Interest in or knowledge of video games, gaming platforms, or player behavior.

#LI-KC

Your next role as a Miracle Maker 

Maravai LifeSciences is seeking a #MiracleMaker to join our R&D team as a Scientist, Chemistry. As a Scientist, Chemistry you will be responsible for research and development activities as we continue to expand our product base. With knowledge and experience with mRNA capping reagent, oligonucleotide and messenger RNA this role will be at the forefront of exciting new therapeutic areas such as gene editing, gene replacement and self-amplifying vaccines research. 

How you will make an impact: 

• Interacts with R&D team to lead new nucleic acid related development projects  
• Interacts with production and analytical teams in troubleshooting and solving synthetic, purification and analytical problems  
• Documents research using lab notebooks, summarizes experimental data, creates PowerPoint presentations, and writes R&D reports  
• Contributes to generation, design and testing of the novel hypotheses and ideas related to the company’s expertise in the chemistry and applications of nucleic acids  
• Develops new analytical methodologies to characterize products manufactured at the company (including nucleosides, nucleotides, oligonucleotides and long DNA and RNA) using various chromatographic and spectroscopic techniques (such as HPLC, LC-MS, LC-MS) as well as immunoassay and molecular biology-based techniques  
• Collaborates with a broad team of RNA, DNA, chemistry, and oligonucleotide scientists, designing and performing laboratory research experiments needed to support RNA/DNA, chemistry, and oligonucleotide process development efforts  
• Closely collaborate with the internal QC group and external customers to support internal and external analytical method validation/qualification and method transfer  
• Maintains proper documentation of all experimental procedures and results  
• Writes/revises analytical methods, prepare technical reports and presentations which summarize procedures, study results, and provide data interpretation  
• Presents scientific results and observations to colleagues, management, and clients at internal and client meetings  
• Perform other functions and duties as required 

 The skills and experience that you will bring: 

• Master’s Degree/PhD Scientist with 2-5 years of research experience in oligonucleotide synthesis, purification, and characterization, ideally with oligonucleotide related industrial working experience  
• In-depth knowledge of oligonucleotide production processes, expertise in analytical method of purification and characterization of nucleic acids and their components  
• A solid background in biochemistry and biology of nucleic acids and their components is a plus  
• Demonstrated technical proficiency, and ability to effectively collaborate with others  
• Strong organizational skills a must  
• Excellent verbal and written communication skills a must  
• Proficient in MS Office (Word, Excel, PowerPoint)  

The anticipated salary range for this position is $120,000 - $130,000.  In addition, highly competitive long-term incentives in the form of company equity, bonus participation and company sponsored benefits are provided as part of the total compensation package.  The salary offer will depend on multiple factors which may include the successful candidate's skills, experience and other qualifications, as well as the location of the role.  

#LI-Onsite

About Tr1X

Tr1X is a private, clinical-stage biotechnology company focused on developing a novel class of regulatory T cell-based products to cure autoimmune and inflammatory diseases. Founded by industry experts, including the scientists who discovered Type 1 regulatory T (Tr1) cells, the company is developing a pipeline of off-the-shelf allogeneic cell therapies for autoimmune diseases with high unmet medical need. Our TRX cells are designed to mimic the function of naturally occurring Tr1 cells, which work to restore immune tolerance, stopping severe autoimmune and inflammatory disease in its tracks. Tr1X is the first company ever to use an allogeneic engineered Tr1 cell therapy in clinical trials. Tr1X is headquartered in San Diego, CA. For more information, please visit www.tr1x.bio.

Position Summary

The Senior Scientist, LNP Platform & Process Development (Scientist) is an experienced hands-on, lab-based, individual contributor that leads the design, development, and optimization of lipid nanoparticle (LNP) formulation and process development efforts supporting the Tr1X in vivo CAR-Treg platform. This individual plays a central role in developing and advancing the targeted lipid nanoparticle (tLNP) delivery systems from early research optimization through scalable, IND-enabling development.

This is a high-impact, foundational role within the company. The Scientist helps design and implement the LNP backbone of the platform and influence both short-term program execution and long-term manufacturability strategy. The Scientist brings deep hands-on expertise in LNP formulation and process development, strong analytical rigor, and the ability to thrive in a fast-paced startup environment.

Key Responsibilities

• Contribute to the design, development, and optimization of LNP formulations for mRNA delivery, including targeted LNP systems incorporating conjugated or functionalized lipids.
• Evaluate lipid composition, formulation parameters, and mixing conditions to optimize particle size, polydispersity, encapsulation efficiency, stability, release characteristics, and biological performance.
• Develop scalable, GMP-compatible manufacturing processes to support program advancement.
• Apply Quality by Design (QbD) principles and Design of Experiment (DoE) studies to study design and execution.
• Lead the development and optimization of analytical characterization methods (both in-house and at the external CDMO), including but not limited to DLS, fluorescence-based assays such as Ribogreen, HPLC/UPLC methods (CAD, UV, IP-RP, SEC, IEX), LC-MS, and endotoxin testing.
• Interpret analytical and stability data to establish meaningful correlations between physicochemical properties and biological function.
• Collaborate closely with platform biology teams to support in vitro and in vivo studies, prepare development reports and technical documentation, and contribute to technology transfer activities with external CDMO partners.
• Spearhead IND-enabling documentation and contribute to defining the long-term strategy for scalable LNP platform development.
• Perform other responsibilities as required based on business needs.

Required Qualifications & Experience

• Ph.D. in Chemical Engineering, Bioengineering, Pharmaceutical Sciences, Chemistry, or a related field with a minimum 4 years of relevant industry experience; or M.S. with 8+ years; or B.S. with 10+ years.
• Demonstrated in-depth expertise in LNP formulation and process development, including hands-on experience with microfluidic or scalable mixing technologies and downstream purification strategies such as TFF.
• Strong experience with analytical characterization of LNP systems and application of statistical design tools for process optimization.
• Highly organized, scientifically rigorous, and capable of independently driving projects while collaborating effectively in a multidisciplinary startup environment.
• Experience with mRNA therapeutics or nucleic acid delivery systems.
• Prior exposure to immunotherapy or cell therapy platforms preferred.
• Familiarity with regulatory expectations for CMC development and experience supporting technology transfer to external manufacturing partners preferred.
• Experience correlating formulation attributes with in vivo performance highly desirable.
  Ability to actively serve, collaborate, and develop relationships inside and outside the organization.
• Excellent written and oral communication skills.
• Strong analytical and problem-solving skills; great attention to detail and the ability to drive timely and fact-based decision making.
• Ability to function in a rapidly changing environment and handle multiple priorities.
• Demonstrated ability to partner, build trust, and cultivate positive working relationships with CDMOs.
• Experience with mRNA production and analytical quality control preferred.
• Effectively communicate changes and resolve issues with CDMOs.
• Lead and/or participate in cross functional development and manufacturing projects to ensure company objectives are met and exceeded.
• Ability to don and wear appropriate clean room attire and wear all required Personal Protective Equipment.

Other Requirements

• Legally authorized to work for any employer in the U.S.
• Position is on site in San Diego
• Travel may be required up to 10% of the time

The job responsibilities and requirements provided above are intended to describe the general nature of the work performed by individuals assigned to this job classification. It is not intended to be an exhaustive list of all duties and requirements. Tr1X retains the right to add, change, or delete duties, education, experience or any other requirements of the position at any time.

Working at Tr1X

At Tr1X, our team is united by a singular shared mission: to transform patients’ lives through breakthrough science. We are a group of skilled experts driven by urgency, innovation and a collaborative spirit. Our culture thrives on excellence, positivity, persistence and the agility to tackle new challenges head-on. With an unwavering commitment to patients, science and one another, we foster an environment where team members feel engaged, supported and empowered to make a meaningful impact. We envision a world where autoimmune diseases are not just being treated but are cured.

Base Pay Range Anticipated: $145,000 - $160,000

Tr1X considers a variety of factors to determine salary such as education, years of experience, time in the position level, training, knowledge, skills, geographic location, and the market value of the position.

Compensation and Benefits

Tr1X provides a fair and competitive total rewards program that includes base salary; discretionary annual target bonus; incentive stock options; 401(k) retirement plan with company contribution; health and welfare insurance plans for employees (and their families) that include medical, dental, vision, long-term and short-term disability, and life insurance; paid time off (PTO); and paid holidays.

Tr1X embraces a diverse, open, and inclusive environment and believes a strong culture connection is key to success. Tr1X is committed to fairness in recruitment, hiring, transfer, promotion or any other employment practice without regard to race, color, citizenship, national origin, ancestry, religion, sex, pregnancy, marital status, sexual orientation, gender, gender identity and expression, age, physical and medical disability, medical condition, genetic information, political affiliation, protected veteran status, or any other characteristic protected by law. If you are an individual needing assistance to complete an employment application or would like to request an accommodation, please contact the Human Resources department at careers@tr1x.bio.

Notice to Employment Agencies

The Tr1X talent acquisition program is managed through internal resources, and unsolicited referrals and resumes are not accepted from employment agencies, unless advance written authorization is granted from the human resources department. Tr1X shall not be liable for any fees arising from any unsolicited or unauthorized candidate information received relative to position vacancies.

Scientist III – NGS and Cellular Assays, Ingredient Discovery

Location: San Diego, CA (Onsite full-time required)

Summary

As a member of the Ingredient Innovation team, you will design, optimize, and execute high-throughput next-generation sequencing (NGS) assays to support the discovery of novel skincare ingredients. The successful candidate will work collaboratively with the bioinformatics team to design robust, reproducible assays and iterate experimental design based on sequencing outputs. This role will also lead the development and implementation of liquid handling robotics and automation solutions to scale NGS workflows. This is a highly collaborative role that will interact with bioinformatics, assay development, and AI/ML teams to bring novel, scientifically backed ingredients to market.

Essential Functions

• Design, test, and execute high-throughput NGS workflows including human cell culture, RNA extraction, RNA-seq library preparation, quality control, and sequencing on the Illumina platform
• Develop and optimize NGS library prep and cell-based protocols to enhance assay performance
• Collaborate with bioinformatics teams to interpret sequencing outputs, troubleshoot data quality issues, and iterate on experimental design
• Maintain rigorous sample tracking, QC metrics, and documentation to ensure data integrity and reproducibility
• Develop and implement liquid handling robotics and automation platforms for NGS library preparation, sample manipulations, and other high-throughput workflows
• Mentor junior scientists and associates on NGS best practices, cell culture techniques, and robotics operation 

Education and Experience

• PhD with 4 years of experience OR MS with 10 years of experience OR BS with 12 years of wet-lab experience in NGS assay development or relevant field
• At least 5 years of experience in developing, optimizing, running, and troubleshooting challenging NGS assays
• Proficiency with liquid handling robotics and automation scripting
• Proficiency in mammalian cell culture, drug discovery, and/or cell biology techniques (e.g., flow cytometry, fluorescent imaging, luciferase reporter assay, ELISA) is a plus
• Strong organizational skills with experience managing multiple projects simultaneously in a fast-paced environment

Essential Physical Characteristics

The physical characteristics described here are representative of those that must be met by an employee to successfully perform the essential functions of this position. Reasonable accommodations may be made to enable qualified individuals with disabilities to perform the essential functions of a job, on a case-by-case basis. 

• Continuous upward and downward flexion of the neck. 
• Frequent: sitting, repetitive use of hands to operate computers, printers and copiers. 
• Frequently uses hands to feel objects or control tools (e.g. pipetting).  Laboratory operations require dexterity and care to perform studies as required.
• Occasional: walking, standing, climbing stairs, bending and twisting of neck, bending and twisting of waist, squatting, simple grasping, reaching above and below shoulder level, and occasional lifting and carrying of files or material weighing up to 50 pounds.
• Must be willing to work with biohazardous agents (up to BSL2) and chemicals.
• The R&D laboratory will result in exposure to hot and cold temperatures, noise, fumes, limited dust, and oily coolants.
• The performance of this position will present exposure to an industrial environment and requires support and compliance with the published Company PPE policy including but not limited to the use of personal protective equipment such as safety glasses with side shields, appropriate attire, safety shoes, hard hat, hearing protection, etc.

Condition of Employment

As part of Debut’s pre-employment process, prospective candidates will undergo a background check prior to beginning employment. Additional types of background investigations may be conducted based on the job-related activities of the position.

Debut is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status.

Salary: $110,000 - $140,000

What You Will Contribute To Altos

As part of our team, you will help to accelerate and optimize our progress in developing unified, multi-modal generative foundation models for multiscale biology. You will be an integral part of our multidisciplinary teams building the computational platforms that will enable Altos to achieve its mission.

In this role, you will partner and collaborate with other multidisciplinary Scientists and Engineers across the Institute of Computation to design, build, and scale state-of-the-art foundation models that tackle biological questions and aid in the discovery of novel interventions for aging and disease. You will focus on the synthesis of unstructured multimodal signals with the structured relational data and knowledge graphs that represent biological reality.

The successful candidate will thrive in a fast-paced environment that stresses teamwork, transparency, scientific excellence, originality, and integrity.

Responsibilities

As a Staff Machine Learning Scientist, you will use your experience to focus on designing, developing, and evaluating state-of-the-art foundation models, at scale, to benefit the research.

• Pre-train and fine-tune large-scale machine learning systems using multimodal biological data, natural language, and structured relational inputs.   
• Architect and implement novel hybrid models that integrate Large Language Models (LLMs) with Graph Neural Networks (GNNs) for multi-hop reasoning over biological knowledge graphs .
• Develop Relational Foundation Models (RFMs) that enable zero-shot predictive tasks over heterogeneous, multi-table biological datasets.   
• Lead the design of efficient data loading strategies and distributed training recipes (e.g., FSDP, DeepSpeed) to train models across multiple GPU nodes.   
• Gain insights into model performance based on theory, deep research, and the mathematical underpinnings of set-invariant and graph-structured architectures .
• Apply strong coding experience to model development and deployment, ensuring research prototypes transition into reliable, scalable production systems.
• Stay up-to-date on the latest developments in deep learning—including native early-fusion and Mixture-of-Experts (MoE) architectures—and apply this knowledge to Altos' research .
• Mentor junior staff while maintaining a high individual technical contribution to the core research ecosystem and peer-reviewed publications.

Who You Are  

We are looking for someone who is:

• Excited about the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities.
• Highly collaborative in mindset and ways of working across research and engineering boundaries.
• Self-motivated to drive and deliver on long-term technical projects and scientific goals.
• Demonstrates the desire to grow professionally and expand their skillset in biology, machine learning, and/or drug development.
• Able to communicate and explain the design, results, and impact of complex AI architectures to both scientific and non-scientific staff.
• Keen to contribute to seminars and scientific initiatives within Altos and the broader AI research community.

Minimum Qualifications

• PhD in Computer Science, Machine Learning, or a similar quantitative field with 5+ years of relevant work experience in academic or industry settings.
• Prior experience in developing and implementing novel generative AI models, specifically in multimodal integration, GraphRAG, or relational deep learning .
• Deep understanding of Machine Learning principles and how they apply to diverse architectures like Transformers, GNNs, and diffusion models .
• Very strong programming skills in Python and deep learning libraries (e.g., PyTorch, JAX, Hugging Face Transformers/Accelerate).   
• Proven experience with multi-GPU and distributed training at scale (e.g., DDP, FSDP, DeepSpeed, Megatron, or Ray).   
• Strong track record of published, peer-reviewed innovative AI/ML research at top-tier conferences (NeurIPS, ICML, ICLR, CVPR).

Preferred Qualifications

• Familiarity with tabular foundation models (e.g., TabPFN) and in-context learning strategies for structured data .
• Specific experience in native multimodal modeling (early-fusion) or the synthesis of LLMs and Knowledge Graphs .
• Track record of ML applied to biological data, such as NGS data (RNA-seq, ATAC-seq), biological imaging (microscopy, IF), or spatial transcriptomics.
• Experience in optimizing large-scale inference via quantization, distillation, or memory-efficient attention mechanisms.

The salary range for Redwood City, CA:

• Scientist I, Machine Learning: $200,900 - $257,500
• Scientist II, Machine Learning: $226,200 - $290,000
• Senior Scientist I, Machine Learning: $257,400 - $330,000

The salary range for San Diego, CA:

• Scientist I, Machine Learning: $179,400 - $230,000
• Scientist II, Machine Learning: $212,900 - $273,000
• 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.

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.

What You Will Contribute To Altos

Altos Labs is building a world-class AI ecosystem to solve the most complex problems in human biology. You will directly design and build high-performance, scalable solutions that unify high-dimensional biomedical imaging with molecular and language data.

By implementing large-scale multimodal data fusion, you will move beyond simple image analysis to create predictive models that map across biological domains. You will be hands-on with the data and the code, collaborating with our engineering team to ensure these models are scalable, efficiently trainable on distributed cloud infrastructure, and accessible to our global research community.

Responsibilities

• Model Development: Design, code, and train large-scale foundation models (e.g., Vision Transformers, Multimodal LLMs) that can embed spatial data and integrate multiple modalities.
• Hands-on Data Fusion: Implement innovative cross-domain mapping and fusion strategies to synchronize heterogeneous biological datasets.
• Scaling & Training: Build and manage high-performance ML pipelines capable of processing petabyte-scale image repositories and multi-omics streams in a cloud environment.
• Technical Collaboration: Work directly in the trenches with experimental scientists and software engineers to translate biological complexity into performant code and reliable distributed systems.

Who You Are

We are looking for a technical specialist who thrives on solving "unsolvable" problems through code and rigorous experimentation. We are open to candidates at the Scientist I, Scientist II, or Senior Scientist level based on technical expertise.

Minimum Qualifications

• Education: PhD in Computer Science, AI/ML, Biomedical Engineering, or a related quantitative field.
• Hands-on CV Expertise: Deep experience building and deploying modern Computer Vision architectures (Vision Transformers, U-Nets, Self-Supervised Learning).
• Distributed Training: Proven experience training and fine-tuning large models at scale using frameworks like PyTorch Distributed, DeepSpeed, or Jax.
• Programming Mastery: Expert-level Python skills, with a focus on building production-ready machine learning code and large-scale data management systems.
• Scientific Contributions: A track record of technical contributions via high-impact publications (CVPR, ICCV, NeurIPS, etc.) or significant contributions to open-source ML frameworks.

Preferred Qualifications

• Direct experience with Multimodal Fusion (e.g., aligning image embeddings with transcriptomic or proteomic data).
• Proficiency with cloud-native AI tools (AWS/GCP, Kubernetes, Docker) and building automated MLOps workflows.
• Experience handling the unique noise and sparsity of biological data.

The salary range for Redwood City, CA:

• Scientist I, Machine Learning: $200,900 - $257,500
• Scientist II, Machine Learning: $226,200 - $290,000
• Senior Scientist I, Machine Learning: $257,400 - $330,000

The salary range for San Diego, CA:

• Scientist I, Machine Learning: $179,400 - $230,000
• Scientist II, Machine Learning: $212,900 - $273,000
• Senior Scientist I, Machine Learning: $239,500 - $307,000

#LI-NN1

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

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.

What You Will Contribute To Altos

As part of our team, you will help to accelerate and optimize our progress in developing multi-modal generative foundation models for multiscale biology. We are open to hiring either a Machine Learning Scientist or Machine Learning Engineer.

In either 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 partner and collaborate with other Machine Learning Scientists and Engineers across the Institute of Computation to contribute to the Altos research and translation ecosystem. Focussing on designing and building state-of-the-art multimodal foundation models that tackle biological questions and aid in the discovery of novel interventions for aging and disease. 

The successful candidate will thrive in a fast-paced environment that stresses teamwork, transparency, scientific excellence, originality, and integrity. 

Responsibilities

Machine Learning Engineer

• As a Machine Learning Engineer you will focus on building, deploying and optimizing machine learning models at scale. 
• Pre-train and fine-tune large-scale machine learning systems using multimodal biological data and natural language inputs.
• Develop efficient data loading strategy and performance tracking to train large models with distributed training across multiple nodes 
• Ability to apply software engineering skills to develop reliable, scalable, performant distributed systems in a cloud environment.

Machine Learning Scientist

• The ideal candidate will be able to use their experience to focus on designing, developing and evaluating state of the art foundation models, at scale, to benefit the research.
• Pre-train and fine-tune large-scale machine learning systems using multimodal biological data and natural language inputs.
• You will be able to gain insights, based on theory, deep research and the mathematical underpinnings of your work.
• Be experienced in using AI as a tool to accelerate your research.
• Can apply strong coding experience to model development using existing languages(s) and framework(s)

Who You Are

We are looking for someone who is :

• Excited about the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities and how they can contribute
• Highly collaborative in mindset and ways of working
• Self-motivated to drive and deliver on projects and goals
• Demonstrates the desire to grow professionally and expand their skillset and knowledge;  is keen to learn more about biology, computational science, and drug development.
• Ability to communicate and explain the design, results, conclusions and the impact of their work to both scientific and nonscientific staff.
• Is able to stay up-to-date on the latest developments in deep learning and apply knowledge to their work.
• Keen to take the opportunity to contribute to seminars and other scientific initiatives within Altos and the broader scientific community.

Minimum Qualifications

Machine Learning Engineer

• MS in Computer Science, Statistics, Machine Learning, Artificial Intelligence, or a related discipline
• 0-5 years of relevant work experience in either an academic or industry setting
• Very strong programming skills, including experience with Python and deep learning libraries (PyTorch, Hugging Face Transformers, H-F Datasets, H-F Accelerate)
• Ideally, experience in a distributed training framework, like DDP, FSDP, Deepspeed, Megatron, or HuggingFace Accelerate, Ray.
• Expertise in a subset of the following: transformers, natural language processing, multi-modality in language and/or in biology, diffusion models.

Machine Learning Scientist

• PhD in Computer Science / Machine Learning or similar fields 
• 0-5 years of relevant work experience in either an academic or industry setting.
• Prior experience in developing and implementing novel generative AI models in a subset of the following: transformers, multi-modality, diffusion models.
• Can demonstrate a deep understanding and expertise of Machine Learning Principles and how they apply to different models  
• Very strong programming skills, including experience with Python and deep learning libraries (PyTorch, Hugging Face Transformers, H-F Datasets, H-F Accelerate)
• Strong track record of published peer reviewed innovative AI/ML research 
• Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar;
• Experience with multi-GPU and distributed training at scale;

Preferred Qualifications

• Familiarity with multimodal data integration, including early and/or late fusion strategies.
• Track record of ML applied to NGS data (e.g.RNA-seq, ATAC-seq, ChIP-seq, DNA methylation), biological imaging modalities (e.g. microscopy, H&E, IF), and/or spatial transcriptomics.

The salary range for Machine Learning Engineer position in San Diego

• Machine Learning Engineer I: $140,000 - $179,500
• Machine Learning Engineer II: $158,300 - $203,000

The salary range for Machine Learning Engineer position in Redwood City

• Machine Learning Engineer I: $152,600 - $195,600
• Machine Learning Engineer II: $174,200 - $223,300

The salary range for Machine Learning Scientist position in San Diego

• Scientist I, Machine Learning: $179,400 - $230,000
• Scientist II, Machine Learning: $212,900 - $273,000

The salary range for Machine Learning Scientist  position in Redwood City

• Scientist I, Machine Learning: $200,900 - $257,500
• Scientist II, Machine Learning: $226,200 - $290,000

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

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.

#LI-NN1

What You Will Contribute To Altos

As a Senior or Principal Machine Learning Scientist, you will play a prominent role in developing generative AI/ML models for multi-modal, multiscale biology from virtual cells to agentic target assessment.  We are looking for a hands-on, creative, and collaborative individual to join our multidisciplinary team of scientists and engineers focused on transforming how we treat aging and disease. The successful candidate will thrive in a fast-paced environment that emphasizes teamwork, transparency, scientific excellence, originality, rigor, and integrity.

Responsibilities

• Pioneer novel machine learning methodologies and statistical frameworks (e.g., generative models, causal inference, diffusion models, and advanced transformer architectures) to address fundamental challenges in cell health and rejuvenation
• Contribute to setting the long-term technical vision and research strategy for a core domain (e.g., multi-modal data fusion, perturbation modeling) within the Institute of Computation
• Translate your deep understanding of the mathematical and theoretical underpinnings of cutting-edge AI research into high-impact applications
• Design, implement, and optimize large-scale machine learning systems using modern frameworks (e.g., PyTorch, JAX) and  agile practices
• Develop and manage efficient distributed training strategies across multiple GPUs and compute clusters to handle terabytes of multi-modal biological data
• Develop robust approaches for multi-modal data integration and cross-domain mapping to extract actionable biological insights
• Apply computational thinking to solve problems in drug target identification, compound assessment, and prediction of cellular perturbation responses
• Lead the full ML development lifecycle from theoretical conception and data strategy through model development, training, and evaluation
• Act as a key technical mentor to Machine Learning Scientists and Engineers, raising the bar for scientific rigor and model robustness across the organization.

Who You Are

• Proven track record leveraging machine learning to solve real-world problems;
• Expertise in one or more of the following: generative models, language models, computer vision, bayesian inference, causal reasoning & inference, transfer & multi-task learning, diffusion models, graph neural networks, active learning, cooperative agents
• Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar
• Experience with multi-GPU and distributed training at scale
• A team player who thrives in collaborative environments and is committed to enabling colleagues to reach their full potential through giving and requesting feedback focussed on professional growth
• Able to advise others across the wider function / company on cutting edge practices and approaches to enable the science / research. Desire to constantly expand your skillset and knowledge. Keen to learn more about biology, computational science, and medicine;
• Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities.

Minimum Qualifications

• Ph.D. in Machine Learning, Computer Science, Artificial Intelligence, Statistics, or a related quantitative field, demonstrating a deep theoretical foundation in ML/AI.
• 6+ years of of relevant post-PhD work experience in either an academic or industry setting
• Proven experience developing and applying complex machine learning models, preferably with a significant portion of that time spent in a fast-paced industry or translational research environment.
• A strong track record of leading and publishing innovative, peer-reviewed research in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR) or high-impact scientific journals.
• Excellent scientific communication skills: verbally and in writing; with computational and non-computational audiences, in informal 1-1 settings, team meetings, and formal seminars
• Expertise in several of the following: deep learning, reinforcement learning, generative models, language models, computer vision, Bayesian inference, causal reasoning & inference, transfer & multi-task learning, graph neural networks, active learning, hybrid mechanistic/ML models
• Proven experience applying sophisticated ML techniques to molecular and cell biological data sets (e.g., NGS, spatial omics, bioimaging).

Preferred Qualifications

• Experience in cell health and rejuvenation related research area
• Experience in the application of machine learning methods to biological data
• Experience in computational approaches to drug discovery
• Experience with software development methodologies and open-source software

The salary range for Redwood City, CA:

• Senior Scientist I, Machine Learning: $257,400 - $330,000
• Senior Scientist II, Machine Learning: $290,900 - $373,000
• Principal Scientist, Machine Learning: $330,800 - $424,100

The salary range for San Diego, CA:

• Senior Scientist I, Machine Learning: $239,500 - $307,000
• Senior Scientist II, Machine Learning: $262,100 - $336,000
• Principal Scientist, Machine Learning: $312,100 - $400,100

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

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.

#LI-NN1

What You Will Contribute To Altos

As a Senior or Principal Machine Learning Scientist, you will play a prominent role in developing generative AI/ML models for multi-modal, multiscale biology from virtual cells to agentic target assessment.  We are looking for a hands-on, creative, and collaborative individual to join our multidisciplinary team of scientists and engineers focused on transforming how we treat aging and disease. The successful candidate will thrive in a fast-paced environment that emphasises teamwork, transparency, scientific excellence, originality, rigor, and integrity.

Responsibilities

• Pioneer novel machine learning methodologies and statistical frameworks (e.g., generative models, causal inference, diffusion models, and advanced transformer architectures) to address fundamental challenges in cell health and rejuvenation
• Contribute to setting the long-term technical vision and research strategy for a core domain (e.g., multi-modal data fusion, perturbation modeling) within the Institute of Computation
• Translate your deep understanding of the mathematical and theoretical underpinnings of cutting-edge AI research into high-impact applications
• Design, implement, and optimize large-scale machine learning systems using modern frameworks (e.g., PyTorch, JAX) and  agile practices
• Develop and manage efficient distributed training strategies across multiple GPUs and compute clusters to handle terabytes of multi-modal biological data
• Develop robust approaches for multi-modal data integration and cross-domain mapping to extract actionable biological insights
• Apply computational thinking to solve problems in drug target identification, compound assessment, and prediction of cellular perturbation responses
• Lead the full ML development lifecycle from theoretical conception and data strategy through model development, training, and evaluation
• Act as a key technical mentor to Machine Learning Scientists and Engineers, raising the bar for scientific rigor and model robustness across the organization.

Who You Are

• Proven track record leveraging machine learning to solve real-world problems;
• Expertise in one or more of the following: generative models, language models, computer vision, bayesian inference, causal reasoning & inference, transfer & multi-task learning, diffusion models, graph neural networks, active learning, cooperative agents
• Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar
• Experience with multi-GPU and distributed training at scale
• A team player who thrives in collaborative environments and is committed to enabling colleagues to reach their full potential through giving and requesting feedback focussed on professional growth
• Able to advise others across the wider function / company on cutting edge practices and approaches to enable the science / research. Desire to constantly expand your skillset and knowledge. Keen to learn more about biology, computational science, and medicine;
• Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities.

Minimum Qualifications

• Ph.D. in Machine Learning, Computer Science, Artificial Intelligence, Statistics, or a related quantitative field, demonstrating a deep theoretical foundation in ML/AI.
• 6+ years of of relevant post-PhD work experience in either an academic or industry setting
• Proven experience developing and applying complex machine learning models, preferably with a significant portion of that time spent in a fast-paced industry or translational research environment.
• A strong track record of leading and publishing innovative, peer-reviewed research in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR) or high-impact scientific journals.
• Excellent scientific communication skills: verbally and in writing; with computational and non-computational audiences, in informal 1-1 settings, team meetings, and formal seminars
• Expertise in several of the following: deep learning, reinforcement learning, generative models, language models, computer vision, Bayesian inference, causal reasoning & inference, transfer & multi-task learning, graph neural networks, active learning, hybrid mechanistic/ML models
• Proven experience applying sophisticated ML techniques to molecular and cell biological data sets (e.g., NGS, spatial omics, bioimaging).

Preferred Qualifications

• Experience in cell health and rejuvenation related research area
• Experience in the application of machine learning methods to biological data
• Experience in computational approaches to drug discovery
• Experience with software development methodologies and open-source software

The salary range for Cambridge, UK:

• Senior Scientist I, Machine Learning: £115,600 - £152,100
• Senior Scientist II, Machine Learning: £131,900 - £173,500
• Principal Scientist, Machine Learning: £173,700 - £228,600

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

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.

#LI-NN1

What You Will Contribute to Altos

This is an opportunity to join the state-of-the-art Virtual Cell team that recently won the Generalist prize in the ARC Virtual Cell Challenge. Here you will help to accelerate and optimize our progress in developing multi-modal generative foundation models for multiscale biology. 

In this role, you will be an integral part of our multidisciplinary teams enabling Altos to achieve its mission. You will partner and collaborate with other Machine Learning Scientists and Engineers, as well as other computational scientists and biologists, across the Institute of Computation to contribute to the Altos research and translation ecosystem. This role is focused on improving our state-of-the-art “virtual cell” models, encompassing gene and protein modeling, imaging, and other modalities to aid in the discovery of novel interventions for aging and disease. 

The successful candidate will thrive in a fast-paced environment that emphasises/emphasizes *please spell differently for UK/US teamwork, transparency, scientific excellence, originality, and integrity.

Responsibilities

• Use your experience to focus on designing, developing and evaluating state of the art foundation and focused models, at scale, to advance the Altos mission
• Pre-train and fine-tune large-scale machine learning systems using multimodal biological data and prior knowledge inputs.
• Pioneer novel machine learning methodologies and statistical frameworks (e.g., generative models,  diffusion/flow matching models, and advanced transformer architectures) to address fundamental challenges in cell health and rejuvenation
• Design, implement, and optimize large-scale machine learning systems using modern frameworks (e.g., PyTorch, JAX), AI-assisted coding, and agile practices
• Develop and manage efficient distributed training strategies across multiple GPUs and compute clusters to handle terabytes of multi-modal biological data
• Develop robust approaches for multi-modal data integration and cross-domain mapping to extract actionable biological insights
• Participate in the full ML development lifecycle from theoretical conception and data strategy through model development, training, and evaluation

Who You Are

• Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities
• Highly collaborative in mindset and ways of working
• Self-motivated to drive and deliver on projects and goals
• Focused on professional growth and expanding you skillset and knowledge
• Able to communicate and explain the design, results, conclusions and the impact of their work to both scientific and nonscientific staff.
• Able to stay up-to-date on the latest developments in deep learning and apply knowledge to their work.
• Keen to take the opportunity to contribute to seminars and other scientific initiatives within Altos and the broader scientific community.

Minimum Qualifications

• Ph.D. in Machine Learning, Computer Science, Artificial Intelligence, Statistics, or a related quantitative field, demonstrating a deep theoretical foundation in ML/AI.
• Relevant work experience in either an academic or industry setting.
• Prior experience in developing and implementing novel generative AI models in a subset of the following: transformers, multi-modality, diffusion/flow matching models.
• Can demonstrate a deep understanding and expertise of Machine Learning Principles and how they apply to different models  
• Proven experience developing and applying complex machine learning models, preferably with a significant portion of that time spent in a fast-paced industry or translational research environment.
• Very strong programming skills, including experience with Python and deep learning libraries (PyTorch, Hugging Face Transformers, H-F Datasets, H-F Accelerate)
• Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar;
• Experience with multi-GPU and distributed training at scale;

Preferred Qualifications

• Strong track record of published peer reviewed innovative AI/ML research 
• Experience in cell health and rejuvenation related research area
• Experience in the application of machine learning methods to biological data
• Experience in computational approaches to drug discovery
• Experience with software development methodologies and open-source software

The salary range for Cambridge, UK:

• Scientist I, Machine Learning: £74,900 - £98,500
• Scientist II, Machine Learning: £107,900 - £142,000
• Senior Scientist I, Machine Learning: £115,600 - £152,100

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

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.

#LI-NN1

What You Will Contribute To Altos

This is an opportunity to join the state-of-the-art Virtual Cell team that recently won the Generalist prize in the ARC Virtual Cell Challenge. Here you will help to accelerate and optimize our progress in developing multi-modal generative foundation models for multiscale biology. 

In this role, you will be an integral part of our multidisciplinary teams enabling Altos to achieve its mission. You will partner and collaborate with other Machine Learning Scientists and Engineers, as well as other computational scientists and biologists, across the Institute of Computation to contribute to the Altos research and translation ecosystem. This role is focused on improving our state-of-the-art “virtual cell” models, encompassing gene and protein modeling, imaging, and other modalities to aid in the discovery of novel interventions for aging and disease. 

The successful candidate will thrive in a fast-paced environment that emphasises/emphasizes *please spell differently for UK/US teamwork, transparency, scientific excellence, originality, and integrity.

Responsibilities

• Use your experience to focus on designing, developing and evaluating state of the art foundation and focused models, at scale, to advance the Altos mission
• Pre-train and fine-tune large-scale machine learning systems using multimodal biological data and prior knowledge inputs.
• Pioneer novel machine learning methodologies and statistical frameworks (e.g., generative models,  diffusion/flow matching models, and advanced transformer architectures) to address fundamental challenges in cell health and rejuvenation
• Design, implement, and optimize large-scale machine learning systems using modern frameworks (e.g., PyTorch, JAX), AI-assisted coding, and agile practices
• Develop and manage efficient distributed training strategies across multiple GPUs and compute clusters to handle terabytes of multi-modal biological data
• Develop robust approaches for multi-modal data integration and cross-domain mapping to extract actionable biological insights
• Participate in the full ML development lifecycle from theoretical conception and data strategy through model development, training, and evaluation

Who You Are

• Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities
• Highly collaborative in mindset and ways of working
• Self-motivated to drive and deliver on projects and goals
• Focused on professional growth and expanding you skillset and knowledge
• Able to communicate and explain the design, results, conclusions and the impact of their work to both scientific and nonscientific staff.
• Able to stay up-to-date on the latest developments in deep learning and apply knowledge to their work.
• Keen to take the opportunity to contribute to seminars and other scientific initiatives within Altos and the broader scientific community.

Minimum Qualifications

• Ph.D. in Machine Learning, Computer Science, Artificial Intelligence, Statistics, or a related quantitative field, demonstrating a deep theoretical foundation in ML/AI.
• Relevant work experience in either an academic or industry setting.
• Prior experience in developing and implementing novel generative AI models in a subset of the following: transformers, multi-modality, diffusion/flow matching models.
• Can demonstrate a deep understanding and expertise of Machine Learning Principles and how they apply to different models  
• Proven experience developing and applying complex machine learning models, preferably with a significant portion of that time spent in a fast-paced industry or translational research environment.
• Very strong programming skills, including experience with Python and deep learning libraries (PyTorch, Hugging Face Transformers, H-F Datasets, H-F Accelerate)
• Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar;
• Experience with multi-GPU and distributed training at scale;

Preferred Qualifications

• Strong track record of published peer reviewed innovative AI/ML research 
• Experience in cell health and rejuvenation related research area
• Experience in the application of machine learning methods to biological data
• Experience in computational approaches to drug discovery
• Experience with software development methodologies and open-source softwar

The salary range for Redwood City, CA:

• Scientist I, Machine Learning: $200,900 - $257,500
• Scientist II, Machine Learning: $226,200 - $290,000
• Senior Scientist I, Machine Learning: $257,400 - $330,000

The salary range for San Diego, CA:

• Scientist I, Machine Learning: $179,400 - $230,000
• Scientist II, Machine Learning: $212,900 - $273,000
• Senior Scientist I, Machine Learning: $239,500 - $307,000

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

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.

#LI-NN1

We are looking for a Senior Algorithm Scientist to develop and validate the next generation of health sensing algorithms at Oura. Health sensing algorithms underpin the suite of features we offer to our members. As an algorithm scientist, your work will have a wide ranging impact and provide the foundation for new insights delivered to millions of Oura members around the world.

What you will do: 

• Contribute to the research, development and deployment of signal processing and machine learning algorithms for Oura features/products based on a range of sensing modalities
• Conduct early stage exploratory research to identify and characterize new potential sensing features and functionality. Develop proof-of-concept features and work with a cross-functional team to take these from proof-of-concept to a commercialized product
• Design and support internal and external data collection studies to develop, evaluate, benchmark and improve new biomarkers and algorithms and to evaluate the signal quality of hardware and firmware prototypes

• Develop and maintain internal signal evaluation tools and libraries to help Oura’s hardware and firmware teams optimize current and next-generation products

• Document, summarize, and present data analysis and algorithm performance results with concrete actionable recommendations for a broad audience on a regular basis
• Support the incorporation of new sensing modalities into next-generation hardware by running feasibility studies and providing scientifically-backed guidance to other teams (hardware, firmware, product, etc)
• Coordinate with cross-functional teams and overseas stakeholders

Requirements

We would love to have you on our team if you have:

• PhD degree with three years of work experience OR MSc degree with five years of work experience in biomedical engineering, electrical engineering, neural engineering or a related field
• 3+ years of solid programming skills in Python and experience with code collaboration tools (git, peer review, etc)
• Experience with signal processing methods and time-series analysis (FIR/IIR filters, Kalman filtering, adaptive filtering, stochastic processes, etc) 
• Experience with biosignal sensing and wearable hardware (including hardware prototypes) is a plus
• A pragmatic can-do attitude and delivery-focused mindset: you can move quickly and prioritize effectively
• Flexible schedule and good asynchronous communication skills to work with Oura’s Finnish teams (early morning meetings two to three times a week)
• This role is based in San Diego, with at least three days in office (at our Carmel Mountain location).

Benefits

At Oura, we care about you and your well-being. Everyone here at Oura has a ring of their own and we are continually looking to improve employee health.

What we offer:

• Competitive salary and equity packages
• Health, dental, vision insurance, and mental health resources
• An Oura Ring of your own plus employee discounts for friends & family
• 20 days of paid time off plus 13 paid holidays plus 8 days of flexible wellness time off
• Paid sick leave and parental leave

Oura takes a market-based approach to pay, which may vary depending on your location. US locations are categorized into tiers based on a cost of labor index for that geographic area. While most offers will be closer to the starting range, successful candidates' pay will be determined based on job-related skills, experience, qualifications, work location, internal peer equity, and market conditions. These ranges may be modified in the future.

• Region 2: $158,950 - $187,000

A recruiter can determine your zones/tiers based on your US location.

We are not considering candidates residing in the following states: Alaska (AK), Delaware (DE), Iowa (IA), Mississippi (MS), Missouri (MO), Nebraska (NE), South Dakota (SD), Vermont (VT), West Virginia (WV), and Wisconsin (WI)

Senior Scientist Biophysics

About the Role

We are seeking an experienced, self-starter, and highly motivated Biophysics Senior Scientists to join our San Diego team to deliver high-quality results and drive small molecule drug discovery. In this role, you will be a key contributor to our small‑molecule discovery engine, designing and executing biophysical strategies that identify high‑quality hits, elucidate mechanisms of action, and accelerate lead optimization. You will work at the center of multidisciplinary project teams, partnering closely with chemistry, biology, and lead discovery to advance programs toward development candidates. The successful candidate will propose, design, and implement new biophysical assays and hit ID approaches (ie. SPR, MST, DSF, NMR), characterize protein-small molecule and protein-protein interactions, and uncover mechanistic insights of our drug discovery targets and lead molecules. You will provide expert interpretation of biophysical results and use data analysis and visualization tools to integrate data with the broader set of data generated at Treeline to drive program decisions.

Responsibilities

• Propose, design, develop, and execute biophysical assays to support hit identification, hit-to-lead, and lead optimization activities.
• Establish robust SPR assays for small‑molecule interaction analysis, including hit triage, affinity/kinetic characterization, and mechanism-of-action studies.
• Efficiently utilize a suite of biophysical techniques to advance drug discovery: primarily SPR but also including DSF, DLS, and others through in-house and CRO capabilities.
• Employ biophysical methods to mechanistically deconvolute the molecular mechanism of action of small molecule hits.
• Effectively analyze, interpret, and communicate biophysical data as a subject matter expert and biophysics representative on project teams.
• In collaboration with chemistry, biology, lead discovery, and medicine design, characterize and establish SAR to rapidly drive the hit-to-lead process.
• Propose and evaluate new approaches and technologies.
• Provide scientific leadership, mentorship, and cross-functional partnership within a dynamic matrixed environment.

Required Qualifications

• PhD in Biophysics, Biochemistry, Chemistry, Chemical Biology or related discipline with 2-3 years of relevant postdoctoral training.
• 4+ years of biotech/pharma experience with a demonstrated impact in hit identification, hit-to-lead, and lead optimization for small-molecule programs.
• Expertise in quantitative biophysical assay development, especially SPR for small‑molecule drug discovery. Hands-on experience characterizing protein–ligand interactions, including affinity, kinetics, stoichiometry, and mechanism.
• Strong theoretical and practical knowledge of an array of biophysical methods with proven hands-on expertise applying biophysics for interaction analysis. Expertise with MST/SS, DSF, MS, or NMR are a plus.
• Demonstrated ability to troubleshoot complex assays, work with challenging proteins, and deliver high‑quality, reproducible data.
• Excellent communication, data visualization, and interpersonal skills, with a track record of effective collaboration on multidisciplinary teams.

Preferred Qualifications

• Ability to lead in a matrix environment, and for example, act as point of contact on project teams.
• Experience with fragment-based lead discovery, covalent lead discovery, and DEL are a plus.
• Strong hands-on biochemistry experience or expertise in enzymology.
• Working knowledge of adjacent disciplines (biochemistry, structural biology, protein purification, biology, chemistry).
• Experience in working with challenging proteins.
• Experience working with CROs.

This position is classified as exempt. The anticipated annual base salary range for candidates who will work in San Diego is $151,694 to $174,363. The final base salary offered to the successful candidate will be dependent upon several factors that may include but are not limited to the type and length of experience within the job, education, and other factors. Treeline Biosciences is a multi-state employer, and this salary range may not reflect positions that work in other cities or states.

Recruitment fraud statement

Please be aware of recruitment fraud and related job scams, where scammers present themselves as recruiters but are seeking to steal money or personal information. Keep the following in mind to protect yourself:

• Treeline Biosciences will never ask for money from you as part of our recruitment process. Do not provide bank details or pay somebody for the promise of a job at Treeline.
• We do not conduct interviews through RingCentral, Skype or Telegram. 
• Our job openings are first posted to treeline.bio/careers. If you locate a listing for a Treeline job on another site, please ensure it is also posted on our careers website.
• You can find more information about job scams at consumer.ftc.gov/articles/job-scams.
• To report job scams, head to ReportFraud.ftc.gov.

What You Will Contribute To Altos

An exciting opportunity is available to join Altos Labs. We are seeking highly motivated, creative, and collaborative individuals who are passionate and dedicated about using their expertise to make impactful contributions for unraveling the deep biology of cellular rejuvenation programming to restore cell health and resilience, including basic science, pre-clinical, and clinical-stage programs.

Responsibilities

• Engage in ground-breaking and innovative science.
• Support and manage internal/external collaborations in one or more multidisciplinary projects to accelerate essential research activities. 
• Study the mechanistic basis of cell programming for health and rejuvenation.
• Responsible for mentoring graduate students.
• Responsible for developing project-specific experimental strategies, techniques, and procedures.
• Responsible for helping PI train lab members, including scientists and technicians.
• Contribute to writing and dissemination of research results.
• Carry out research projects in collaboration with the PI.

Who You Are

We have multiple Scientist openings are are interested in having people at varying levels of experience. Minimum requirements for the Scientist role include:

• PhD and a documented record of professional achievement in the form of impactful publications.
• Excellent computer skills, including advanced proficiency with Google apps, Excel, and Powerpoint graphic skills to produce documents and manage office projects.
• Excellent professional writing skills and the ability to attune through writing and presentations to a variety of audiences including senior executives through entry-level employees.
• Problem-solving skills sufficient to identify issues, conduct research, and develop innovative solutions. 
• Ability to maintain cooperative working relationships with a broad range of people, including staff colleagues, lab members, faculty, outside agencies and collaborators, and the community. 
• Demonstrated high productivity and ability to complete work in a timely manner.
• Ability to organize work and set priorities.
• Ability to focus on details to produce accurate, quality work driven by deadlines.
• Ability to work in a dynamic environment and with others in a team.
• Strengths in dealing with ambiguity.

Preferred Qualifications

• Candidates with strong training in the following fields are preferred:
  
  
  • Epigenetics and Epigenetic modifications
  • Metabolism, including metabolome and adipose tissue/skeletal muscle/liver metabolism
  • Stem cell biology, prior experience with animal models is a plus
  • Single cell analysis of animal tissues
  • Screen platforms, including small molecules, CRISPR/Cas systems, RNAi, etc.
  • Gene delivery systems, including enhancing the delivery efficiency of AAVs
  • Tissues crosstalk
  • Animal disease models

The salary ranges for this position in San Diego, CA: 

• Scientist I $116,450 - $157,550
• Scientist II $137,000- $184,800
• Senior Scientist I $154,000 - $204,000
• Senior Scientist II $170,000- $247,000

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 (https://bit.ly/3fHGl98)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment

We’re looking to hire a Strategic Deployment Manager to join us in our mission to improve human health and quality of life through the development, distribution, and application of advanced computational methods!

As a member of our Enterprise Informatics team, you’ll play a vital role in all stages of the Schrödinger Platform deployment for customers, from initial project scoping through to long term successful adoption. By serving as the bi-directional voice for these customers, you’ll also help drive future product development strategy.

Click here for more information about how the Schrödinger Platform is helping shape the future of collaborative therapeutic design. 

Who will love this job:

• A pharmaceutical or chemical enterprise software technology expert who’s knowledgeable about industry best practices and enjoys interacting with medicinal chemists, computational chemists, biologists, and project leadership
• A scientist who understands project management in a corporate research setting (direct experience with pharmaceutical drug discovery is a huge plus!)
• An effective communicator with excellent organizational skills
• A customer-service oriented deployment manager who’s passionate about helping drive user success

What you’ll do:

• Manage LiveDesign implementation projects from early-stage discussions through deployment, training, and growth
• Ensure long-term customer success through use of the Schrödinger Platform
• Collaborate internally with Account Managers, Applications Scientists, Solutions Architects, and the Education team to ensure success of the account by enabling substantial growth and usage
• Help drive the product roadmap and development by working closely with product management and engineering, representing real-world customer needs

What you should have:

• B.Sc. in a life science (M.Sc. or Ph.D. preferred)
• At least three years of experience in a life sciences field related to drug discovery
• Experience with computational chemistry or cheminformatics in a research setting

Schrödinger understands it’s people that make a company great. Because of this, we’re prepared to offer a competitive salary, equity-based compensation, and a wide range of benefits that include healthcare (with dental and vision), a 401k, pre-tax commuter benefits, a flexible work schedule, and a parental leave program. We have catered meals in the office, a company culture that is relaxed but engaged, and over a month of paid vacation time. Our Administrative and Human Resources departments also plan a myriad of fun company-wide events. Schrödinger is honored to have been included in Crain's New York Best Places to Work, BuiltIn's NYC Best Place to Work, and Newsweek's list of America's 100 Most Loved Workplaces. 

Sound exciting? Apply today and join us!