Our Mission Our mission is to restore cell health and resilience through cell rejuvenation to reverse disease, injury, and the disabilities that can occur throughout life. For more information, see our website at Our Value Our Single Altos Value: Everyone Owns Achieving Our Inspiring Mission. Diversity at Altos We believe that diverse perspectives are foundational to scientific innovation and inquiry. At Altos, exceptional scientists and industry leaders from around the world work together to advance a shared mission. Our intentional focus is on Belonging, so that all employees know that they are valued for their unique perspectives. We are all accountable for sustaining a diverse and inclusive environment. What You Will Contribute To Altos As a Machine Learning Engineer, you will play a prominent role in developing generative AI/ML models for multi-modal, multi scale biology. We are looking for a hands on, senior level creative and collaborative person 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 Partner with world class scientists across Altos to help generate biological insights with the goal of developing novel therapies; Design and implement large scale machine learning algorithms and systems applied to biological datasets; Train, evaluate, and optimize machine learning models at scale; Communicate effectively with internal and external collaborators to meet ambitious research and development goals. 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; 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; Growth mindset - the desire to constantly expand your skillset and knowledge. Keen to learn more about biology, computational science, and medicine; Excitement about the Altos mission of restoring cell health and resilience to reverse disease, injury, and age related disabilities. Minimum Qualifications Masters or Ph.D. degree in a quantitative/computational field such as computer science, artificial intelligence, mathematics, statistics, physics, or computational biology, or equivalent experience; 8+ years experience in developing machine learning models; Very strong programming skills, including experience with Python and deep learning libraries such as PyTorch or JAX; Experience in large scale distributed optimization of machine learning models across multiple GPUs and nodes. Preferred Qualifications Familiarity with biological data formats, concepts, and computational models; Experience in cell health and rejuvenation related research area; Experience with identification and assessment of drug targets and/or therapeutic compounds; Experience in the application of machine learning methods to biological data, including genomics, transcriptomics, epigenetics, proteomics, and imaging; Track record in open source software development, e.g., demonstrated by high impact GitHub repository; Track record of high caliber scientific work, e.g., demonstrated through publications in peer reviewed scientific journals or major ML conferences; Experience with one lower level language (e.g., C++, Rust); Experience with large scale data processing and database tools such as MapReduce, Dask, SQL, Hugging Face Datasets, TileDB, Ray. The salary range Senior Machine Learning Engineer: $200,600 - $271,400 (Redwood City, CA) Staff Machine Learning Engineer: $232,900 - $315,100 (Redwood City, CA) Senior Machine Learning Engineer: $186,150 - $251,850 (San Diego, CA) Staff Machine Learning Engineer: $221,000 - $299,000 (San Diego, CA) Exact compensation may vary based on skills, experience, and location. Important Information for UK Applicants Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice). The Privacy Notice is not a contract and does not set terms or conditions of employment. We Want You To Know We are a culture of collaboration and scientific excellence, and we believe in the values of inclusion and belonging to inspire innovation. Equal Employment Opportunity Altos Labs provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Vaccination Policy Altos currently requires all employees to be fully vaccinated against COVID-19, subject to legally required exemptions (e.g., due to a medical condition or sincerely held religious belief). EEO Statement Altos Labs complies with the law and is not required to provide statements except as required by statute. All positions at Altos are open to qualified individuals with a high level of academic prowess and candidness. Altos Labs welcomes diverse backgrounds.
04/02/2026
Full time
Our Mission Our mission is to restore cell health and resilience through cell rejuvenation to reverse disease, injury, and the disabilities that can occur throughout life. For more information, see our website at Our Value Our Single Altos Value: Everyone Owns Achieving Our Inspiring Mission. Diversity at Altos We believe that diverse perspectives are foundational to scientific innovation and inquiry. At Altos, exceptional scientists and industry leaders from around the world work together to advance a shared mission. Our intentional focus is on Belonging, so that all employees know that they are valued for their unique perspectives. We are all accountable for sustaining a diverse and inclusive environment. What You Will Contribute To Altos As a Machine Learning Engineer, you will play a prominent role in developing generative AI/ML models for multi-modal, multi scale biology. We are looking for a hands on, senior level creative and collaborative person 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 Partner with world class scientists across Altos to help generate biological insights with the goal of developing novel therapies; Design and implement large scale machine learning algorithms and systems applied to biological datasets; Train, evaluate, and optimize machine learning models at scale; Communicate effectively with internal and external collaborators to meet ambitious research and development goals. 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; 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; Growth mindset - the desire to constantly expand your skillset and knowledge. Keen to learn more about biology, computational science, and medicine; Excitement about the Altos mission of restoring cell health and resilience to reverse disease, injury, and age related disabilities. Minimum Qualifications Masters or Ph.D. degree in a quantitative/computational field such as computer science, artificial intelligence, mathematics, statistics, physics, or computational biology, or equivalent experience; 8+ years experience in developing machine learning models; Very strong programming skills, including experience with Python and deep learning libraries such as PyTorch or JAX; Experience in large scale distributed optimization of machine learning models across multiple GPUs and nodes. Preferred Qualifications Familiarity with biological data formats, concepts, and computational models; Experience in cell health and rejuvenation related research area; Experience with identification and assessment of drug targets and/or therapeutic compounds; Experience in the application of machine learning methods to biological data, including genomics, transcriptomics, epigenetics, proteomics, and imaging; Track record in open source software development, e.g., demonstrated by high impact GitHub repository; Track record of high caliber scientific work, e.g., demonstrated through publications in peer reviewed scientific journals or major ML conferences; Experience with one lower level language (e.g., C++, Rust); Experience with large scale data processing and database tools such as MapReduce, Dask, SQL, Hugging Face Datasets, TileDB, Ray. The salary range Senior Machine Learning Engineer: $200,600 - $271,400 (Redwood City, CA) Staff Machine Learning Engineer: $232,900 - $315,100 (Redwood City, CA) Senior Machine Learning Engineer: $186,150 - $251,850 (San Diego, CA) Staff Machine Learning Engineer: $221,000 - $299,000 (San Diego, CA) Exact compensation may vary based on skills, experience, and location. Important Information for UK Applicants Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice). The Privacy Notice is not a contract and does not set terms or conditions of employment. We Want You To Know We are a culture of collaboration and scientific excellence, and we believe in the values of inclusion and belonging to inspire innovation. Equal Employment Opportunity Altos Labs provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Vaccination Policy Altos currently requires all employees to be fully vaccinated against COVID-19, subject to legally required exemptions (e.g., due to a medical condition or sincerely held religious belief). EEO Statement Altos Labs complies with the law and is not required to provide statements except as required by statute. All positions at Altos are open to qualified individuals with a high level of academic prowess and candidness. Altos Labs welcomes diverse backgrounds.
Mission Our mission is to restore cell health and resilience through cell rejuvenation to reverse disease, injury, and the disabilities that can occur throughout life. Value Our Single Altos Value: Everyone Owns Achieving Our Inspiring Mission. Diversity at Altos We believe that diverse perspectives are foundational to scientific innovation and inquiry. At Altos, exceptional scientists and industry leaders from around the world work together to advance a shared mission. Our intentional focus is on Belonging, so that all employees know that they are valued for their unique perspectives. We are all accountable for sustaining a diverse and inclusive environment. What You Will Contribute to Altos Altos Labs is seeking a Machine Learning Engineer I/II who can accelerate and optimize our progress in developing foundation models for biology. This role is integral to our Computational Systems Modeling & Scaling team, working in a team of experienced ML and infrastructure engineers to deliver compelling internal frameworks, services, and expertise, and to train and deploy scalable, robust models. It will involve close collaboration with computational scientists from a diverse range of disciplines, including molecular modeling, computational biology, discrete simulation, machine learning, and artificial intelligence. Responsibilities Training, evaluating, and optimizing large scale machine learning systems including data transformation pipelines, feature stores, distributed training, architecture optimization, model management & serving, etc. Building, deploying, and managing systems to accelerate large-scale machine learning workflows in an integrated, usable framework Understanding user needs across a wide range of scientific disciplines, and communicating with users to build systems that they can use productively Developing reliable, scalable, performant systems in a cloud environment Employing maintainable, scalable, and reusable software engineering techniques Demonstrating best practices around development tools, CI/CD, and other methods to improve code quality and efficiency. Who You Are Minimum Qualifications M.S. or Ph.D. in Computer Science, or related quantitative field, or equivalent technical experience Candidates should have 1-4 years of relevant industry and/or academic experience Experience with large-scale machine learning tools and infrastructure Experience applying software engineering practices in a scientific environment, collaborating with cross functional teams Strong written and verbal communication skills Preferred Qualifications Familiarity with biological data formats, concepts, and computational models is a plus. Salary Range: San Francisco Bay Area, CA Machine Learning Engineer I: $153,000 - $207,000 Machine Learning Engineer II: $178,500 - $241,500 Salary Range: San Diego, CA Machine Learning Engineer I: $150,450 - $203,550 Machine Learning Engineer II: $170,000 - $230,000 Exact compensation may vary based on skills, experience, and location. For UK Applicants Please click here to read the Altos Labs EU and UK Applicant Privacy Notice. This Privacy Notice is not a contract, express or implied, and it does not set terms or conditions of employment. What We Want You To Know We are a culture of collaboration and scientific excellence, and we believe in the values of inclusion and belonging to inspire innovation. Equal Employment Opportunity Altos Labs provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training. COVID 19 Vaccination Altos currently requires all employees to be fully vaccinated against COVID 19, subject to legally required exemptions (e.g., due to a medical condition or sincerely held religious belief). Thank You Thank you for your interest in Altos Labs where we strive for a culture of scientific excellence, learning, and belonging. Note about Job Scam Altos Labs will not ask you to download a messaging app for an interview or outlay your own money to get started as an employee. If this sounds like your interaction with people claiming to be with Altos, it is not legitimate and has nothing to do with Altos. Learn more about a common job scam at
04/02/2026
Full time
Mission Our mission is to restore cell health and resilience through cell rejuvenation to reverse disease, injury, and the disabilities that can occur throughout life. Value Our Single Altos Value: Everyone Owns Achieving Our Inspiring Mission. Diversity at Altos We believe that diverse perspectives are foundational to scientific innovation and inquiry. At Altos, exceptional scientists and industry leaders from around the world work together to advance a shared mission. Our intentional focus is on Belonging, so that all employees know that they are valued for their unique perspectives. We are all accountable for sustaining a diverse and inclusive environment. What You Will Contribute to Altos Altos Labs is seeking a Machine Learning Engineer I/II who can accelerate and optimize our progress in developing foundation models for biology. This role is integral to our Computational Systems Modeling & Scaling team, working in a team of experienced ML and infrastructure engineers to deliver compelling internal frameworks, services, and expertise, and to train and deploy scalable, robust models. It will involve close collaboration with computational scientists from a diverse range of disciplines, including molecular modeling, computational biology, discrete simulation, machine learning, and artificial intelligence. Responsibilities Training, evaluating, and optimizing large scale machine learning systems including data transformation pipelines, feature stores, distributed training, architecture optimization, model management & serving, etc. Building, deploying, and managing systems to accelerate large-scale machine learning workflows in an integrated, usable framework Understanding user needs across a wide range of scientific disciplines, and communicating with users to build systems that they can use productively Developing reliable, scalable, performant systems in a cloud environment Employing maintainable, scalable, and reusable software engineering techniques Demonstrating best practices around development tools, CI/CD, and other methods to improve code quality and efficiency. Who You Are Minimum Qualifications M.S. or Ph.D. in Computer Science, or related quantitative field, or equivalent technical experience Candidates should have 1-4 years of relevant industry and/or academic experience Experience with large-scale machine learning tools and infrastructure Experience applying software engineering practices in a scientific environment, collaborating with cross functional teams Strong written and verbal communication skills Preferred Qualifications Familiarity with biological data formats, concepts, and computational models is a plus. Salary Range: San Francisco Bay Area, CA Machine Learning Engineer I: $153,000 - $207,000 Machine Learning Engineer II: $178,500 - $241,500 Salary Range: San Diego, CA Machine Learning Engineer I: $150,450 - $203,550 Machine Learning Engineer II: $170,000 - $230,000 Exact compensation may vary based on skills, experience, and location. For UK Applicants Please click here to read the Altos Labs EU and UK Applicant Privacy Notice. This Privacy Notice is not a contract, express or implied, and it does not set terms or conditions of employment. What We Want You To Know We are a culture of collaboration and scientific excellence, and we believe in the values of inclusion and belonging to inspire innovation. Equal Employment Opportunity Altos Labs provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training. COVID 19 Vaccination Altos currently requires all employees to be fully vaccinated against COVID 19, subject to legally required exemptions (e.g., due to a medical condition or sincerely held religious belief). Thank You Thank you for your interest in Altos Labs where we strive for a culture of scientific excellence, learning, and belonging. Note about Job Scam Altos Labs will not ask you to download a messaging app for an interview or outlay your own money to get started as an employee. If this sounds like your interaction with people claiming to be with Altos, it is not legitimate and has nothing to do with Altos. Learn more about a common job scam at
A leading laboratory organization in San Diego is seeking a Machine Learning Engineer I/II to contribute to the development of foundation models for biology. This role involves training and optimizing large-scale machine learning systems in a collaborative environment with a diverse team. Ideal candidates will have relevant degrees and practical experience in large-scale ML tools, with strong communication skills. The position offers competitive compensation with a salary range from $150,450 to $203,550 for Machine Learning Engineer I.
04/02/2026
Full time
A leading laboratory organization in San Diego is seeking a Machine Learning Engineer I/II to contribute to the development of foundation models for biology. This role involves training and optimizing large-scale machine learning systems in a collaborative environment with a diverse team. Ideal candidates will have relevant degrees and practical experience in large-scale ML tools, with strong communication skills. The position offers competitive compensation with a salary range from $150,450 to $203,550 for Machine Learning Engineer I.
A cutting-edge biotech company in San Diego is seeking a Senior Machine Learning Engineer to develop generative AI models for multi-modal biology. You will collaborate with top scientists to advance research and development goals in cell health restoration. The ideal candidate has over 8 years of experience in machine learning and a strong programming background. This role offers competitive salary and inclusivity in a fast-paced environment.
04/02/2026
Full time
A cutting-edge biotech company in San Diego is seeking a Senior Machine Learning Engineer to develop generative AI models for multi-modal biology. You will collaborate with top scientists to advance research and development goals in cell health restoration. The ideal candidate has over 8 years of experience in machine learning and a strong programming background. This role offers competitive salary and inclusivity in a fast-paced environment.
About Arc Institute The Arc Institute is a new scientific institution that conducts curiosity-driven basic science and technology development to understand and treat complex human diseases. Headquartered in Palo Alto, California, Arc is an independent research organization founded on the belief that many important research programs will be enabled by new institutional models. Arc operates in partnership with Stanford University, UCSF, and UC Berkeley. While the prevailing university research model has yielded many tremendous successes, we believe in the importance of institutional experimentation as a way to make progress. These include: Funding: Arc will fully fund Core Investigators' (PIs') research groups, liberating scientists from the typical constraints of project-based external grants. Technology: Biomedical research has become increasingly dependent on complex tooling. Arc Technology Centers develop, optimize and deploy rapidly advancing experimental and computational technologies in collaboration with Core Investigators. Support: Arc aims to provide first-class support-operationally, financially and scientifically-that will enable scientists to pursue long-term high risk, high reward research that can meaningfully advance progress in disease cures, including neurodegeneration, cancer, and immune dysfunction. Culture: We believe that culture matters enormously in science and that excellence is difficult to sustain. We aim to create a culture that is focused on scientific curiosity, a deep commitment to truth, broad ambition, and selfless collaboration. Arc has scaled to nearly 200 people. With $650M+ in committed funding and a state of the art new lab facility in Palo Alto, Arc will continue to grow quickly in the coming years. About the position We are searching for an experienced and collaborative machine learning research engineer focused on advancing the frontiers of biological foundation models. This role will contribute to the development and application of Arc's frontier DNA foundation model (Evo), Arc's Virtual Cell Initiative focused on developing cell biological models capable of predicting the impact of perturbations and stimuli, and other projects in the context of Institute wide machine learning efforts. About you You are an innovative machine learning engineer with a deep understanding of ML principles, enabling you to design, modify, and critically evaluate model architectures, not just apply existing ones. You have significant experience in training large deep learning models. You enjoy thinking from first principles, seeking to deeply understand the data and its underlying dynamics to drive effective and innovative modeling strategies. You are excited about working closely with a multidisciplinary team of computational and experimental biologists at Arc to achieve breakthrough capabilities in biological prediction and design tasks. You are a strong communicator, capable of translating complex technical concepts to researchers outside of your domain. You are a continuous learner and are enthusiastic about developing and evaluating a model that impacts many biological disciplines. In this position, you will Actively participate in the design, implementation, and refinement of state of the art foundation models developed in collaboration with other ML researchers and scientists at Arc with the goal of understanding and designing complex biological systems. Engineer large scale distributed model pretraining and pipelines for efficient model inference. Enable robust systematic evaluation of trained models. Stay up to date with the latest advancements in technologies for large scale sequence modeling and alignment, and implement the most promising strategies to ensure the underlying models remain state of the art. Work with experimental biologists to ensure that the developed models are grounded in biologically meaningful problems and evaluations. Publish findings through journal publications, white papers, and presentations (both internal to Arc and external). Foster internal and external collaborations centered on generative design of biological systems at Arc Institute. Commit to a collaborative and inclusive team environment, sharing expertise and mentoring others. Job Requirements B.S., M.S. or Ph.D. in Computer Science, Machine Learning or a related field. Minimum of 5 8+ years of relevant experience in machine learning research or ML engineering in an academic (e.g., Ph.D.) or industry research lab. Well versed in machine learning frameworks such as PyTorch or JAX. Experience with developing distributed training tools such as FSDP, DeepSpeed, or Megatron LM. Excellent communication skills, both written and verbal, with a strong track record of presentations and publications. Ability to communicate and collaborate successfully with biologists and software/infrastructure engineers. Motivated to work in a fast paced, ambitious, multi disciplinary, and highly collaborative research environment. The base salary range for this position is $168,000 $242,500. These amounts reflect the range of base salary that the Institute reasonably would expect to pay a new hire or internal candidate for this position. The actual base compensation paid to any individual for this position may vary depending on factors such as experience, market conditions, education/training, skill level, and whether the compensation is internally equitable, and does not include bonuses, commissions, differential pay, other forms of compensation, or benefits. This position is also eligible to receive an annual discretionary bonus, with the amount dependent on individual and institute performance factors.
04/02/2026
Full time
About Arc Institute The Arc Institute is a new scientific institution that conducts curiosity-driven basic science and technology development to understand and treat complex human diseases. Headquartered in Palo Alto, California, Arc is an independent research organization founded on the belief that many important research programs will be enabled by new institutional models. Arc operates in partnership with Stanford University, UCSF, and UC Berkeley. While the prevailing university research model has yielded many tremendous successes, we believe in the importance of institutional experimentation as a way to make progress. These include: Funding: Arc will fully fund Core Investigators' (PIs') research groups, liberating scientists from the typical constraints of project-based external grants. Technology: Biomedical research has become increasingly dependent on complex tooling. Arc Technology Centers develop, optimize and deploy rapidly advancing experimental and computational technologies in collaboration with Core Investigators. Support: Arc aims to provide first-class support-operationally, financially and scientifically-that will enable scientists to pursue long-term high risk, high reward research that can meaningfully advance progress in disease cures, including neurodegeneration, cancer, and immune dysfunction. Culture: We believe that culture matters enormously in science and that excellence is difficult to sustain. We aim to create a culture that is focused on scientific curiosity, a deep commitment to truth, broad ambition, and selfless collaboration. Arc has scaled to nearly 200 people. With $650M+ in committed funding and a state of the art new lab facility in Palo Alto, Arc will continue to grow quickly in the coming years. About the position We are searching for an experienced and collaborative machine learning research engineer focused on advancing the frontiers of biological foundation models. This role will contribute to the development and application of Arc's frontier DNA foundation model (Evo), Arc's Virtual Cell Initiative focused on developing cell biological models capable of predicting the impact of perturbations and stimuli, and other projects in the context of Institute wide machine learning efforts. About you You are an innovative machine learning engineer with a deep understanding of ML principles, enabling you to design, modify, and critically evaluate model architectures, not just apply existing ones. You have significant experience in training large deep learning models. You enjoy thinking from first principles, seeking to deeply understand the data and its underlying dynamics to drive effective and innovative modeling strategies. You are excited about working closely with a multidisciplinary team of computational and experimental biologists at Arc to achieve breakthrough capabilities in biological prediction and design tasks. You are a strong communicator, capable of translating complex technical concepts to researchers outside of your domain. You are a continuous learner and are enthusiastic about developing and evaluating a model that impacts many biological disciplines. In this position, you will Actively participate in the design, implementation, and refinement of state of the art foundation models developed in collaboration with other ML researchers and scientists at Arc with the goal of understanding and designing complex biological systems. Engineer large scale distributed model pretraining and pipelines for efficient model inference. Enable robust systematic evaluation of trained models. Stay up to date with the latest advancements in technologies for large scale sequence modeling and alignment, and implement the most promising strategies to ensure the underlying models remain state of the art. Work with experimental biologists to ensure that the developed models are grounded in biologically meaningful problems and evaluations. Publish findings through journal publications, white papers, and presentations (both internal to Arc and external). Foster internal and external collaborations centered on generative design of biological systems at Arc Institute. Commit to a collaborative and inclusive team environment, sharing expertise and mentoring others. Job Requirements B.S., M.S. or Ph.D. in Computer Science, Machine Learning or a related field. Minimum of 5 8+ years of relevant experience in machine learning research or ML engineering in an academic (e.g., Ph.D.) or industry research lab. Well versed in machine learning frameworks such as PyTorch or JAX. Experience with developing distributed training tools such as FSDP, DeepSpeed, or Megatron LM. Excellent communication skills, both written and verbal, with a strong track record of presentations and publications. Ability to communicate and collaborate successfully with biologists and software/infrastructure engineers. Motivated to work in a fast paced, ambitious, multi disciplinary, and highly collaborative research environment. The base salary range for this position is $168,000 $242,500. These amounts reflect the range of base salary that the Institute reasonably would expect to pay a new hire or internal candidate for this position. The actual base compensation paid to any individual for this position may vary depending on factors such as experience, market conditions, education/training, skill level, and whether the compensation is internally equitable, and does not include bonuses, commissions, differential pay, other forms of compensation, or benefits. This position is also eligible to receive an annual discretionary bonus, with the amount dependent on individual and institute performance factors.