Palo Alto

Our formula for success is to hire exceptional people, encourage their ideas and reward their results.

As an AI Researcher, you will be an integral member of a team of experienced technologists, researchers, quants and traders. You will collaborate closely with two other researchers to solve challenging AI and machine learning problems. Your projects will vary depending on priorities at the start of your employment and could include AI for time series modeling, or developing large language models (LLMs). We are looking for individuals eager to learn new AI technologies, create innovative solutions, and choose the right tools to directly impact our business. You will be surrounded by cutting-edge technology, given immediate responsibility, mentored by industry-leading experts, and attend a robust training program to ensure your success at DRW.

How you will make an impact... Algorithm Development: Creating and testing new AI models and algorithms to solve specific problems or improve existing methods. Data Engineering: Building data pipelines for model training and evaluation, including data collection, cleaning, preprocessing, and labeling, while contributing to better data management practices. Model Testing & Evaluation: Designing and implementing rigorous testing frameworks to assess model performance and identify areas for improvement. Collaboration: Working closely with team members to establish and refine research methodologies, promoting peer reviews, testing, and thorough documentation. Research & Learning: Staying updated on the latest AI techniques and advancements, sharing insights, and actively bringing improvements to research processes.

You will be right at home if you have… A PhD in artificial intelligence, machine learning, computer science, or a related field graduating between December 2025 and June 2026. Strong foundation in AI concepts. Strong knowledge of machine learning. Solid technical and programming skills (Python, Java, GitHub). Familiarity with machine learning framework (Spark, PyTorch, etc.). Excellent analytical, problem-solving, and communication skills. Deep interest in financial markets. Experience with NLP tasks Knowledge of TensorFlow or PyTorch. Basic understanding of MLOps principles (monitoring, versioning, model serving).

Learning Opportunities: Gain in-depth experience with cutting-edgeML/AI techniques and model deployment. Develop robust machine learning research skills, from data engineering to model evaluation, while contributing to advancements in AI methodologies and practices. Contribute to research projects with potential impact on financial decision-making and other applied domains. Engage in fostering a collaborative research culture, driving improvements in research quality, and interdisciplinary collaboration.

The annual base salary range for this position is $175,000 to $200,000 depending on the candidate’s experience, qualifications, and relevant skill set. The position is also eligible for an annual discretionary bonus. In addition, DRW offers a comprehensive suite of employee benefits including group medical, pharmacy, dental and vision insurance, 401k (with discretionary employer match), short and long-term disability, life and AD&D insurance, health savings accounts, and flexible spending accounts.

For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice.

California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice.

San Francisco

WRITER is looking for an AI engineer with a strong software engineering background to join our expanding team of AI experts.

At WRITER, we believe in using the power of AI to unlock the potential of the enterprise. With the help of our AI engineers, we can continue to build the most advanced language model available in the industry and revolutionize how companies interact with AI. We’re looking for a creative problem solver who has a deep understanding of NLP and ML technologies and who can help us create powerful and meaningful applications of AI.

As an AI engineer at WRITER, you'll play a pivotal role in developing and implementing state-of-the-art generative AI models and algorithms. Collaborating closely with our diverse and dynamic team of software engineers, data scientists, and researchers, you'll be able to design and deploy AI solutions that drive our innovative products.

If you’re passionate about using AI to transform the enterprise, we want to hear from you.

Your responsibilities

• Collaborate closely with our broader engineering team, data scientists, and AI engineers to evolve our software architecture as we productize new AI-powered capabilities
• Evaluate the performance of AI models & systems through rigorous testing and experimentation.
• Deploy LLM-based applications in production, evaluating and improving their performance over time
• Collaborate with our skilled software engineers to seamlessly integrate AI-powered capabilities into production systems, ensuring scalability and efficiency.
• Stay up-to-date with the latest advancements in AI and machine learning research, and proactively suggest improvements to enhance our generative AI capabilities.
• Collaborate closely with cross-functional teams to understand business requirements and translate them into innovative AI solutions.
• Own the design, implementation, and maintenance of robust and scalable production retrieval and agentic systems
• Implement strong testing and CI/CD practices that help us move with confidence in our AI system development

Is this you?

• Bachelor’s degree in Computer Science, Engineering, Mathematics, related field, or equivalent experience
• High level of coding proficiency using Python
• 5+ years of professional experience in software engineering, AI/ML development including:
• Proficiency with production software (Python) and systems design
• Machine learning algorithms and model development techniques
• ML lifecycle tools like MLflow, dvc, weights & biases
• Cloud deployment of ML systems
• Professional experience with LLMs and large-scale models
• Very strong software engineering skills with a track record of building scalable, distributed product machine learning systems
• Strong analytical and problem-solving skills
• Ability to communicate complex ideas and concepts effectively
• Ability to work independently and collaboratively

Palo Alto, CA

Position Description: As a Software Engineer for the Optimus team, you will build the tools and infrastructure to make and measure improvements to neural network architecture, visualize data, assist with exporting and deploying neural networks to the bot, and evaluate experimental results. You will help us automate the entire workflows of training, validation, and production of the Optimus. Most importantly, you will see your work repeatedly shipped to and utilized by thousands of Humanoid Robots in real world applications.

Responsibilities: Build and improve our Python training infrastructure for stable and faster training

Build the tooling and infrastructure for reporting and visualizing model metrics and performance

Build the pipelines to run and validate our PyTorch models

Manage, analyze, and visualize our training and test datasets

Coordinate with the team managing the hardware cluster to maintain high availability / jobs throughput for Machine Learning

Build and improve tooling to deploy trained neural nets to Tesla hardware

Requirements: Practical experience programming in Python and/or C++

Proficient in system-level software, particularly hardware-software interactions and resource utilization

Understanding of modern machine learning concepts and state of the art deep learning

Experience working with training frameworks, ideally PyTorch

Demonstrated experience scaling neural network training jobs across clusters of GPU’s

Optional: Previous experience in deep learning deployment

Optional: Profiling and optimizing CPU-GPU interactions (pipelining compute/transfers, etc)

San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US; Remote, US

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.

We are looking for a Principal Machine Learning Engineer, a senior technical visionary, to be the Principal Technical Lead for our Content Engineering team setting up overall technical strategy, unified technical architecture and defining a roadmap for industry‑leading methodology. Strong hands-on machine learning background including deep learning architectures, generative AI, low-resource ML (zero shot, few shot), responsible AI and large scale deployment and measurement is required.

As the Principal Tech Lead for Content you'll be responsible for the technical direction, strategy and health of our Content Engineering org. You'll ensure that our technology can deliver on the business/product requirements necessary to keep Pinterest safe and positive. This means working with other leads to set and execute a long-term strategy for Trust, aligning the strategy with other clients where it makes sense and communicating to leadership our current status and path to having world-class Trust capabilities. You'll also foster a healthy community where all Trust engineers can learn best practices, collaborate effectively and understand our technical direction.

What you’ll do

• Develop strong partnerships with product teams to understand and proactively address future technology needs and current developer pain points.
• Champion and drive large-scale, cross-functional initiatives that improve the trust and safety of our platform.
• Act as the ultimate “customer representative” for engineers on Trust, including representing needs to leadership and prioritizing projects on the platform teams that ensure high quality capabilities and a world-class Pinner experience.
• Scale your leadership through both direct mentorship and via best practices, processes, training and tools.
• Ensure solid technical plans are in place for projects within Trust via direct review or delegation.
• Be the technical point of contact for decisions that impact the whole Pinterest platform and for cross-functional partners like policy, operations and legal.

What we’re looking for:

• Deep expertise building large scale ML systems at scale with modern frameworks.
• Knowledge of (and a passion for) building responsible and quality‑first discovery surfaces.
• Track record of delivering large, cross-functional projects across multiple organizations.
• Strong written and verbal communication skills and proven ability to collaborate cross-functionally.

Postdoctoral Scholar: Computational Medicine Research Group, University of California, Irvine (NIH Funded)

The Computational Medicine Research Group directed by Prof. Pratik Shah at the University of California, Irvine, invites applications for an NIH-funded Postdoctoral Scholar position. We seek outstanding Ph.D. candidates in computer science, biomedical informatics, statistics, or related fields to develop novel deep learning and AI technologies for digital biopsies from medical images and clinical decision-making from non-imaging datasets. Research areas include:

• Generative AI for Medical Imaging & Digital Biopsies: Developing and interpreting DNNs for automated tissue analyses using high-parameter images (pathology, MRI, CT, RGB) and validating these models in collaboration with hospitals nationwide.

• Generative & Predictive AI for Clinical Decision Support: Developing biologically informed statistical methods and uncertainty estimation generative models for explainable clinical decision-making from EMRs and genetic data.

Responsibilities include data preprocessing, training and real-world validation of generative deep learning models (GANs, Diffusion models, Transformers), developing novel statistical models, and publishing research in leading journals and conferences. Comprehensive training in publication, fellowship and grant writing, and career development for roles in academia, industry, or government will be provided.More information about the lab can be found at https://faculty.sites.uci.edu/pratikshahlab/

Location UC Berkeley, Berkeley, CA US

Description The Bakar Institute of Digital Materials for the Planet (BIDMaP) is an institute in UC Berkeley’s new College of Computing, Data Science, and Society (CDSS), bringing together AI, machine learning and data science with the natural sciences to address the planet’s most urgent challenges. BIDMaP is focused on developing new techniques in AI that will enhance and accelerate discovery in experimental natural sciences and development of novel materials to address planetary challenges. To this end, BIDMaP promotes collaboration between world-renowned AI/ML experts, chemists, physicists and other physical scientists. By combining cutting-edge chemistry with artificial intelligence, machine learning, and robotics, BIDMaP is reimagining how materials can be designed and optimized for clean energy, clean air, clean water, advanced batteries, and sustainable chemical production.

San Jose, CA, USA

Join Adobe as a skilled and proactive Machine Learning Ops Engineer to drive the operational reliability, scalability, and performance of our AI systems! This role is foundational in ensuring our AI systems operate seamlessly across environments while meeting the needs of both developers and end users. You will lead efforts to automate and optimize the full machine learning lifecycle—from data pipelines and model deployment to monitoring, governance, and incident response.

What you'll Do

• Model Lifecycle Management: Manage model versioning, deployment strategies, rollback mechanisms, and A/B testing frameworks for LLM agents and RAG systems. Coordinate model registries, artifacts, and promotion workflows in collaboration with ML Engineers

• Monitoring & Observability: Implement real-time monitoring of model performance (accuracy, latency, drift, degradation). Track conversation quality metrics and user feedback loops for production agents.

• CI/CD for AI: Develop automated pipelines for timely/agent testing, validation, and deployment. Integrate unit/integration tests into model and workflow updates for safe rollouts.

• Infrastructure Automation: Provision and manage scalable infrastructure (Kubernetes, Terraform, serverless stacks). Enable auto-scaling, resource optimization, and load balancing for AI workloads.

• Data Pipeline Management: Craft and maintain data ingestion pipelines for both structured and unstructured sources. Ensure reliable feature extraction, transformation, and data validation workflows.

• Performance Optimization: Monitor and optimize AI stack performance (model latency, API efficiency, GPU/compute utilization). Drive cost-aware engineering across inference, retrieval, and orchestration layers.

• Incident Response & Reliability: Build alerting and triage systems to identify and resolve production issues. Maintain SLAs and develop rollback/recovery strategies for AI services.

• Compliance & Governance: Enforce model governance, audit trails, and explainability standards. Support documentation and regulatory frameworks (e.g., GDPR, SOC 2, internal policy alignment).

What you need to succeed - 3–5+ years in MLOps, DevOps, or ML platform engineering. - Strong experience with cloud infrastructure (AWS/GCP/Azure), container orchestration (Kubernetes), and IaC tools (Terraform, Helm). - Familiarity with ML model serving tools (e.g., MLflow, Seldon, TorchServe, BentoML). - Proficiency in Python and CI/CD automation (e.g., GitHub Actions, Jenkins, Argo Workflows). - Experience with monitoring tools (Prometheus, Grafana, Datadog, ELK, Arize AI, etc.).

Preferred Qualifications - Experience supporting LLM applications, RAG pipelines, or AI agent orchestration. - Understanding of vector databases, embedding workflows, and model retraining triggers. - Exposure to privacy, safety, and responsible AI principles in operational contexts. - Bachelor's or equivalent experience in Computer Science, Engineering, or a related technical field.

Johns Hopkins University

We invite applications for Postdoctoral Fellow positions in the broad areas of data science and AI, with a focus on developing and applying novel data science approaches, computational tools and statistical methods to advance health and biomedical research. Johns Hopkins University has recently made transformative new investment in launching a new Data Science and AI institute that will serve as the hub for interdisciplinary data collaborations with faculties and students from across Johns Hopkins and will build the nation’s foremost destination for emerging applications, opportunities and challenges presented by data science, machine learning and AI.

About AIMATX

AIMATX is a Berkeley-based startup revolutionizing materials science by creating next-generation materials and molecules that power the future economy. Our AI-driven platform explores vast chemical spaces, predicts new materials and their properties, and accelerates discovery through intelligent, targeted experimentation. By reducing years of R&D to weeks, we are shaping the future of materials innovation;come join us!

AIMATX is built and guided by a world-class team at the intersection of science, AI and engineering. Our leadership includes Omar Yaghi (2025 Nobel Prize), Fernando Perez inventor of Jupyter/IPython, alongside former CEOs of public companies and leading researchers in generative AI and autonomous experimentation. This ecosystem brings unmatched scientific depth, computational expertise, and entrepreneurial excellence to accelerate the future of discovery.

Role Overview

We are seeking a highly skilled Computational Chemist / Materials Scientist to join our innovative team. You will apply your expertise in chemical and materials science R&D to develop sustainable, high-performance materials tailored to specific use cases. As part of our technical team, you will:

• Develop and apply AI-computational tools to predict novel material structures and properties.
• Design and implement machine learning algorithms to analyze large datasets and predict material behavior.
• Build AI-based methods for synthesis prediction of candidate materials.
• Collaborate with engineering teams to translate computational predictions into high-throughput experimental workflows.
• Incorporate experimental feedback into predictive models to improve accuracy within a closed-loop, self-improving platform.
• Analyze and visualize theoretical and experimental data, presenting insights to stakeholders and guiding research and product strategy.
• Work with data science experts to quantify and calibrate uncertainties across the predictive pipeline.
• Stay current with scientific advances and integrate relevant ideas into ongoing projects.
• Implement computational methods in a rigorously tested codebase deployed using modern software engineering best practices.

Required Qualifications

• PhD in Machine Learning, Computational Chemistry, Chemistry, Materials Science, Physics or a related field.
• Experience applying machine learning to scientific or structured data
• Proficiency with Python, GitHub workflows, testing, documentation, and continuous integration.
• Demonstrated leadership and project ownership in computational or ML-driven research.

Preferred Qualifications

• Experience developing modeling approaches, including physics-based atomistic modeling.
• Experience in polymer chemistry, ceramics, nanomaterials, or related areas.
• Publication record in peer-reviewed journals and presentations at scientific conferences.

Soft Skills & Cultural Fit

• Excellent written and verbal communication skills.
• Collaborative mindset and ability to work effectively in a multidisciplinary team.
• Strong organization, attention to detail, and a results-driven attitude.
• Proactive and self-motivated, with the ability to take initiative.
• Commitment to scientific rigor, innovation, and continuous learning.

Benefits & Perks

We offer a competitive salary with bonus potential and meaningful early equity. Compensation reflects experience, expertise and expected impact.

Additional benefits may include: - Flexible work arrangements and remote options. - Medical, dental, and vision coverage. - 401(k) with company matching. - Generous PTO and parental leave.

Equal Opportunity Statement

AIMATX is committed to fostering a diverse and inclusive workplace. All qualified applicants will receive consideration without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, disability, or vet

Send your CV to theo.jaf@aimatx.ai

New York

As a Data Scientist, you will analyze complex datasets, build predictive models, and generate insights that drive strategic decisions. You’ll partner with engineers, researchers, and business leaders to turn data into actionable outcomes. Opportunities may be available from time to time in any location in which the business is based for suitable candidates. If you are interested in a career with Citadel, please share your details and we will contact you if there is a vacancy available.