Transformers Jobs

Liquid AI, a rapidly scaling company spun out of MIT CSAIL, is seeking an Applied ML professional to join their team. This role offers a unique opportunity to apply advanced sequential recommendation architectures to real-world enterprise problems at scale. You will be responsible for the end-to-end applied ML work for recommendation system workloads, adapting large-scale models for customers requiring efficient personalization and ranking capabilities under production constraints. This position provides full ownership over model adaptation, evaluation, and deployment, differing from more siloed recommendation roles. You will also contribute to building reusable tooling and workflows to accelerate future projects, making this an ideal role for those passionate about data quality, user behavior modeling, and implementing effective enterprise recommendation systems.

Anduril Expeditionary Systems is developing specialized, high-performance computing centers designed for AI processing at the tactical edge. These are not traditional data centers; they are air-transportable, power-constrained, and hardened systems optimized for AI inference in forward operating bases. We are seeking a Power Systems Architect to design and build these tactical AI/HPC data centers from the ground up. This is a critical, new role where you will define and architect the complete electrical infrastructure, enabling AI processing in austere, contested, and degraded environments. This capability is novel and will be deployed in some of the most challenging locations globally.

$146k - $170k

NVIDIA is seeking New College Graduates to join our GPU compute architecture and performance engineering team. This role focuses on pre-silicon modeling, data-supported architecture exploration, and GPU microarchitecture improvement for generative AI workloads, including LLM inference and agentic AI. You will contribute to improving the efficiency and scalability of these models on NVIDIA platforms, gaining hands-on experience with performance modeling, bottleneck analysis, and system-level analysis. This is an opportunity to shape the performance of next-generation AI models in data center and edge environments by developing system-level modeling and correlation solutions.

$124k - $242k

Nebius is building a full-stack AI cloud platform for the global AI economy, supporting developers and enterprises from data and model training through to production deployment. As a Forward Deployed Engineer, you will work directly with Physical AI customers to understand their workloads and production requirements. Your insights will shape our core infrastructure products and inform future development by connecting needs across Physical AI industries with product decisions. You will also investigate opportunities for new Nebius products by developing hypotheses about unmet needs, examining demand, and building prototypes to test with customers. This hands-on role involves writing code, deploying and benchmarking models, building agents, and troubleshooting infrastructure alongside customer engineers, with close collaboration across customers, NVIDIA, Product, and Engineering.

$180k - $224k

Nebius is building a full-stack AI cloud platform for the global AI economy, supporting developers and enterprises from data and model training through to production deployment. As a Forward Deployed Engineer, you will work alongside Physical AI customers to understand their workloads and production requirements, translating these into actionable insights for our core infrastructure products. You will also investigate and prototype new product opportunities based on unmet customer needs, helping to shape the future of Nebius' offerings. This hands-on role involves writing code, deploying and benchmarking models, building agents, and troubleshooting infrastructure in close collaboration with customers, NVIDIA, Product, and Engineering teams.

We are building AI that changes how people capture, understand, and act on conversations and meetings. As Director of AI Research, you will lead research and development across automatic speech recognition (ASR), speaker identification (SID), large language models (LLMs), and audio language models. Your work will shape our AI capabilities, product direction, and long-term research strategy. This is a hands-on leadership role for someone who combines research depth with experience building and deploying AI systems at scale. You will set technical priorities, guide model and infrastructure decisions, and work directly with the team on challenging research and engineering problems. Partnering closely with Product, Engineering, and Data teams, you will turn research advances into reliable product capabilities. You will also build the team, experimentation practices, and technical foundation needed to move quickly while maintaining high standards for quality and performance.

$244k - $313k

Anthropic

As a TPU Kernel Engineer, you will be responsible for identifying and addressing performance issues across various ML systems, including research, training, and inference. A significant part of this role involves designing and optimizing kernels specifically for the TPU. You will also provide crucial feedback to researchers regarding how model changes affect performance. The ideal candidate will have a proven history of solving large-scale systems problems and demonstrating expertise in low-level optimization.

$280k - $850k

Outset is building AI-powered user interviews, creating digital twins that represent specific real people and respond to research questions as those individuals would. The Digital Twins Team focuses on measuring and improving how faithfully these AI systems reproduce human responses and behavior. As a Research Engineer, you will report to the Head Scientist and be responsible for building and maintaining the systems that enable the team's scientists to conduct their studies correctly, reproducibly, and at scale. Your role involves ensuring experiments execute as designed, results are reproducible, and research code stays aligned with the shipped product, supporting scientists in a computational research setting with hands-on experience in LLM-based systems.

$200k - $240k

Scale AI

Scale's ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs, as well as data quality evaluation. You will work closely across Scale’s ML teams and researchers to build the foundation platform that supports all our ML research and development, enabling the next generation of LLM training, inference, and data curation.

$190k - $237k

Scale AI

Scale's LLM post-training platform team builds an internal distributed framework for large language model training, powering MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs. This platform also serves as the underlying training framework for the data quality evaluation pipeline. You will work closely with Scale’s ML teams and researchers to build the foundation platform which supports all our ML research and development works, enabling next generation LLM training, inference, and data curation.

$290k - $363k

The Radar ML team builds the fraud detection models that protect Stripe's $1.9 trillion payment network from fraud. The team owns over 10 real-time deep learning models that must constantly evolve to stay ahead of fraudsters. Each ML improvement translates directly into dollar impact for Stripe and its users. The team's models also power the Radar product suite that tens of thousands of businesses use to screen payments and manage fraud. In this role, you will own ML work across the full lifecycle: researching new fraud patterns, building and deploying models, and sharing results directly with top Stripe customers. You will have opportunities to optimize Stripe’s most intensive ML models, and opportunities to ship 0-to-1 products from scratch.

The Radar ML team builds the machine learning systems that power Stripe’s Radar fraud and abuse product suite. Our models make real-time decisions across a significant share of internet commerce, helping businesses stop fraud, increase authorization, and grow safely. By turning economy-scale datasets into compelling ML products, the team directly improves customer outcomes and drives meaningful revenue for Stripe. The team is growing and expanding into multiple new areas, building abuse protections across the full customer life-cycle, adaptive and customizable fraud systems for enterprises, and risk intelligence for over 50 global payment methods. You will own ML problems from conception to production, analyzing new fraud and abuse patterns, experimenting with model architectures, designing evaluations, deploying models, and monitoring performance. Your work may include developing transformer architectures for payment data, building graph-powered intelligence, leveraging LLMs to detect emerging attacks, or rapidly prototyping new protections.

Financial Connections is Stripe's open banking platform, enabling businesses to securely access consumer-permissioned financial data. Our platform connects to thousands of financial institutions, powering use cases from account verification to risk assessment to personal financial management. Across the Financial Connections Engineering org, we focus on delivering high-quality, enriched bank data at scale — building the ML systems that transform raw financial data into actionable signals for both internal Stripe teams and external merchants. Our ML work spans transaction categorization, risk scoring, data enrichment, and the development of intelligent systems that improve data quality across our network. We operate at the intersection of fintech infrastructure and applied machine learning, solving problems that directly impact Stripe's ability to serve millions of businesses and consumers.

Plaid is seeking a Staff Machine Learning Engineer to join the Data Foundation & AI team. This team builds the shared ML and AI infrastructure that powers intelligent capabilities across Plaid's product suite, transforming unique financial network data into scalable, general-purpose representations. The role involves working at the intersection of machine learning infrastructure, applied AI, and distributed systems to establish the core AI platform that enables innovation. The Staff ML Engineer will lead the technical strategy and development of Plaid’s foundation models, driving key decisions across pretraining objectives, model architecture, and fine-tuning approaches. This position requires establishing rigorous evaluation frameworks, building scalable pipelines, and partnering with teams across the organization to define product integrations with foundation models. As a senior technical leader, you will mentor engineers, elevate engineering standards, and represent Plaid's AI and machine learning capabilities externally.

$249k - $368k

Ema builds AI Employees for HR, IT, and Finance, automating busy work across the employee experience. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team comprises engineers from premier tech companies and graduates of top universities. We are backed by leading investors and are at the forefront of Agentic AI, shipping real systems that run business processes at scale. We are seeking innovative and passionate Machine Learning Engineers who excel at solving complex problems with large datasets, transforming theoretical concepts into practical, scalable solutions, and pushing the boundaries of Natural Language Processing and Information Retrieval.

$160k - $220k

Etched is building AI systems that accelerate its own development. As a Research Engineer on the RL Frontiers team, you will train proprietary frontier models to automate kernel development, ASIC engineering, production pipelines, and 3-D hardware operating systems. You will use proprietary simulators and environments to create custom data mixes and post-train models to SOTA performance on the company's hardest engineering tasks. The company is focused on inference and bets on transformer architectures, aiming to capture the entire inference market. Etched is a fully in-person team in San Jose, valuing engineering skills and expecting technical staff to contribute to both engineering and research across disciplines.

From $400k

Anthropic

The Interpretability team at Anthropic is dedicated to understanding how modern language models work, believing that a deep, mechanistic understanding is crucial for making advanced AI systems safe and steerable. This role involves building and maintaining the specialized infrastructure that powers interpretability research, akin to performing 'neuroscience' on neural networks. The work spans the entire lifecycle of a production language model, from pretraining and inference to performance optimization, and directly contributes to safety audits on frontier models.

$315k - $560k

Anthropic

The Interpretability team at Anthropic is dedicated to reverse-engineering how trained models work, believing that a mechanistic understanding is crucial for making advanced AI systems safe and steerable. This role focuses on mechanistic interpretability, aiming to discover how neural network parameters map to meaningful algorithms, akin to performing "biology" or "neuroscience" on neural networks. The team has made significant progress in understanding issues like "superposition" and decomposing models into interpretable components, with recent work identifying millions of features in production models and developing methods to understand multi-hop reasoning and planning. This research is foundational for building reliable, interpretable, and steerable AI systems and often involves collaboration with other teams at Anthropic to enhance AI safety.

$350k - $850k

Cresta is seeking a Senior Machine Learning Engineer to join their team and work across several high-impact AI initiatives. The role involves leading and building next-generation agentic AI systems that augment contact center agents in real time, designing evaluation frameworks to improve the reliability and performance of LLM-powered agents, and architecting/scaling LLM and retrieval-augmented generation pipelines. Final team placement will be determined by experience, strengths, and business needs.

$205k - $270k

We are seeking a Lead Engineer, AI Agent Voice Experience to develop the next generation of AI-powered voice systems for contact centers. This role involves working at the intersection of speech, language, and real-time production systems to enhance how AI listens, understands, reasons, empathizes, and responds in live customer conversations. You will be responsible for developing and improving end-to-end machine learning systems for voice experiences, including automatic speech recognition, turn detection, agentic workflows, voice evaluation, text-to-speech, speech-to-speech models, and production optimization. Collaboration with researchers, product managers, designers, and engineers will be key to translating model improvements into measurable business impact. This position is ideal for individuals passionate about both model quality and production realities, focusing on rigorous evaluation, failure analysis, latency and robustness improvements, and shipping reliable, scalable real-time voice systems.

$205k - $270k