Transformers Jobs

SpaceXAI is seeking skilled Electricians to join its internal construction and electrical teams, supporting the rapid build-out of its data centers. This is a traveling role where you will mobilize with project teams to active construction sites, install and commission mission-critical electrical systems, and move with the work as new facilities come online. You will work on high-voltage and medium-voltage power distribution, backup power systems, grounding, lighting, and process power in a fast-paced, high-stakes environment where uptime and safety are paramount. This hands-on position is ideal for experienced electricians who thrive in industrial or data-center settings, enjoy project-based travel, and want to contribute directly to groundbreaking AI infrastructure.

Anthropic

Anthropic is seeking a Performance Engineer for its Inference Engine team. The inference engine is a critical in-house software component that manages the entire token path, from batching requests to coordinating forward passes across accelerator platforms. This role involves building and optimizing this system at scale to enhance throughput, cost-efficiency, reliability, and latency. You will leverage your deep understanding of hardware and bandwidth metrics to model and solve performance bottlenecks. This is a highly technical and impactful position for engineers who thrive on accelerator programming, high-performance host-device coordination, and large-scale distributed systems.

Anthropic

Anthropic's Safeguards team is responsible for developing systems that detect and mitigate misuse of AI models. This role focuses on building and owning the infrastructure that supports the research efforts of this team. You will create the tooling, pipelines, and abstractions that enable researchers to run experiments, train detection methods, and select detections for launch efficiently and reliably. This position bridges the gap between research and production, ensuring fast iteration for researchers and dependable results for detection systems as models evolve. The ideal candidate will have a proven ability to solve large-scale systems and data problems and a strong desire to deepen their machine learning expertise.

Anthropic

Anthropic is seeking ML Engineers and Research Engineers to join the Safeguards ML team. The primary focus of this role is to develop systems that detect and mitigate misuse of AI systems, ranging from individual policy violations to sophisticated coordinated attacks. You will build defenses to ensure product safety as AI capabilities advance, protect user well-being, and guarantee appropriate model behavior across various contexts. This work is crucial for Anthropic's Responsible Scaling Policy commitments.

Anthropic

Anthropic's mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society. 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, and providing feedback to researchers on how model changes affect performance. We are looking for individuals with a strong background in solving large-scale systems problems and performing low-level optimizations.

Anthropic

Anthropic's performance and scaling teams focus on making the most efficient and impactful use of our compute resources for inference and training. As an Engineering Manager on these teams, you will be responsible for identifying and removing bottlenecks, building robust and durable solutions, and maximizing the efficiency of our systems. You will also help bring clarity, focus, and context to your teams in a fast-paced, dynamic environment.

Anthropic

Anthropic's mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society. As a Performance Engineer, you will identify and solve novel systems problems that arise from running machine learning (ML) algorithms at scale. You will develop systems to optimize the throughput and robustness of our largest distributed systems. This role requires a strong track record of solving large-scale systems problems and a desire to become an expert in ML.

Crusoe is seeking a detail-oriented and intellectually curious Senior Strategic Sourcing Data Analyst to be the intelligence engine of their Procurement Shared Services team. This role goes beyond simple reporting to provide actionable insights that drive cost savings, optimize working capital, and improve operational efficiency. The analyst will play a key role in digital transformation, utilizing AI-driven tools and advanced procurement platforms to automate bid analysis and supplier performance tracking. This is a 100% on-site role in Denver, Colorado.

$110k - $120k

Crusoe is seeking a detail-oriented and intellectually curious Strategic Sourcing Data Analyst to be the intelligence engine of their Procurement Shared Services team. This role goes beyond simple reporting to provide actionable insights that drive cost savings, optimize working capital, and improve operational efficiency. You will play a key role in the company's digital transformation, utilizing AI-driven tools and advanced procurement platforms to automate bid analysis and supplier performance tracking. This is a 100% on-site role in Denver, Colorado.

$90k - $105k

Poolside is building a world where AI drives economically valuable work and scientific progress, aiming to accelerate the development of Artificial General Intelligence (AGI). We focus on reshaping the developer experience with agentic systems, coding assistants, and frontier models. This role is an opportunity to build and lead a new team focused on multimodality, specifically teaching our frontier coding model to understand and process image inputs. You will shape this critical capability from its early stages, leveraging our extensive resources including a powerful model factory, thousands of GPUs, and a strong research team. The initial focus will be on image input capabilities, such as interpreting designs, generating and verifying code, and understanding diagrams, with a long-term vision of evolving towards native multimodal understanding.

Fal

fal is building the generative media ecosystem for the next generation of AI products, providing the infrastructure, tools, and model access needed to scale from idea to production. As generative media reshapes industries, fal is becoming the foundation for ambitious teams. This hybrid ML Engineering / Site Reliability Engineering role will own the reliability, security, and safety of fal's generative media model APIs, ensuring they remain available, performant, secure, and safe for thousands of developers and enterprises. You will address model-specific failure modes, such as degraded output quality, drift, unsafe generations, and abuse patterns, as critical reliability concerns alongside uptime and latency.

OpenAI

As a Machine Learning Engineer in OpenAI's Integrity team, you will work with state-of-the-art models and classifiers, experiment with new architectures, and advance our capabilities in content and user understanding. This role offers the chance to transform research breakthroughs into tangible solutions that enhance platform trust and safety, particularly for those excited about training LLMs and building ML models. You will be instrumental in designing and deploying advanced machine learning models to solve real-world problems, bringing AI-driven applications from concept to implementation. Collaboration with researchers, software engineers, and product managers is key to delivering AI-powered solutions for complex business challenges. You will also optimize and scale data pipelines, ensure models are production-ready, and contribute to projects requiring cutting-edge technology. Staying ahead of the curve in machine learning and AI developments, participating in code reviews, and leading by example are essential aspects of this role, as is monitoring and maintaining deployed models to ensure continued value delivery.

Together AI

This research engineering role focuses on translating new Reinforcement Learning (RL) algorithms, scheduling methods, and inference optimizations into production-grade systems that power Together's API. The Core ML team operates at the intersection of efficient inference (algorithms, architectures, engines) and post-training/RL systems, building and maintaining high-performance inference and RL engines at production scale. The goal is to significantly improve model speed, cost-efficiency, and capabilities through RL-based post-training. This position requires a blend of algorithmic understanding and systems engineering, with opportunities to work across the entire stack from RL algorithms and training engines to kernels and serving systems, ultimately driving measurable improvements in latency, throughput, cost, and model quality at scale.

$200k - $280k

Together AI

The Turbo team operates at the intersection of efficient inference (algorithms, architectures, engines) and post-training/RL systems. We are responsible for building and managing the systems that power Together's API, focusing on high-performance inference and RL/post-training engines capable of operating at production scale. Our core mission is to advance the frontiers of efficient inference and RL-driven training, aiming to make models significantly faster and more cost-effective to run, while simultaneously enhancing their capabilities through RL-based post-training methods. This role involves working across the entire stack, from RL algorithms and training engines to kernels and serving systems, to develop and refine state-of-the-art models using RL pipelines. We value individuals with deep expertise in one area and a strong willingness to collaborate and grow across others.

$200k - $280k

Together AI

The Agents team investigates how to build, align, and scale frontier AI systems capable of complex, multi-step tasks and workflows across text and speech, with a focus on agentic and scientific domains. This role sits at the intersection of agent capabilities, human-computer interaction, and infrastructure, exploring areas like post-training methods for agentic behavior and developing evaluation frameworks for open-ended tasks. As a research intern, you will tackle challenges in alignment, reliability, and scalability, potentially working on new training recipes for self-learning and long-horizon reasoning, curating datasets, studying failure modes, or building scalable agent infrastructure.

Google DeepMind

Google DeepMind is seeking a Research Engineer to join their materials science team. This role involves accelerating the discovery of new functional materials by integrating artificial intelligence, computational simulation, and automated experimentation. You will collaborate with a diverse interdisciplinary team of domain experts, ML researchers, and engineers. The work focuses on pioneering research in various scientific domains, enabling the validation of early ideas and building infrastructure for promising research lines. You will contribute your scientific domain knowledge to the team's collective expertise.

$141k - $202k

Scale AI

Scale is seeking a Machine Learning Systems Research Engineer to join their Enterprise ML Research Lab. This role will focus on building algorithms for a next-generation Agent RL training platform, supporting large-scale training, and integrating state-of-the-art technologies to optimize ML systems. You will collaborate with other ML researchers and engineers who apply these algorithms to client use cases, including AI cybersecurity firewalls and healthtech search models. If you are passionate about shaping the future of AI, this is an exciting opportunity to contribute to cutting-edge advancements in enterprise GenAI.

$265k - $331k

Scale AI

Scale's LLM post-training platform team builds our 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, optimizing it to enable next generation LLM training, inference, and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you!

$265k - $331k

Sarvam is building the bedrock of Sovereign AI for India, developing a full-stack AI platform focused on making AI genuinely work for India. This role is for a researcher who will tackle open-ended questions about the architecture, optimization, data composition, and training dynamics of our next generation of foundational models. You will have direct access to large compute resources and a tight feedback loop with engineers, driving research from initial hunches to production-ready decisions. This is a hands-on role requiring independent research design, execution at scale, and the ability to translate findings into concrete proposals for production training runs.

Scale AI

Scale's ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. This 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, optimizing it to enable the next generation of LLM training, inference, and data curation. If you are excited about shaping the future of AI via fundamental innovations, we would love to hear from you!

$190k - $237k