7,877 Machine Learning Engineers jobs in the United States

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.

• Design, develop, and implement deep learning models.
• Conduct research and experiments on large datasets.
• Utilize frameworks like TensorFlow, PyTorch, or Keras for model development.
• Train, evaluate, and fine-tune neural networks for optimal performance.
• Deploy machine learning models into production environments.
• Optimize models for scalability, efficiency, and accuracy.
• Collaborate with data scientists and software engineers on AI projects.
• Stay up-to-date with the latest advancements in AI and machine learning.
• Develop and implement strategies for data preprocessing and feature engineering.
• Contribute to technical documentation and present findings to stakeholders.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Minimum of 3-5 years of experience in AI/ML engineering, with a focus on deep learning.
• Proficiency in Python and experience with relevant libraries (e.g., NumPy, Pandas, Scikit-learn).
• Hands-on experience with deep learning frameworks (TensorFlow, PyTorch).
• Strong understanding of various neural network architectures (CNNs, RNNs, Transformers).
• Experience with data preprocessing, feature engineering, and model evaluation.
• Familiarity with cloud platforms (AWS, GCP, Azure) for ML deployment is a plus.
• Strong analytical and problem-solving skills.
• Excellent programming and software development skills.
• Strong communication and teamwork abilities.

• Lead and conduct cutting-edge research in deep learning, neural networks, and related AI fields.
• Develop novel algorithms and models to address complex scientific and technological challenges.
• Publish research findings in top-tier academic conferences and journals.
• Collaborate with cross-functional teams to integrate research outcomes into product development.
• Mentor and guide junior researchers and engineers, fostering a culture of innovation and academic rigor.
• Identify new research directions and opportunities for technological advancement.
• Represent the institution at conferences and workshops, contributing to the broader AI community.
• Develop and maintain strong relationships with academic and industry partners.
• Oversee the management of research projects, including resource allocation and timelines.
• Ensure the ethical development and application of AI technologies.

• Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Minimum of 10 years of post-doctoral research experience in deep learning and neural networks.
• A strong publication record in leading AI conferences (e.g., NeurIPS, ICML, ICLR) and journals.
• Proven expertise in developing and implementing deep learning models using frameworks like TensorFlow, PyTorch, or Keras.
• Demonstrated experience in leading research teams and managing complex research projects.
• Exceptional analytical, problem-solving, and critical thinking skills.
• Outstanding communication, presentation, and interpersonal skills.
• Ability to articulate complex technical concepts to both technical and non-technical audiences.
• Experience with large-scale data processing and high-performance computing environments is advantageous.
• Passion for exploring and advancing emerging AI technologies.

• Designing, developing, and deploying scalable deep learning models for various applications, such as natural language processing, computer vision, and predictive analytics.
• Collaborating with cross-functional teams, including data scientists, software engineers, and product managers, to define AI strategies and roadmaps.
• Evaluating and selecting appropriate AI algorithms, frameworks, and tools for specific project requirements.
• Optimizing deep learning models for performance, efficiency, and accuracy in production environments.
• Developing proof-of-concepts and prototypes to demonstrate the feasibility of AI solutions.
• Providing technical leadership and mentorship to junior team members.
• Staying current with the latest advancements in AI research, machine learning, and deep learning.
• Documenting AI architectures, methodologies, and best practices.
• Translating complex business problems into viable AI solutions.
• Ensuring ethical considerations and responsible AI development practices are integrated into all projects.

• Conduct cutting-edge research in deep learning and related AI fields.
• Develop, implement, and evaluate novel AI models and algorithms.
• Publish research findings in leading academic conferences and journals.
• Collaborate with a global, remote team of researchers and engineers.
• Design and execute experiments to validate hypotheses and assess model performance.
• Contribute to the development of AI-powered products and solutions.
• Stay current with the latest advancements in AI and machine learning.
• Mentor junior researchers and contribute to a collaborative research environment.
• Effectively communicate research progress and results through written reports and presentations.

• Ph.D. or Master's degree in Computer Science, AI, Machine Learning, or a related quantitative field.
• Proven track record of research excellence, demonstrated by publications in top-tier AI venues.
• Extensive experience with deep learning frameworks (e.g., TensorFlow, PyTorch, Keras, JAX).
• Strong programming skills in Python and experience with scientific computing libraries.
• Deep understanding of machine learning theory, statistics, and algorithms.
• Experience in one or more areas: NLP, Computer Vision, Reinforcement Learning, Generative Models.
• Excellent analytical, critical thinking, and problem-solving abilities.
• Demonstrated ability to work independently and collaboratively in a remote setting.
• Strong communication and presentation skills.