2,032 Researchers jobs in the United States

Language Researchers

JTG is currently seeking Language Researchers in the following areas of research involving less commonly taught languages:

Somali

Middle Eastern and African varieties of Arabic

Amharic

North African varieties of French

Farsi

Pashto

Kurdish (all varieties)

 

General linguistic and lexicographic description

The ideal candidate must be capable of developing or assisting in the development of linguistics products such as bilingual dictionaries and glossaries; annotated readers at ILR levels 2-4; grammars; text books; hand books; phrase books; and word lists. Additionally, the researcher will provide grammatical descriptions of languages which are undocumented or poorly documented.

Location: Hyattsville, MD

Basic Requirements:

• Bachelor's degree
li>Highly proficient skills in language of interest
• Five years’ experience in applied linguistic research
< i>Ability to work independently as a developer and author of linguistics products

Preferred qualifications

• Graduate degree in linguistics or related field
• Authorship of published reference or training materials in target language, linguistics, or related area studies
• Ten years’ experience in applied linguistic research
< i>Native skills in language of interest

Machine learning researchers and engineers with impressive records of academic and professional achievements sought to join our interdisciplinary team in New York City.  We will consider candidates at all levels of experience.

This is a unique opportunity to collaborate with our chemists, biologists, and computer scientists to expand the group’s efforts applying machine learning to drug discovery, biomolecular simulation, and biophysics.  Ideal candidates will have demonstrated expertise in developing deep learning techniques, as well as strong Python programming skills.  Relevant areas of experience might include molecular dynamics, structural biology, medicinal chemistry, cheminformatics, and/or quantum chemistry, but specific knowledge of any of these areas is less critical than intellectual curiosity, versatility, and a track record of achievement and innovation in the field of machine learning.

D. E. Shaw Research (DESRES) develops and uses advanced computational technologies to understand the behavior of biologically and pharmaceutically significant molecules at an atomic level of detail, and to design precisely targeted, highly selective drugs for the treatment of various diseases.  Among our core technologies is a proprietary special-purpose supercomputer called ANTON® which we designed and constructed to perform molecular dynamics simulations more than 100 times faster than the world's fastest general-purpose supercomputers.  DESRES develops and refines advanced biomolecular modeling methods, software, and machine learning techniques on ANTON®, as well as on general-purpose supercomputers, in order to pursue both internal and collaborative drug discovery programs.  Machine learning techniques are a rapidly-growing aspect of our research efforts.  For example, we have developed and published neural networks that improve the accuracy of quantum chemistry models, and have trained deep learning models to generate optimized molecules for drug discovery.

We take great pride in the caliber of our team, and we offer above-market compensation.  We also provide generous relocation and immigration assistance to new hires.  In addition, we strive to support the personal and professional needs of our team members by offering generous benefits, opportunities for community engagement, and a variety of learning and development programs.

To submit an application, please use the link provided below:

D. E. Shaw Research is an equal opportunity employer, dedicated to the goal of building a diverse workforce. We embrace diversity along all dimensions, and respect and value the unique qualities, perspectives, and identities of every person in our group. We welcome inquiries from all exceptionally well-qualified applicants, regardless of race, color, nationality, national or ethnic origin, religion or religious belief, caste, gender identity, pregnancy, caregiver status, age, military service eligibility, veteran status, sexual orientation, marital or civil partner status, disability, or status in any other category protected in this regard by law in any jurisdiction in which we operate.

The expected annual base salary for this position is $250,000–$550,000.  Our compensation package also includes variable compensation in the form of sign-on and year-end bonuses, and generous benefits.  The applicable annual base salary paid to a successful applicant will be determined based on multiple factors including the nature and extent of prior experience and educational background.

Cambridge, MA Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science. We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method. We are introducingscientific superintelligence to solve humankind's greatestchallenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at At Lila, we are uniquely cross-functional and collaborative. We are actively reimagining the way teams work together and communicate. Therefore, we seek individuals with an inclusive mindset and a diversity of thought. Our teams thrive in unstructured and creative environments. All voices are heard because we know that experience comes in many forms, skills are transferable, and passion goes a long way. If this sounds like an environment you’d love to work in, even if you only have some of the experience listed below, please apply. Lila Sciences is seeking experienced, creative, and talented Machine Learning Researchers (LLMs) across Scientist, Senior Scientist, and Principal Scientist levelsto join our team. Title will be determined by merit and experience level. Join our agile team to reimagine the way scientific research is conducted! You'll train and fine-tune cutting-edge models on scientific data. Collaborate with experts across biology, materials science, and automation to push boundaries. We’re looking for an ML pro skilled in large-scale generative models, data pipelines, and software engineering excellence. Ready to transform science? Let’s talk! Designing, training, and fine-tuning large language models (LLMs), including the ability to successfully adapt an LLM for use in a specific domain. Leveraging ML tools and techniques to solve real world problems that require sequential decision making. Implementing rigorous testing, documentation, and model benchmarking. What You’ll Need to Succeed PhD in quantitative disciplines with contributions to research conferences or journals (e.g. NeurIPS, ICML, AAAI, ICLR) Experience in developing deep learning, NLP, and/or LLMs Expertise in ML frameworks (PyTorch/TensorFlow/Jax) and robust experience in the Python data science ecosystem Experience in training and deploying ML models on distributed computing services (e.g. AWS/GCP/Azure, or clusters) Distributed training experience of 70B+ parameter models Built custom benchmarks to challenge frontier models Developed AI agents for complex, long ranging tasks Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. A Note to Agencies Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto. Apply for this job * indicates a required field First Name * Last Name * Email * Phone * Location (City) Resume/CV * Enter manually Accepted file types: pdf, doc, docx, txt, rtf Enter manually Accepted file types: pdf, doc, docx, txt, rtf Employment Title Select. Start date year End date month Select. End date year Current role Will you now or in the future require sponsorship for employment visa status (e.g., H-1B visa status)? * Select. If you'll require the company to commence ("sponsor") an immigration or work permit case in order to employ you, either now or at some point in the future, then you should select Yes. Otherwise, select No. Do you currently reside within the continental United States? * Select. Are you able to work in the specified job location, or are you willing to relocate for this position? * Select. How did you hear about us? * When are you able to start a new position? * How many of the following accomplishments will you have achieved before starting your next role? Options below answer box * Select. - At least one publication in a top conference (NeurIPS, ICML, etc.) or workshop - PhD-degree - At least one year of industry experience Please include links to your GitHub and any notable Open Source projects. * #J-18808-Ljbffr

Join to apply for the Machine Learning Researchers (LLMs) - Open Level role at Lila Sciences Company Summary Lila Sciences is a privately held, early-stage technology company pioneering the application of artificial intelligence to transform every aspect of the scientific method. Backed by Flagship Pioneering, we aim to realize ambitious results. Join our mission-driven team and contribute to the future of science. Our focus is leveraging AI and automation for therapeutic discovery and development across biological modalities. We foster an inclusive, collaborative, and creative environment where all voices are valued. If you resonate with our environment, consider applying even if you have some but not all listed experiences. The Role We seek experienced, creative, and talented Machine Learning Researchers (LLMs) at Scientist, Senior Scientist, and Principal Scientist levels. The role involves training and fine-tuning models on scientific data, collaborating across biology, materials science, and automation, with a focus on large-scale generative models, data pipelines, and software engineering. Ready to transform science? Let’s talk! Candidates Should Have Experience And/or Interest In Designing, training, and fine-tuning large language models (LLMs), including adaptation for specific domains. Using ML tools and techniques for sequential decision-making problems. Implementing rigorous testing, documentation, and benchmarking of models. Qualifications PhD in quantitative disciplines with contributions to research conferences or journals (e.g., NeurIPS, ICML, AAAI, ICLR). Experience in deep learning, NLP, and/or LLMs. Proficiency in ML frameworks (PyTorch, TensorFlow, Jax) and the Python data ecosystem. Experience training and deploying models on distributed computing services (AWS, GCP, Azure, or clusters). Ideal Distributed training experience of models with 70B+ parameters. Developed benchmarks to challenge frontier models. Created AI agents for complex, long-term tasks. Technology Areas at Lila Sciences AI experimental design and simulation. Automated liquid handling and instrumentation. Generative molecular design. About Flagship Pioneering Flagship Pioneering is a platform innovation company building transformative ventures in health and sustainability, with a track record of impactful scientific and technological innovations. Committed to equal opportunity, we welcome diverse backgrounds and experiences. Experience in many forms is valued; if you have some relevant skills and passion, we encourage you to apply. We are dedicated to building diverse, inclusive teams. Additional Information We do not accept unsolicited resumes from recruitment agencies unless explicitly contacted by our Talent Acquisition team. Resumes submitted without agreement will become property of FSP without fees owed. #J-18808-Ljbffr

24.11.18 Machine Learning Researchers and Engineers Machine learning researchers and engineers with impressive records of academic and professional achievements sought to join our interdisciplinary team in New York City. This is a unique opportunity to collaborate with our chemists, biologists, and computer scientists to expand the group's efforts applying machine learning to drug discovery, biomolecular simulation, and biophysics. Responsibilities: Develop deep learning techniques. Collaborate with interdisciplinary teams in drug discovery and biomolecular simulation. Utilize strong Python programming skills. Qualifications: Demonstrated expertise in machine learning. Experience in relevant areas such as molecular dynamics, structural biology, medicinal chemistry, cheminformatics, and/or quantum chemistry is a plus. Intellectual curiosity and a track record of achievement in the field of machine learning. D. E. Shaw Research develops and uses advanced computational technologies to understand the behavior of biologically and pharmaceutically significant molecules at an atomic level of detail, and to design precisely targeted, highly selective drugs for the treatment of various diseases. Our core technologies include a proprietary special-purpose supercomputer called ANTON, which we designed and constructed to perform molecular dynamics simulations more than 100 times faster than the world's fastest general-purpose supercomputers. We are looking to add innovative contributors who share our commitment to fostering a stimulating, positive, and collaborative work environment. The expected annual base salary for this position is $300,000 - $600,000. Our compensation package includes variable compensation in the form of sign-on and year-end bonuses, and generous benefits, including relocation and immigration assistance. We follow a hybrid work schedule, with employees working from the office Tuesday through Thursday, and having the option to work from home on Monday and Friday. To submit an application, please use the link provided below: Apply Here NOTE THAT E-MAIL ADDRESSES HAVE BEEN MODIFIED! All @ signs were changed to ^ to fight spam. Before you send e-mail, you need to change ^to @. For example: change joe big123comp.com to Please let your prospective employer know that you learned about the job from the Computational Chemistry List Job Listing at CCL Jobs . #J-18808-Ljbffr

Cambridge, MA Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science. We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method. We are introducingscientific superintelligence to solve humankind's greatestchallenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at At Lila, we are uniquely cross-functional and collaborative. We are actively reimagining the way teams work together and communicate. Therefore, we seek individuals with an inclusive mindset and a diversity of thought. Our teams thrive in unstructured and creative environments. All voices are heard because we know that experience comes in many forms, skills are transferable, and passion goes a long way. If this sounds like an environment you’d love to work in, even if you only have some of the experience listed below, please apply. Lila Sciences is seeking experienced, creative, and talented Machine Learning Researchers (Generative Biology) across Scientist, Senior Scientist, and Principal Scientist levelsto join our team. Title will be determined by merit and experience level. Join our agile team to reimagine the way scientific research is conducted! You'll train and fine-tune cutting-edge models on real-world lab data. Collaborate with experts across biology and automation to push boundaries. We’re looking for an ML pro skilled in large-scale generative models, data pipelines, and software engineering excellence. Ready to transform science? Let’s talk! Designing and implementing generative models (e.g., LLMs, VAEs, diffusion models) tailored for biological sequences, structures, and molecular modalities. Integrating domain-specific constraints and priors into generative models to enhance biological plausibility and experimental viability. Developing rigorous testing, documentation, and model benchmarking. What You’ll Need to Succeed PhD in quantitative disciplines with contributions to research conferences or journals (e.g. NeurIPS, ICML, AAAI, ICLR). Solid understanding of fundamental biology concepts and demonstrated ability to apply these to AI model development. Expertise in ML frameworks (PyTorch/TensorFlow/Jax) and robust experience in the Python data science ecosystem. Experience in training and deploying ML models on distributed computing services (g. AWS/GCP/Azure, or clusters). Familiarity with state-of-the-art generative models for biological sequences, e.g., proteins, RNA, and DNA. Experience designing biological sequences or molecular structures with demonstrated improvements in real world outcomes (e.g. stability, binding affinity, or functional specificity) Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. A Note to Agencies Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto. Apply for this job * indicates a required field First Name * Last Name * Email * Phone * Location (City) Resume/CV * Enter manually Accepted file types: pdf, doc, docx, txt, rtf Enter manually Accepted file types: pdf, doc, docx, txt, rtf Employment Title Select. Start date year End date month Select. End date year Current role Will you now or in the future require sponsorship for employment visa status (e.g., H-1B visa status)? * Select. If you'll require the company to commence ("sponsor") an immigration or work permit case in order to employ you, either now or at some point in the future, then you should select Yes. Otherwise, select No. Do you currently reside within the continental United States? * Select. Are you able to work in the specified job location, or are you willing to relocate for this position? * Select. When are you able to start a new position? * How did you hear about us? * How many of the following accomplishments will you have achieved before starting your next role? Options below answer box * Select. - At least one publication in a top conference (NeurIPS, ICML, etc.) or workshop - PhD-degree - At least one year of industry experience Please include links to your GitHub and any notable Open Source projects. * #J-18808-Ljbffr

About Lila Sciences Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science. We are pioneering a new age of boundless discovery by building capabilities to apply AI to every aspect of the scientific method. We are introducing scientific superintelligence to solve humankind’s greatest challenges, enabling scientists to bring solutions in human health, climate, and sustainability at unprecedented pace and scale. Learn more at . At Lila, we are uniquely cross-functional and collaborative. We actively reimagine how teams work together and communicate. We seek individuals with an inclusive mindset and diverse perspectives. Our teams thrive in unstructured, creative environments where all voices are valued, recognizing that experience varies, skills are transferable, and passion matters. If this environment excites you, even if you only meet some of the listed qualifications, we encourage you to apply. Your Impact at Lila Lila Sciences seeks experienced, creative, and talented Machine Learning Researchers (Open-Endedness) at Scientist, Senior Scientist, and Principal Scientist levels, with titles determined by merit and experience. Open-Endedness is an emerging machine learning field focused on automating continuous discovery and exploration. Led by Ken Stanley, our team investigates how to sustain a chain of deep, transformative creativity that surpasses current models' derivative creativity. Our systems aim to go beyond solving existing problems to conceive unimagined future directions of science. We seek a broad range of ML expertise to support daring, unconventional investigations, including pre-training, fine-tuning, RLHF, distillation, mechanistic interpretability, and quality diversity (QD) techniques. What You’ll Be Building Designing, implementing, and modifying generative models (e.g., LLMs, diffusion models, multimodal models) through unconventional pipelines to achieve novel behaviors. Developing unconventional evaluation techniques, including subjective assessments and interestingness metrics. Investigating, understanding, and visualizing internal representations of large models, exploring mechanistic interpretability and new directions beyond it. Implementing QD algorithms like MAP-Elites, novelty search with local competition, POET, OMNI, and minimal criterion novelty search, potentially updating models in the inner loop. What You’ll Need to Succeed PhD in quantitative disciplines is ideal; exceptional self-taught researchers will also be considered. Publications in conferences such as NeurIPS, ICML, AAAI, ICLR, GECCO, ICCC. Experience with ML frameworks (PyTorch, TensorFlow, Jax), QD algorithms, or neuroevolution algorithms. Experience training and deploying ML models on distributed platforms (AWS, GCP, Azure, or clusters). We’re All In Lila Sciences is committed to equal employment opportunity regardless of race, color, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. A Note to Agencies We do not accept unsolicited resumes unless contacted directly by our Talent Acquisition team. Resumes from agencies without a signed agreement will become our property, and no fees will be owed. Company: Lila Sciences Qualifications: Language requirements: Specific requirements: Educational level: Level of experience (years): Senior (5+ years of experience) Tagged as: Clustering , Industry , Machine Learning , NLP , United States #J-18808-Ljbffr

Cambridge, MA Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science. We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method. We are introducingscientific superintelligence to solve humankind's greatestchallenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at At Lila, we are uniquely cross-functional and collaborative. We are actively reimagining the way teams work together and communicate. Therefore, we seek individuals with an inclusive mindset and a diversity of thought. Our teams thrive in unstructured and creative environments. All voices are heard because we know that experience comes in many forms, skills are transferable, and passion goes a long way. If this sounds like an environment you’d love to work in, even if you only have some of the experience listed below, please apply. Lila Sciences is seeking experienced, creative, and talented Machine Learning Researchers (Reinforcement Learning) across Scientist, Senior Scientist, and Principal Scientist levelsto join our team. Title will be determined by merit and experience level. Join our agile team to reimagine the way scientific research is conducted! You'll train and fine-tune cutting-edge models on scientific data. Collaborate with experts across biology, materials science, and automation to push boundaries. We’re looking for an ML pro skilled in reinforcement learning and software engineering excellence. Ready to transform science? Let’s talk! Incorporating RL approaches with large language models (LLMs) to enhance reasoning, planning, and decision-making capabilities. DPO, PPO, and/or RLHF for fine-tuning LLMs Implementing robust evaluation frameworks, including custom benchmarks, to rigorously test model performance and reliability. What You’ll Need to Succeed PhD in Computer Science, Machine Learning, Robotics, or a related quantitative field, with demonstrated contributions to top-tier conferences (e.g., NeurIPS, ICML, ICLR, AAAI). Deep expertise in RL, including experience with policy optimization, value-based methods, or model-based RL. Experience with distributed computing platforms (AWS, GCP, Azure, or on-prem clusters). Demonstrated ability to run rigorous experiments, document findings, and iteratively improve models based on quantitative results. Hands-on experience in multi-agent RL settings or hierarchical and offline RL methods. Experience with online reinforcement learning in cost-sensitive settings. Knowledge of LLM training/fine-tuning methods and experience with these methods at scale. Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. A Note to Agencies Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto. Apply for this job * indicates a required field First Name * Last Name * Email * Phone * Location (City) Resume/CV * Enter manually Accepted file types: pdf, doc, docx, txt, rtf Enter manually Accepted file types: pdf, doc, docx, txt, rtf Employment Title Select. Start date year End date month Select. End date year Current role Will you now or in the future require sponsorship for employment visa status (e.g., H-1B visa status)? * Select. If you'll require the company to commence ("sponsor") an immigration or work permit case in order to employ you, either now or at some point in the future, then you should select Yes. Otherwise, select No. Do you currently reside within the continental United States? * Select. Are you able to work in the specified job location, or are you willing to relocate for this position? * Select. When are you able to start a new position? * How did you hear about us? * How many of the following accomplishments will you have achieved before starting your next role? Options below answer box * Select. - At least one publication in a top conference (NeurIPS, ICML, etc.) or workshop - PhD-degree - At least one year of industry experience Please include links to your GitHub and any notable Open Source projects. * #J-18808-Ljbffr

• Incorporating RL approaches with large language models (LLMs) to enhance reasoning, planning, and decision-making capabilities.
• DPO, PPO, and/or RLHF for fine-tuning LLMs
• Implementing robust evaluation frameworks, including custom benchmarks, to rigorously test model performance and reliability.

• PhD in Computer Science, Machine Learning, Robotics, or a related quantitative field, with demonstrated contributions to top-tier conferences (e.g., NeurIPS, ICML, ICLR, AAAI).
• Deep expertise in RL, including experience with policy optimization, value-based methods, or model-based RL.
• Experience with distributed computing platforms (AWS, GCP, Azure, or on-prem clusters).
• Demonstrated ability to run rigorous experiments, document findings, and iteratively improve models based on quantitative results.

• Hands-on experience in multi-agent RL settings or hierarchical and offline RL methods.
• Experience with online reinforcement learning in cost-sensitive settings.
• Knowledge of LLM training/fine-tuning methods and experience with these methods at scale.