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 Machine Learning Engineer with deep expertise in large-scale generative models (e.g., LLMs, diffusion models) to join our innovative team. You will design, build, and scale the core AI systems that power our materials discovery engine, enabling rapid experimentation, robust deployment, and continuous improvement. As part of our technical team, you will:

• Design and implement training pipelines for LLMs, diffusion models and related architectures for molecular, materials and experimental design.
• Build robust data pipelines and preprocessing workflows for multimodal scientific data.
• Optimize model training and inference at scale, including distributed training and mixed-precision acceleration.
• Develop evaluation, benchmarking and monitoring frameworks to assess reliability, calibration and performance of generative models.
• Collaborate with scientists and engineers to integrate models into self-driving lab workflows and closed-loop experimentation.
• Work closely with MLOps and platform teams to ensure reproducibility, experiment tracking and scalable deployment.
• Stay current with advances in LLMs, diffusion models, reinforcement learning and agentic AI, and translate promising ideas into production systems.
• Maintain high engineering standards, including testing, documentation and code review.

Required Qualifications

• Degree in Computer Science, Machine Learning, Applied Mathematics, Engineering or a related technical field (or equivalent practical experience).
• Strong software engineering experience building and maintaining ML systems in production.
• Expertise with deep learning frameworks such as PyTorch or JAX.
• Proficiency with Python and experience working in collaborative, large-scale codebases.
• Demonstrated track record of owning and delivering end-to-end ML projects from prototype to production.

Preferred Qualifications

• Experience working with generative models in chemistry or materials science.
• Background or strong interest in scientific domains (chemistry, materials science, physics, biology) or scientific ML.
• Contributions to open-source ML or infrastructure projects, or publications in ML/AI conferences or journals.
• Expertise in training large-scale generative models (e.g., LLMs, diffusion models).

Soft Skills & Cultural Fit

• Excellent written and verbal communication skills.
• Collaborative mindset and ability to work effectively in a multidisciplinary team.
• 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.

How to Apply

Send your CV to theo.jaf@aimatx.ai

UK

Research Engineer - Novel AI applications and Next Generation Hardware

Mission: You will join the hardware team with the goal of supporting novel application areas and AI modes beyond current use cases. Responsibilities include researching the evolving landscape of AI applications and models, analyzing underlying model architectures, and building implementations on Groq. Further responsibilities include analyzing mappings to existing and future hardware, modeling performance, and working cross-functionally with the hardware design team on novel hardware features e.g. functional units, numeric modes, interconnect, system integration, etc to unlock novel application areas for Groq. There will be opportunities to participate in a wider range of R&D activities, either internally or externally with key Groq partners.

Responsibilities & opportunities in this role: AI application and model research Performance modeling Cross-functional work with hardware and software teams Next generation hardware architecture development Support internal and outward-facing R&D

Ideal candidates have/are: Strong foundation in computer science Experience with AI models and applications Knowledge of LLMs and other Gen AI applications Strong foundation in computer architecture and computer arithmetic Python and common ML frameworks such as PyTorch & TensorFlow Experience with performance analysis / modelling Problem solving mindset

Nice to Have: Experience with scientific computing & HPC Experience in optimizing applications on specialized accelerators (GPU, FPGA, or other custom accelerators). Experience with compiler tools and MLIR. Experience in delivering complex projects in a fast-moving environment.

Attributes of a Groqster: Humility - Egos are checked at the door Collaborative & Team Savvy - We make up the smartest person in the room, together Growth & Giver Mindset - Learn it all versus know it all, we share knowledge generously Curious & Innovative - Take a creative approach to projects, problems, and design Passion, Grit, & Boldness - no limit thinking, fueling informed risk taking

Compensation: At Groq, a competitive base salary is part of our comprehensive compensation package, which includes equity and benefits. For this role, salary range is determined by your location, skills, qualifications, experience and internal benchmarks. Compensation for candidates outside the USA will be dependent on the local market.

This position may require access to technology and/or information subject to U.S. export control laws and regulations, as well as applicable local laws and regulations, including the Export Administration Regulations (EAR). To comply with these requirements, candidates for this role must meet all relevant export control eligibility criteria.

USA - Austin, Seattle

Job Overview

At Arm, we’re redefining what’s possible with AI. Whether it’s enabling edge devices to see and hear, empowering cloud platforms to learn at scale, or pioneering energy-efficient compute for autonomous systems - our AI engineers are at the forefront of building a smarter, connected world.

We’re looking for AI Engineers who are excited by the challenges and opportunities AI presents across industries. From optimizing machine learning performance on next-gen processors to contributing to cutting-edge research, if you’re passionate about the future of AI, we want to meet you.

Responsibilities

Depending on your background and experience, you could be involved in:

Designing and optimizing machine learning models for efficient deployment on Arm-based platforms Building high-performance AI software tools, libraries, and compilers Leading system-level architecture for next-gen AI accelerators Partnering with ecosystem collaborators on real-world ML applications Pushing the boundaries of AI/ML research for embedded, edge, or cloud use cases Understanding and working in a deep technology stack to deliver intelligent, efficient compute

Required Skills and Experience

Strong programming skills in Python, C/C++, or similar languages used in AI and high-performance computing Hands-on experience with machine learning frameworks such as TensorFlow, Pytorch, or ONNX Deep technical understanding of AI/ML model development, training, and inference Experience leading the design and architecture of reliable and scalable systems Ability to work across disciplines in a collaborative, technically ambitious, and fast-paced environment Excellent communication skills and problem solving mindset

“Nice to Have” Skills and Experience

Experience in model optimization for performance, efficiency, or deployment Exposure to deploying machine learning models on edge, devices, or mobile platforms Familiarity with Arm architecture and performance analysis tools

Bala Cynwyd (Philadelphia Area), Pennsylvania United States

Overview

We’re looking for a Machine Learning Systems Engineer to help build the data infrastructure that powers our AI research. In this role, you'll develop reliable, high-performance systems for handling large and complex datasets, with a focus on scalability and reproducibility. You’ll partner with researchers to support experimental workflows and help translate evolving needs into efficient, production-ready solutions. The work involves optimizing compute performance across distributed systems and building low-latency, high-throughput data services. This role is ideal for someone with strong engineering instincts, a deep understanding of data systems, and an interest in supporting innovative machine learning efforts.

What You’ll Do

Design and implement high-performance data pipelines for processing large-scale datasets with an emphasis on reliability and reproducibility Collaborate with researchers to translate their requirements into scalable, production-grade systems for AI experimentation Optimize resource utilization across our distributed computing infrastructure through profiling, benchmarking, and systems-level improvements Implement low-latency high-throughput sampling for models

What we're looking for

Experience building and maintaining data pipelines and ETL systems at scale Experience with large-scale ML infrastructure and familiarity with training and inference workflows Strong understanding of best practices in data management and processing Knowledge of systems level programming and performance optimization Proficiency in software engineering in python Understanding of AI/ML workloads, including data preprocessing, feature engineering, and model evaluation

Why Join Us?

Susquehanna is a global quantitative trading firm that combines deep research, cutting-edge technology, and a collaborative culture. We build most of our systems from the ground up, and innovation is at the core of everything we do. As a Machine Learning Systems Engineer, you’ll play a critical role in shaping the future of AI at Susquehanna — enabling research at scale, accelerating experimentation, and helping unlock new opportunities across the firm.

Successful hires will expand the group's efforts applying machine learning to drug discovery, biomolecular simulation, and biophysics. Areas of focus include generative models to help identify novel molecules for drug discovery targets, predict PK and ADME properties of small molecules, develop more accurate approaches for molecular simulations, and understand disease mechanisms. Ideal candidates will have strong Python programming skills. Relevant areas of experience might include deep learning techniques, systems software, high performance computation, numerical algorithms, data science, cheminformatics, medicinal chemistry, structural biology, molecular physics, 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. For more information, visit www.DEShawResearch.com.

Please apply using this link: https://apply.deshawresearch.com/careers/Register?pipelineId=597&source=NeurIPS_1

The expected annual base salary for this position is USD 300,000 - USD 800,000. Our compensation package also includes variable compensation in the form of sign-on and year-end bonuses, and generous benefits, including relocation and immigration assistance. 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. We follow a hybrid work schedule, in which employees work from the office on Tuesday through Thursday, and have the option of working from home on Monday and Friday.

D. E. Shaw Research, LLC is an equal opportunity employer.

New York

Quant Analyst

Quants at the D. E. Shaw group apply mathematical techniques and write software to develop, analyze, and implement statistical models for our computerized financial trading strategies. They utilize their creativity and innovation to create novel approaches to trade profitably in markets around the globe with a firm that offers a collegial, collaborative, and engaging working environment.

What you'll do day-to-day

Specific responsibilities range from leveraging financial data in an effort to increase profitability, decrease risk, and reduce transaction costs to conceiving new trading ideas, formulating them into systematic strategies, and critically evaluating their performance.

Who we're looking for

• Successful candidates will have impressive records of academic achievement and be the top students in their respective math, statistics, physics, engineering, computer science, and other technical and quantitative programs.
• The expected annual base salary for this position is 225,000USD for applicants who have completed undergraduate or master’s degrees and 250,000USD for applicants who have completed PhDs (or have comparable professional experience). Our compensation and benefits package includes substantial variable compensation in the form of a year-end bonus, guaranteed in the first year of hire, a sign-on bonus, a relocation bonus, and benefits including medical and prescription drug coverage, 401(k) contribution matching, wellness reimbursement, family building benefits, and a charitable gift match program.

About Kumo.ai

Kumo.ai is redefining enterprise AI with foundation models for relational data, enabling organizations to predict, optimize, and act with speed and confidence.
Our mission is simple yet ambitious: make the world’s most important data also its most useful.

At Kumo, we are committed to building cutting-edge products that are also intuitive and easy to use. Our work blends deep technical innovation with thoughtful user-centric design.

Our Culture

We foster an inclusive, collaborative culture where every individual contributes to our shared mission.
We value:

• Diversity of thought
• Open and transparent communication
• Working together to solve meaningful problems
• Serving our customers with excellence
• Building a supportive and thriving community

We’re Hiring

We are looking for ML/AI Engineers with experience in one or more of the following:

• Graph Neural Networks (GNNs)
• Graph Transformers
• Agentic Frameworks
• Applied Machine Learning

If you're excited about building the next generation of AI for relational data, we’d love to talk.

Work Location:

Toronto, Ontario, Canada

Description

We are currently seeking talented individuals for a variety of positions, ranging from junior to senior levels, and will evaluate your application in its entirety.

Layer 6 is the AI center of excellence for TD Bank Group. We develop and deploy industry-leading machine learning systems that impact the lives of over 27 million customers, helping more people achieve their financial goals and needs. Our work spans the field of machine learning with areas such as deep learning and generative AI, time series forecasting and responsible use of AI. We have access to massive financial datasets and actively collaborate with world renowned academic faculty. We are driven to be at the cutting edge of machine learning in research, engineering, and impactful applications.

We are looking for world-class engineers to tackle cutting-edge problems in Machine Learning applied to the real world. Work with large-scale, real-world datasets spanning multiple modalities, ranging from banking transactions, conversation transcripts to large document collections.

As a Machine Learning Engineer, you will:

• Join a world-class team of AI developers with an extensive track record of shipping solutions at the cutting-edge

• Architect scalable machine learning and Gen AI systems that integrate with existing data platform and infrastructure, focusing on automation, operation efficiency, and reliability

• Write clean, efficient, and maintainable code for ML models to ensure efficient deployment of scalable AI application

• Work with large-scale, real-world datasets that range from banking transactions, conversation histories, to large document collections

• Grow by continuously learning new skills and exploring advanced topics in AI with a team that thrives on knowledge-sharing

Required Qualifications:

• Master or bachelor's degree in computer science, Statistics, Mathematics, Engineering or a related field

• 3+ years of developer experience shipping code in production settings

• Strong background in machine learning and deep learning

• Strong coding proficiency in Python, Java, C, or C++ You value good software design and sweat over details in code and API design

• You take great personal pride in building robust and scalable software

• You are highly accountable and have a strong sense of ownership

• You strive to communicate clearly and with empathy

Preferred Qualifications:

• Research experience with publication record

• Experience with LangGraph, Pytorch, Tensorflow, Jax, or comparable library

• Experience with building and scaling data-intensive software

• Experience using GPUs for accelerated deep learning training

Senior Software Engineer (Backend)

Location: Boston (US) / Barcelona (Spain)

About us:

Axiomatic_AI is dedicated to accelerating R&D by developing the next generation of Automated Interpretable Reasoning, a verifiably truthful AI model built for reasoning in science and engineering, empowering engineers specifically in hardware design and Electronic Design Automation (EDA), with a mission to revolutionize the fields of hardware design and simulation in the photonics and semiconductor industry. We seek highly motivated professionals to help us bring these innovations to life, driving the evolution from development to commercial product.

Position Overview

As a Senior Software Engineer (Backend) at Axiomatic, you will:

• Design and build scalable backend services (FastAPI, FastMCP, Python)
• Own key features end-to-end: from API design to database schema to deployment
• Integrate AI capabilities (LLMs, Agents) into production systems
• Collaborate with frontend, AI, and infrastructure teams on architecture and delivery
• Ensure system reliability, performance, and security
• Mentor other engineers as the team grows

Key Responsibilities

Architecture & Design

• Contribute to system architecture and technical decisions
• Design for scalability, reliability, and security
• Propose and implement improvements to codebase and infrastructure
• Document technical designs and API contracts
• Ensure best practices are followed by the team

Backend Development

• Design and implement REST APIs using FastAPI
• Build scalable, maintainable, and testable services
• Design database schemas and optimize SQL queries (PostgreSQL)
• Integrate with external services (OpenAI, Anthropic)
• Optimize API performance, latency, and throughput

Quality & Testing

• Write comprehensive unit and integration tests
• Participate in code reviews (give and receive feedback)
• Debug and resolve production issues
• Maintain high code quality standards

Collaboration & Mentorship

• Work closely with Tech Lead on architecture and roadmap
• Partner with AI Platform Engineer on AI integrations
• Mentor mid-level engineers and share knowledge

Required Skills & Experience

Must-Have

• 7+ years of backend development experience
• Deep knowledge in Python, FastAPI
• Strong database skills: PostgreSQL, SQL, ORMs (SQLAlchemy)
• Experience designing REST APIs: best practices, versioning, documentation
• Cloud platform experience: GCP preferred (AWS, Azure acceptable)
• Testing mindset: unit tests, integration tests, TDD
• Version control & CI/CD: Git, GitHub Actions, Docker
• Strong problem-solving skills: debugging, performance optimization
• Fluent in English (Spanish is a plus)

Nice-to-Have

• Experience with FastMCP
• Familiarity with LangChain, Pydantic AI or similar frameworks
• Knowledge of async programming (asyncio, async/await)
• Familiarity with AI/ML APIs (OpenAI, HuggingFace, Vertex AI)
• Understanding of infrastructure as code (Terraform)
• Experience with microservices architecture

Tech Stack

Current Stack:

• Backend: Python, FastAPI, SQLAlchemy, Pydantic AI, Alembic
• Databases: PostgreSQL, Redis (caching)
• APIs: REST, WebSockets, SSE
• AI/ML: OpenAI API, Anthropic, Gemini
• Cloud: Google Cloud Platform (Cloud Run, Cloud SQL, GCS, VPCs, Bucket)
• Infrastructure: Terraform, Docker
• CI/CD: GitHub Actions, Terraform
• Testing: pytest, pytest-asyncio, pytest-cov

D. E. Shaw Research welcomes applications for our summer 2026 internship program from undergraduate and graduate students who are pursuing degrees in scientific and technical disciplines, including machine learning and other areas of computer science, electrical and computer engineering, applied mathematics, physics, chemistry, and chemical or biomolecular engineering. Programming experience in Python or C/C++ is required, and experience with Linux systems, high-performance computing, PyTorch, and/or CUDA would be a plus.

Interns spend 12 to 15 weeks (with flexible start and end dates) working closely with members of our computer science and machine learning team. They are fully immersed in a challenging project involving, for example, applying ML (including large language models) to drug discovery, building and deploying AI-powered systems, developing scientific software, or working on various other engineering and research problems to advance our drug discovery goals. At the end of the summer, interns have the opportunity to give group-wide presentations of their work.

Throughout the summer, interns are invited to attend scientific and technical seminars and workshops, and to join in lively social programming in and around New York City.

For more information, visit www.DEShawResearch.com.

Please apply using the link below:

https://apply.deshawresearch.com/careers/Register?pipelineId=657&source=NeurIPS_1

The expected monthly salary for our internships is USD 11,700 - USD 20,600. The applicable monthly salary paid to a successful applicant will be determined based on multiple factors, including the nature and extent of prior experience and educational background. We also provide our interns with a generous housing allowance.

D. E. Shaw Research, LLC is an equal opportunity employer.