The Opportunity We are seeking a highly skilled and motivated Principal Machine Learning Scientist to join the BRAID team (Biology Research | AI Development) within our Computational Sciences organization. This role will focus on building novel machine-learning methods to enhance drug development and clinical trial design, with a particular emphasis on early-stage clinical trials. The successful candidate will develop novel machine learning methods for multimodal clinical data, including generative models and representation learning, leveraging their expertise to improve trial efficiency, patient outcomes, and overall trial success rates. The candidate is expected to routinely publish work in top-tier Machine Learning and scientific venues. We seek exceptional researchers with a demonstrated research background in machine learning, a passion for interdisciplinary research and technical problem-solving, and a proven ability to develop and implement ideas from research. Key Responsibilities Lead research initiatives at the intersection of machine learning, biology, and clinical sciences. Conceive and lead collaborations both internally and externally. Maintain expertise at the forefront of multiple areas in machine learning and biology/clinical sciences. Collaborate with cross-functional teams, including chemists, biostatisticians, clinical scientists, and data engineers, to integrate ML methods into clinical trial development. Lead and contribute to the design and execution of clinical trials by developing foundation models using multimodal pre-clinical and clinical datasets. Publish research findings in top-tier machine learning and scientific journals and present at leading conferences. Mentor junior scientists and contribute to the strategic direction of the ML group within the Computational Science Organization. Who you are Educational Background: Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, Physics, or a related field with a strong emphasis on machine learning. Experience: Proven track record with 2 years of experience developing and applying advanced ML models in a research or industry setting. Technical Skills Proficiency in scientific programming languages such as Python as well as MLOps workflows (e.g., familiar with code version control, high-performance compute infrastructures, and machine learning experiment monitoring workflows). Extensive experience with machine learning frameworks and libraries (e.g., JAX, PyTorch, Tensorflow). Strong background in statistics, probabilistic modeling, and data analysis. Domain Knowledge: Understanding of clinical trials, drug development, and biological data. Soft Skills: Excellent communication, collaboration, and problem-solving skills. Publications: Strong publication record and experience contributing to research communities, including scientific journals and conferences like NeurIPS, ICML, ICLR, CVPR, ICCV, etc. Preferred You have an extensive track record of delivering innovative solutions in machine learning, strong communication skills with the ability to effectively communicate technical concepts to both technical and non-technical audiences as well as interfacing with scientific leadership. You have practical experience in one or more of the following areas: reinforcement learning, geometric deep learning, representation learning, and generative learning. You have a passion for solving complex technical problems and a commitment to staying up-to-date with the latest developments in machine learning. You have experience in early-stage clinical trial design and execution and knowledge of regulatory requirements and standards in clinical trials. Relocation benefits are available for this job posting. The expected salary range for this position based on the primary location of South San Francisco, CA is $188,200 to $349,400. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below. Genentech is an equal opportunity employer, and we embrace the increasingly diverse world around us. Genentech prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin or ancestry, age, disability, marital status and veteran status. J-18808-Ljbffr

Are you passionate about machine learning and using Generative AI models to improve customer experience? That is what we, the Intelligent Agents team at Expedia, do. Our mission is to provide a platform that powers intelligent agent experiences (conversational and non-conversational) for Expedia customers with Generative AI being the core of it. The platform supports over 2M conversations per week.
What you will do:
Utilize SQL, Python, and other relevant tools to efficiently extract and merge data from diverse sources and create comprehensive datasets essential for building models and/or fine-tuning large language models.
Conduct exploratory data analysis to understand data distributions, trends, and potential challenges.
Fine-tune pre-existing Large Language Models (LLMs) to address specific business problems and domains.
Engage in prompt engineering, crafting tailored prompts and inputs to guide LLM outputs toward desired business outcomes.
Experiment with fine-tuning strategies, prompt designs, and domain-specific adaptations to optimize LLM performance for travel domain applications.
Work closely with stakeholders to understand business objectives, translate them into actionable tasks for LLM fine-tuning, and iterate on feedback-based solutions.
Contribute to developing innovative approaches for leveraging LLMs to solve business challenges, driving value and impact for the organization.
Document experimental procedures, findings, and results clearly and organized.
Communicate progress, challenges, and proposed solutions effectively to team members and stakeholders.
Give feedback to other MLS in the team meetings and help them with technical discussions.
Stay updated with the latest research papers, techniques, and best practices in the field of LLMs and related areas, and lead regular meet-ups with other MLSs in the team to discuss them.
Develop an understanding of ethical considerations related to LLMs, including bias, fairness, privacy, and misinformation issues.
Collaborate effectively with team members from diverse backgrounds, including product managers, engineers, and domain experts.
Who you are:
Experience: 7+ years for Bachelor's OR 5+ years for Master's OR 4+ years for PhD.
Learned experience across a wide range of technologies and algorithms with strong algorithm design and object-oriented programming skills in at least one of the major programming languages like Java, C/C++, Python.
Working knowledge of Generative AI and AI ethics.
Built and maintained multiple data science projects/products in production environments.
Participated in the technical community, including blog posts, tech talks, open source contributions, or data mining competitions.
Vocal with opinions and energized by new ideas, keen to educate others with excellent written and verbal communication.
The total cash range for this position in Seattle is $173,000.00 to $242,500.00. Employees in this role have the potential to increase their pay up to $277,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.
Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual’s knowledge, skills, and experience. Pay ranges may be modified in the future.
Expedia Group is proud to offer a wide range of benefits to support employees and their families, including medical/dental/vision, paid time off, and an Employee Assistance Program. To fuel each employee’s passion for travel, we offer a wellness & travel reimbursement, travel discounts, and an International Airlines Travel Agent (IATAN) membership. View our full list of benefits.
About Expedia Group
Expedia Group (NASDAQ: EXPE) powers travel for everyone, everywhere through our global platform. Driven by the core belief that travel is a force for good, we help people experience the world in new ways and build lasting connections. We provide industry-leading technology solutions to fuel partner growth and success, while facilitating memorable experiences for travelers. Expedia Group's family of brands includes: Brand Expedia, Hotels.com, Expedia Partner Solutions, Vrbo, trivago, Orbitz, Travelocity, Hotwire, Wotif, ebookers, CheapTickets, Expedia Group Media Solutions, Expedia Local Expert, CarRentals.com, and Expedia Cruises.
Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. This employer participates in E-Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 to confirm work authorization.

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We are seeking a pioneering Senior Machine Learning Scientist to join our Discovery Science ML team at Coursera, focusing on creating the next generation of hyper-personalized search systems and recommender systems. The candidate will play an instrumental role in researching and developing state-of-the-art techniques for relevant search and recommendations. In addition to helping build robust systems, this role requires keeping abreast of emerging trends and innovations in machine learning, information retrieval, and online education.
Responsibilities:
Design, develop, and maintain advanced search ranking models, leveraging machine learning techniques such as label collection, personalized ranking, candidate retrieval, user behavior analysis, & LLM’s.
Explore and implement robust query understanding functionality, document understanding, user preference understanding, and low latency transformer-based architectures to improve search relevance.
Collaborate with cross-functional teams to align research goals with business needs and ensure successful deployment of innovative search solutions into production.
Build and manage large-scale search datasets, including corpora, relevance labels, and user interactions, utilizing tools and techniques for data collection, cleaning, and preprocessing.
Conduct thorough evaluations of search models using industry-standard metrics, analyze results, and provide insights for model improvement and business strategy.
Stay up-to-date with the latest trends in ML, search science, RecSys, and information retrieval, frequently attending conferences, workshops, and engaging in collaborative research projects.
Contribute to Coursera's research efforts by publishing in top-tier conferences such as SIGIR, WWW, CIKM, and similar venues.
Basic Qualifications:
PhD or Master's degree in Computer Science, Information Retrieval, or closely related fields.
Demonstrated experience in developing advanced search models, recommender systems, incorporating techniques like natural language processing (NLP) and learning-to-rank algorithms.
Familiarity with information retrieval metrics, evaluation methodologies, and scalable search system architecture.
Track record of publishing research in top-tier conferences such as RecSys, SIGIR, EMNLP, WWW, CIKM, or similar venues.
Preferred Qualifications:
Proficiency in programming languages and deep learning frameworks such as Python, TensorFlow, or PyTorch.
Experience in working with large-scale search datasets and tools for data collection, cleaning, and preprocessing.
Familiarity with ML deployment in production environments and tools for version control, such as Git.
Proven ability to stay current with emerging research and technologies in the ML, search science, or recommender systems domain.
Experience collaborating with cross-functional teams and excellent communication abilities.
Passion for driving impact in the field of online education through innovative ML and search science techniques.
Familiarity with Coursera's platform and course offerings, as well as active participation in wider AI and Machine Learning communities, is a plus.
If this opportunity interests you, you might like these courses on Coursera:
Unsupervised Learning, Recommenders, Reinforcement Learning.
Recommender Systems: Evaluation and Metrics.
Compensation:
Coursera offers competitive pay and equitable compensation practices. Our job titles may span more than one career level. The targeted hiring base salary range for this role is between $134,000 - $200,000 for all Canada candidates. The actual base pay is dependent upon many factors, including but not limited to prior work experiences, training/education, transferable skills, business needs, and geographical location. The base pay range is subject to change and may be modified in the future. This role may also be eligible for variable pay, equity, and benefits.

#J-18808-Ljbffr

The Opportunity
We are seeking a highly skilled and motivated Principal Machine Learning Scientist to join the BRAID team (Biology Research | AI Development) within our Computational Sciences organization. This role will focus on building novel machine-learning methods to enhance drug development and clinical trial design, with a particular emphasis on early-stage clinical trials. The successful candidate will develop novel machine learning methods for multimodal clinical data, including generative models and representation learning, leveraging their expertise to improve trial efficiency, patient outcomes, and overall trial success rates. The candidate is expected to routinely publish work in top-tier Machine Learning and scientific venues.
We seek exceptional researchers with a demonstrated research background in machine learning, a passion for interdisciplinary research and technical problem-solving, and a proven ability to develop and implement ideas from research.
Key Responsibilities Lead research initiatives at the intersection of machine learning, biology, and clinical sciences.
Conceive and lead collaborations both internally and externally.
Maintain expertise at the forefront of multiple areas in machine learning and biology/clinical sciences.
Collaborate with cross-functional teams, including chemists, biostatisticians, clinical scientists, and data engineers, to integrate ML methods into clinical trial development.
Lead and contribute to the design and execution of clinical trials by developing foundation models using multimodal pre-clinical and clinical datasets.
Publish research findings in top-tier machine learning and scientific journals and present at leading conferences.
Mentor junior scientists and contribute to the strategic direction of the ML group within the Computational Science Organization.
Who you are Educational Background: Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, Physics, or a related field with a strong emphasis on machine learning.
Experience: Proven track record with 2+ years of experience developing and applying advanced ML models in a research or industry setting.
Technical Skills Proficiency in scientific programming languages such as Python as well as MLOps workflows (e.g., familiar with code version control, high-performance compute infrastructures, and machine learning experiment monitoring workflows).
Extensive experience with machine learning frameworks and libraries (e.g., JAX, PyTorch, Tensorflow).
Strong background in statistics, probabilistic modeling, and data analysis.
Domain Knowledge: Understanding of clinical trials, drug development, and biological data.
Soft Skills: Excellent communication, collaboration, and problem-solving skills.
Publications: Strong publication record and experience contributing to research communities, including scientific journals and conferences like NeurIPS, ICML, ICLR, CVPR, ICCV, etc.
Preferred You have an extensive track record of delivering innovative solutions in machine learning, strong communication skills with the ability to effectively communicate technical concepts to both technical and non-technical audiences as well as interfacing with scientific leadership.
You have practical experience in one or more of the following areas: reinforcement learning, geometric deep learning, representation learning, and generative learning.
You have a passion for solving complex technical problems and a commitment to staying up-to-date with the latest developments in machine learning.
You have experience in early-stage clinical trial design and execution and knowledge of regulatory requirements and standards in clinical trials.
Relocation benefits are available for this job posting.
The expected salary range for this position based on the primary location of South San Francisco, CA is $188,200 to $349,400. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
Genentech is an equal opportunity employer, and we embrace the increasingly diverse world around us. Genentech prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin or ancestry, age, disability, marital status and veteran status.

#J-18808-Ljbffr

Are you passionate about machine learning and using Generative AI models to improve customer experience? That is what we, the Intelligent Agents team at Expedia, do. Our mission is to provide a platform that powers intelligent agent experiences (conversational and non-conversational) for Expedia customers with Generative AI being the core of it. The platform supports over 2M conversations per week.What you will do:<ol><li>Utilize SQL, Python, and other relevant tools to efficiently extract and merge data from diverse sources and create comprehensive datasets essential for building models and/or fine-tuning large language models.</li><li>Conduct exploratory data analysis to understand data distributions, trends, and potential challenges.</li><li>Fine-tune pre-existing Large Language Models (LLMs) to address specific business problems and domains.</li><li>Engage in prompt engineering, crafting tailored prompts and inputs to guide LLM outputs toward desired business outcomes.</li><li>Experiment with fine-tuning strategies, prompt designs, and domain-specific adaptations to optimize LLM performance for travel domain applications.</li><li>Work closely with stakeholders to understand business objectives, translate them into actionable tasks for LLM fine-tuning, and iterate on feedback-based solutions.</li><li>Contribute to developing innovative approaches for leveraging LLMs to solve business challenges, driving value and impact for the organization.</li><li>Document experimental procedures, findings, and results clearly and organized.</li><li>Communicate progress, challenges, and proposed solutions effectively to team members and stakeholders.</li><li>Give feedback to other MLS in the team meetings and help them with technical discussions.</li><li>Stay updated with the latest research papers, techniques, and best practices in the field of LLMs and related areas, and lead regular meet-ups with other MLSs in the team to discuss them.</li><li>Develop an understanding of ethical considerations related to LLMs, including bias, fairness, privacy, and misinformation issues.</li><li>Collaborate effectively with team members from diverse backgrounds, including product managers, engineers, and domain experts.</li></ol>Who you are:<ol><li>Experience: 7+ years for Bachelor's OR 5+ years for Master's OR 4+ years for PhD.</li><li>Learned experience across a wide range of technologies and algorithms with strong algorithm design and object-oriented programming skills in at least one of the major programming languages like Java, C/C++, Python.</li><li>Working knowledge of Generative AI and AI ethics.</li><li>Built and maintained multiple data science projects/products in production environments.</li><li>Participated in the technical community, including blog posts, tech talks, open source contributions, or data mining competitions.</li><li>Vocal with opinions and energized by new ideas, keen to educate others with excellent written and verbal communication.</li></ol>The total cash range for this position in Seattle is $173,000.00 to $242,500.00. Employees in this role have the potential to increase their pay up to $277,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual’s knowledge, skills, and experience. Pay ranges may be modified in the future.Expedia Group is proud to offer a wide range of benefits to support employees and their families, including medical/dental/vision, paid time off, and an Employee Assistance Program. To fuel each employee’s passion for travel, we offer a wellness & travel reimbursement, travel discounts, and an International Airlines Travel Agent (IATAN) membership. View our full list of benefits.About Expedia GroupExpedia Group (NASDAQ: EXPE) powers travel for everyone, everywhere through our global platform. Driven by the core belief that travel is a force for good, we help people experience the world in new ways and build lasting connections. We provide industry-leading technology solutions to fuel partner growth and success, while facilitating memorable experiences for travelers. Expedia Group's family of brands includes: Brand Expedia, Hotels.com, Expedia Partner Solutions, Vrbo, trivago, Orbitz, Travelocity, Hotwire, Wotif, ebookers, CheapTickets, Expedia Group Media Solutions, Expedia Local Expert, CarRentals.com, and Expedia Cruises.Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. This employer participates in E-Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 to confirm work authorization.
#J-18808-Ljbffr

The Opportunity We are seeking a highly skilled and motivated Principal Machine Learning Scientist to join the BRAID team (Biology Research | AI Development) within our Computational Sciences organization. This role will focus on building novel machine-learning methods to enhance drug development and clinical trial design, with a particular emphasis on early-stage clinical trials. The successful candidate will develop novel machine learning methods for multimodal clinical data, including generative models and representation learning, leveraging their expertise to improve trial efficiency, patient outcomes, and overall trial success rates. The candidate is expected to routinely publish work in top-tier Machine Learning and scientific venues. We seek exceptional researchers with a demonstrated research background in machine learning, a passion for interdisciplinary research and technical problem-solving, and a proven ability to develop and implement ideas from research. <h3>Key Responsibilities </h3><ul><li>Lead research initiatives at the intersection of machine learning, biology, and clinical sciences. </li><li>Conceive and lead collaborations both internally and externally. </li><li>Maintain expertise at the forefront of multiple areas in machine learning and biology/clinical sciences. </li><li>Collaborate with cross-functional teams, including chemists, biostatisticians, clinical scientists, and data engineers, to integrate ML methods into clinical trial development. </li><li>Lead and contribute to the design and execution of clinical trials by developing foundation models using multimodal pre-clinical and clinical datasets. </li><li>Publish research findings in top-tier machine learning and scientific journals and present at leading conferences. </li><li>Mentor junior scientists and contribute to the strategic direction of the ML group within the Computational Science Organization. </li> </ul><h3>Who you are </h3><ul><li>Educational Background: Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, Physics, or a related field with a strong emphasis on machine learning. </li><li>Experience: Proven track record with 2+ years of experience developing and applying advanced ML models in a research or industry setting. </li> </ul><h3>Technical Skills </h3><ul><li>Proficiency in scientific programming languages such as Python as well as MLOps workflows (e.g., familiar with code version control, high-performance compute infrastructures, and machine learning experiment monitoring workflows). </li><li>Extensive experience with machine learning frameworks and libraries (e.g., JAX, PyTorch, Tensorflow). </li><li>Strong background in statistics, probabilistic modeling, and data analysis. </li><li>Domain Knowledge: Understanding of clinical trials, drug development, and biological data. </li><li>Soft Skills: Excellent communication, collaboration, and problem-solving skills. </li><li>Publications: Strong publication record and experience contributing to research communities, including scientific journals and conferences like NeurIPS, ICML, ICLR, CVPR, ICCV, etc. </li> </ul><h3>Preferred </h3><ul><li>You have an extensive track record of delivering innovative solutions in machine learning, strong communication skills with the ability to effectively communicate technical concepts to both technical and non-technical audiences as well as interfacing with scientific leadership. </li><li>You have practical experience in one or more of the following areas: reinforcement learning, geometric deep learning, representation learning, and generative learning. </li><li>You have a passion for solving complex technical problems and a commitment to staying up-to-date with the latest developments in machine learning. </li><li>You have experience in early-stage clinical trial design and execution and knowledge of regulatory requirements and standards in clinical trials. </li> </ul>Relocation benefits are available for this job posting. The expected salary range for this position based on the primary location of South San Francisco, CA is $188,200 to $349,400. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below. Genentech is an equal opportunity employer, and we embrace the increasingly diverse world around us. Genentech prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin or ancestry, age, disability, marital status and veteran status. #J-18808-Ljbffr

We are seeking a pioneering Senior Machine Learning Scientist to join our Discovery Science ML team at Coursera, focusing on creating the next generation of hyper-personalized search systems and recommender systems. The candidate will play an instrumental role in researching and developing state-of-the-art techniques for relevant search and recommendations. In addition to helping build robust systems, this role requires keeping abreast of emerging trends and innovations in machine learning, information retrieval, and online education. Responsibilities: <ol><li>Design, develop, and maintain advanced search ranking models, leveraging machine learning techniques such as label collection, personalized ranking, candidate retrieval, user behavior analysis, & LLM’s. </li><li>Explore and implement robust query understanding functionality, document understanding, user preference understanding, and low latency transformer-based architectures to improve search relevance. </li><li>Collaborate with cross-functional teams to align research goals with business needs and ensure successful deployment of innovative search solutions into production. </li><li>Build and manage large-scale search datasets, including corpora, relevance labels, and user interactions, utilizing tools and techniques for data collection, cleaning, and preprocessing. </li><li>Conduct thorough evaluations of search models using industry-standard metrics, analyze results, and provide insights for model improvement and business strategy. </li><li>Stay up-to-date with the latest trends in ML, search science, RecSys, and information retrieval, frequently attending conferences, workshops, and engaging in collaborative research projects. </li><li>Contribute to Coursera's research efforts by publishing in top-tier conferences such as SIGIR, WWW, CIKM, and similar venues. </li> </ol>Basic Qualifications: <ol><li>PhD or Master's degree in Computer Science, Information Retrieval, or closely related fields. </li><li>Demonstrated experience in developing advanced search models, recommender systems, incorporating techniques like natural language processing (NLP) and learning-to-rank algorithms. </li><li>Familiarity with information retrieval metrics, evaluation methodologies, and scalable search system architecture. </li><li>Track record of publishing research in top-tier conferences such as RecSys, SIGIR, EMNLP, WWW, CIKM, or similar venues. </li> </ol>Preferred Qualifications: <ol><li>Proficiency in programming languages and deep learning frameworks such as Python, TensorFlow, or PyTorch. </li><li>Experience in working with large-scale search datasets and tools for data collection, cleaning, and preprocessing. </li><li>Familiarity with ML deployment in production environments and tools for version control, such as Git. </li><li>Proven ability to stay current with emerging research and technologies in the ML, search science, or recommender systems domain. </li><li>Experience collaborating with cross-functional teams and excellent communication abilities. </li><li>Passion for driving impact in the field of online education through innovative ML and search science techniques. </li><li>Familiarity with Coursera's platform and course offerings, as well as active participation in wider AI and Machine Learning communities, is a plus. </li> </ol>If this opportunity interests you, you might like these courses on Coursera: <ol><li>Unsupervised Learning, Recommenders, Reinforcement Learning. </li><li>Recommender Systems: Evaluation and Metrics. </li> </ol>Compensation: Coursera offers competitive pay and equitable compensation practices. Our job titles may span more than one career level. The targeted hiring base salary range for this role is between $134,000 - $200,000 for all Canada candidates. The actual base pay is dependent upon many factors, including but not limited to prior work experiences, training/education, transferable skills, business needs, and geographical location. The base pay range is subject to change and may be modified in the future. This role may also be eligible for variable pay, equity, and benefits. #J-18808-Ljbffr

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Machine Learning Scientist Karkidi Jobs

Principal Machine Learning Scientist Gcs BraidDecember 19, 2024

Senior Machine Learning ScientistDecember 11, 2024

Senior Machine Learning Scientist DiscoveryDecember 10, 2024

Principal Machine Learning Scientist Gcs BraidDecember 10, 2024

Senior Machine Learning ScientistDecember 9, 2024

Principal Machine Learning Scientist Gcs BraidDecember 9, 2024

Senior Machine Learning Scientist DiscoveryDecember 9, 2024