Second Renaissance
Palo Alto, California
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.
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.
Second Renaissance
San Francisco, California
Overview As a Senior Staff Software Optimization Engineer you will collaborate with a specialized team to drive C++ system optimizations for enhancing LLM model inference and training performance. You will play a pivotal role in transforming innovative concepts into tangible products alongside top AI/ML researchers. This is a full-time position. Working remotely is possible, but local candidates are preferred. Responsibilities Efficiently transform ideas and concepts into working prototypes and production-level code. Conduct in-depth performance analysis and profiling, and identify performance bottlenecks. Devise and implement novel strategies that exploit algorithm insights and hardware capabilities for enhanced efficiency, and speed. Optimize core AI/ML algorithms to enhance performance. Stay at the forefront of software, hardware optimization and AI advancements, utilizing this knowledge to spearhead continuous improvements. Offer technical leadership and mentorship, elevating engineering practices and contributing to the development process. Qualifications Master's degree (or equivalent experience) in Computer Science, Engineering, or a related field. Must have over 5 years of experience in software engineering and product development. A minimum of 2 years experience in optimizing AI models is strongly preferred. Outstanding proficiency in C/C++, with hands-on experience developing high-performance systems. Familiarity with SIMD programming, assembly, intrinsic functions, AVX, or similar instruction sets, is a strong plus. A strong understanding of memory allocation, the memory hierarchy and optimizing to make the best use of caches and memory layout on multi-core multi socket servers. Expertise in common data structures and an understanding of CPU/GPU architectures, essential for developing optimized software. A thorough grasp of system architecture, including hardware accelerators and advanced optimization techniques. Experience working with LLMs, and a strong understanding of transformer attention is strongly preferred. Strong communication abilities, capable of simplifying complex technical details for diverse audiences. Adaptable and quick to embrace new technologies and methods, thriving in a fast-paced and innovative environment. What We Offer A role at the forefront of the AI revolution with a company shaping the future of intelligent computing. A high degree of autonomy and responsibility from the outset, with significant opportunities for professional growth. The chance to work with a world-class team of scientists and engineers. A vibrant startup culture that values innovation, creativity, and collaboration. Compensation & Application Compensation: At Numenta, we offer a competitive salary reflective of the candidate's expertise. Our compensation package includes full medical, dental, and vacation benefits. The base annual salary range for this position for candidates residing in the San Francisco Bay Area is $150,000 to $225,000; exact salary will depend on the candidate's experience level and fit to the job description. We also include a competitive stock option package, ensuring a shared stake in our future success. How To Apply To apply please send your resume and a cover letter to . The cover letter must state your specific fit to Numenta's technology and products, and the requirements above. Numenta is an equal opportunity employer supporting workforce diversity. Join us at Numenta to help shape the future of AI. Apply today!
Overview As a Senior Staff Software Optimization Engineer you will collaborate with a specialized team to drive C++ system optimizations for enhancing LLM model inference and training performance. You will play a pivotal role in transforming innovative concepts into tangible products alongside top AI/ML researchers. This is a full-time position. Working remotely is possible, but local candidates are preferred. Responsibilities Efficiently transform ideas and concepts into working prototypes and production-level code. Conduct in-depth performance analysis and profiling, and identify performance bottlenecks. Devise and implement novel strategies that exploit algorithm insights and hardware capabilities for enhanced efficiency, and speed. Optimize core AI/ML algorithms to enhance performance. Stay at the forefront of software, hardware optimization and AI advancements, utilizing this knowledge to spearhead continuous improvements. Offer technical leadership and mentorship, elevating engineering practices and contributing to the development process. Qualifications Master's degree (or equivalent experience) in Computer Science, Engineering, or a related field. Must have over 5 years of experience in software engineering and product development. A minimum of 2 years experience in optimizing AI models is strongly preferred. Outstanding proficiency in C/C++, with hands-on experience developing high-performance systems. Familiarity with SIMD programming, assembly, intrinsic functions, AVX, or similar instruction sets, is a strong plus. A strong understanding of memory allocation, the memory hierarchy and optimizing to make the best use of caches and memory layout on multi-core multi socket servers. Expertise in common data structures and an understanding of CPU/GPU architectures, essential for developing optimized software. A thorough grasp of system architecture, including hardware accelerators and advanced optimization techniques. Experience working with LLMs, and a strong understanding of transformer attention is strongly preferred. Strong communication abilities, capable of simplifying complex technical details for diverse audiences. Adaptable and quick to embrace new technologies and methods, thriving in a fast-paced and innovative environment. What We Offer A role at the forefront of the AI revolution with a company shaping the future of intelligent computing. A high degree of autonomy and responsibility from the outset, with significant opportunities for professional growth. The chance to work with a world-class team of scientists and engineers. A vibrant startup culture that values innovation, creativity, and collaboration. Compensation & Application Compensation: At Numenta, we offer a competitive salary reflective of the candidate's expertise. Our compensation package includes full medical, dental, and vacation benefits. The base annual salary range for this position for candidates residing in the San Francisco Bay Area is $150,000 to $225,000; exact salary will depend on the candidate's experience level and fit to the job description. We also include a competitive stock option package, ensuring a shared stake in our future success. How To Apply To apply please send your resume and a cover letter to . The cover letter must state your specific fit to Numenta's technology and products, and the requirements above. Numenta is an equal opportunity employer supporting workforce diversity. Join us at Numenta to help shape the future of AI. Apply today!