Find your next AI Engineering role

Anthropic

Anthropic is dedicated to building AI systems that are safe, reliable, and steerable, aiming to benefit both users and society. This role is central to advancing Reinforcement Learning (RL), the core technology enabling Claude's reasoning, coding, and autonomous capabilities. The RL Scaling team focuses on how RL performance, stability, and learning efficiency evolve with increasing model size, episode length, and compute power. You will be instrumental in developing and scaling next-generation RL algorithms and architectures, from initial research to large-scale deployment, while deeply understanding and addressing the challenges that arise at scale. This position bridges research and engineering, requiring you to build the systems that accelerate iteration and experimentation, and to tackle complex, unsolved problems in Anthropic's largest RL runs.

$500k - $850k

Anthropic

Reinforcement learning is crucial for training AI models to reason, write code, and act autonomously. At scale, this process involves a demanding distributed system where training, sampling, and environment execution run concurrently across a large fleet of accelerators and hosts. This system must continuously exchange data and maintain progress despite hardware failures, shifting loads, and evolving research. The efficiency of this system directly impacts learning outcomes and the speed of research iteration. As a Research Engineer on the Distributed Systems team within RL Engineering, you will focus on the most critical bottlenecks within this system. This could involve areas like scheduling, data movement, sandboxed environment execution, storage, networking, fault tolerance, autoscaling, or observability. The role seeks generalist engineers capable of reasoning from first principles across different system layers and prioritizing impactful problems over familiar ones. The ideal candidate will have experience building and operating large distributed systems, a commitment to detail, and a desire to apply their expertise to a complex, heterogeneous, and rapidly changing workload.

$500k - $850k

Datadog AI Research (DAIR) is seeking a Research Scientist to partner with Research Engineers on fundamental research problems. The role involves translating research advances into products by collaborating with Datadog's product and engineering teams. The team focuses on high-risk, high-reward problems in cloud observability and security, building on existing AI-powered solutions. The research areas include developing multimodal foundation models for understanding distributed systems and training autonomous agents for observability tasks like incident response and code repair.

$320k - $400k

Datadog is seeking a customer-focused, deeply technical Distinguished Architect to join our Product Solutions Architecture team. In this role, you will act as a technical multiplier for leading AI labs and AI-native companies, bridging the gap between their infrastructure aspirations and Datadog’s technology roadmap. You will ensure our platform natively solves the unique observability challenges of training and deploying foundational models at scale. We operate as a hybrid workplace to foster collaboration and creativity while ensuring work-life harmony.

$330k - $440k

Code Intelligence is at the intersection of agentic engineering and product, running agents against real customer source code in production. This role offers the opportunity to lead an AI-native team in a business-critical growth area, providing high visibility and leverage within the fastest-growing segment of the AI agent space. Datadog operates as a hybrid workplace, valuing office culture for collaboration and creativity while ensuring employees can achieve work-life harmony.

$192k - $240k

Datadog is seeking ambitious leaders to drive the growth of its Database Monitoring product, which is expanding beyond traditional monitoring to include self-healing capabilities powered by AI. The role involves building and developing engineering teams, collaborating closely with Product, and launching new features that deliver significant value to developers. This position is ideal for AI-forward leaders with product engineering backgrounds who are passionate about owning business lines and scaling exceptional teams.

$244k - $305k

The Internal Product Analytics (IPA) team serves as the analytics backbone for Datadog's Product organization, providing PMs and leadership with the data, tooling, platform, and analysis necessary for informed decision-making. The team is responsible for recurring analytical tasks and developing AI-first workflows to enhance the speed and consistency of analysis across the organization. As the Manager of IPA, you will lead a team of data analysts, collaborate closely with Product Managers, and partner with platform engineering teams. Your role will involve setting the strategic direction for team analysis, AI-first tooling development, and cross-functional partnerships, focusing on transforming complex data and open questions into clear, actionable insights.

$160k - $200k

Datadog's People Technology team is seeking a People Systems Developer to design and deploy AI-native workflows that will revolutionize how employees are hired, developed, and supported. This is a hands-on role where you will move beyond traditional HRIS configuration to prototype and productionize AI-enabled systems across various HR functions. You will work with high autonomy, collaborate directly with stakeholders, and deliver solutions that significantly enhance the People team's operations. Success in this role involves reducing manual People workflows by at least 20% through AI-enabled automation and intelligent system design.

$156k - $195k

Datadog AI Research (DAIR) is partnering with Carnegie Mellon University to support PhD students working on open research problems grounded by ongoing efforts at Datadog/DAIR. You will frame a problem, run your own experiments, and write up what you find, with compute and data at a scale most academic labs cannot provide. You will collaborate with colleagues working on the same questions. DAIR is an industrial research lab motivated by practical challenges in observability and software operation, focusing on creating specialized foundation models, post-training and evaluating AI agents, and building frontier-scale machine learning systems. Internship projects are shaped with your DAIR mentor and your CMU faculty advisor.

$110k - $140k

The Agentic Interfaces team at Datadog is seeking a Staff Applied Scientist to lead the evaluation strategy for AI agent integrations. This role focuses on defining and building the measurement systems that ensure AI agents interacting with Datadog's observability, security, and software delivery data are continuously improving. You will be responsible for establishing metrics that cover answer quality, tool selection accuracy, retrieval relevance, latency, and cost, and will partner with AI engineers to implement these systems. This is an opportunity to tackle open research questions in agent-data interaction, such as evaluating non-deterministic trajectories, scoring tool selection in large catalogs, and building scalable measurement systems that benefit both first-party and third-party agents.

$276k - $345k

Asana's AI Teammates are autonomous agents designed to integrate into enterprise workflows, proactively driving work forward. The AI Teammates Platform (AITP) team is responsible for the execution engine and platform layer that ensures these agents are effective, reliable, and scalable. This involves building core systems for agentic execution, including model evaluation, rollout strategies, infrastructure for detecting blocked work, quality assurance, tool orchestration, and platform APIs that power AI across Asana's engineering efforts. The team focuses on creating a composable foundation rather than a monolithic feature, enabling AI Teammates to reason, act, and autonomously improve.

$248k - $282k

Anthropic

The Account Abuse team is responsible for ensuring Anthropic's computing capacity is allocated fairly by minimizing resources for bad actors and preventing their return. As a software engineer on this team, you will build the machine learning systems that detect and stop abuse at scale. The ideal candidate can anticipate opponent strategies and responses to countermeasures. This role involves full-stack machine learning engineering across model training, productionization, and evaluation, with opportunities to leverage Claude to accelerate model development and maintenance. The focus is on classical ML applied to structured and behavioral data, emphasizing robust production systems, precise measurement, and safe rollout strategies, as false positives can lead to legitimate customer lockout.

$320k - $485k

Latent is seeking a Machine Learning Engineer, Research, to lead the design and development of innovative modeling approaches that push the boundaries of clinical intelligence. This role involves driving research from initial problem definition to validated outcomes, influencing how models learn from longitudinal patient data. We are looking for senior and staff-level engineers adept at managing critical research challenges from inception to completion, with a focus on problems that directly impact patient well-being.

$225k - $300k

Latent is seeking a Machine Learning Engineer to join their team and build systems that run in real clinical workflows. This role involves owning the design, development, and operation of production-grade ML systems from ambiguous problem definition through to reliable production deployment. The ideal candidate will drive systems end-to-end, setting technical direction and taking ownership of critical systems that directly impact real patient outcomes. This is an opportunity to work on mission-critical problems at the intersection of AI and healthcare within a fast-growing, early-stage company backed by top-tier investors.

$225k - $300k

Thinking Machines is building AI that extends human will and judgment, with a focus on training frontier models and developing tools like Tinker, a fine-tuning API that allows researchers and developers to customize AI models. This role is for an engineer focused on developer experience, who will work hands-on with users of Tinker, turning their challenges into product improvements. You will write and update documentation, add library features, prototype integrations, and ensure users can customize models smoothly. This position acts as a bridge between Tinker users and internal teams, surfacing user patterns to guide product and infrastructure priorities, and sharing learnings through various channels. It's a technical-first role with a significant user-facing component, ideal for someone who enjoys coding and engaging with creative individuals.

$300k - $350k

Salesforce is seeking a Senior AI Engineer to join the Agentforce Operations team, a high-velocity 'startup-within-Salesforce' focused on revolutionizing the public sector supply chain with an AI-powered platform. This role offers the unique opportunity to build a '0 to 1' product in a rapidly growing vertical, working alongside a founding team with deep startup roots but backed by the global scale of Salesforce. You will be instrumental in shaping both the product and the engineering team, partnering with product leaders and sector experts to deliver trusted AI systems for mission-critical public-sector workflows. The role involves building AI features tailored to public-sector customers, designing systems with security, compliance, reliability, and operational constraints at their core, and operating with wide autonomy to raise the bar for technical quality and mentorship.

$149k - $224k

Salesforce is seeking a Senior Member of Technical Staff (SMTS) for their Monitoring Cloud team. This role is focused on owning and operating the systems that ensure Salesforce's reliability across its multi-cloud footprint. You will be responsible for productizing infrastructure to enhance monitoring capabilities and bridge the gap between high-level feature design and deep-system stability. This is an AI-first engineering role, where AI-assisted development tools will be used for various tasks, allowing engineers to focus on architecture, security, and customer outcomes. The position involves working with automation frameworks, securing air-gapped environments, and ensuring the monitoring stack is invisible, resilient, and intelligent.

$149k - $224k

Salesforce is seeking a highly accomplished technologist to join their Forward Deployed Engineering Team as an Expert Agent Builder. This role is at the pinnacle of AI technical expertise, focusing on architecting, designing, and building complex agentic systems to solve challenging customer problems. The successful candidate will translate ambiguous customer needs into concrete, executable AI solutions, driving transformative AI solutions by tackling the technical frontier of intelligent automation. This involves building first-of-their-kind, best-in-class experiences for major brands, including headless agent automations, dynamic AI-driven custom user interfaces, and complex multi-agent solutions. The role demands unparalleled software development mastery, deep software architecture skills, and a relentless focus on implementing engineering best practices to deliver maximum tangible value in dynamic, real-world enterprise environments.

$158k - $288k

NVIDIA Research is seeking a world-class generative AI researcher to join its fundamental generative AI research team. The team focuses on advancing generative AI methods for text, image, video, 3D, and scientific applications, aiming for research that pushes boundaries and has a real-world impact. This role offers the freedom to conduct groundbreaking research within a collaborative team that consistently publishes at top machine learning venues.

$168k - $265k

Artificial intelligence is shifting from passive help to autonomous, always-on workflows. Our mission is to make this change seamless, efficient, and secure for millions globally. We seek a Senior Engineer to lead technical efforts in deploying advanced AI agent frameworks and local runtimes on Windows and NVIDIA GeForce RTX GPUs. You will guide development so open-source AI agents operate locally, safely, and efficiently on consumer PCs. By combining powerful local inference with strong privacy routers and sandboxed execution, you will help develop the foundation of the desktop AI operating system.

$184k - $357k

NVIDIA is seeking a Senior Software Engineer to lead the bring-up, triage, benchmarking, analysis, and optimization of distributed training and inference workloads across NVIDIA GPU platforms at the largest scales. In this role, you will set technical direction for communication libraries, model frameworks, and inference/training stacks to ensure state-of-the-art LLM workloads run efficiently and reliably at scale. You will lead deep performance and reliability investigations on multi-GPU and multi-node deployments, define how new platforms are benchmarked and qualified, and build the resilience and failure-attribution capabilities essential for large clusters. This is a hands-on, senior individual-contributor role for an engineer experienced at the intersection of deep learning systems, GPU performance, distributed computing, and large-scale operations.

$184k - $357k

Joining NVIDIA's DGX Cloud AI Efficiency Team means contributing to the infrastructure that powers our innovative AI research. This team focuses on developing tools for optimizing efficiency and resiliency of AI workloads, including pre-training, post-training, and inference. Our objective is to deliver a stable, scalable environment for AI researchers, providing them with the necessary resources and scale to foster innovation. As a senior DGX Cloud AI Infrastructure software engineer, you will have the opportunity to work on innovative technologies that power the future of AI and data science and be part of a dynamic, diverse, and supportive team that values learning and growth.

$184k - $357k

Joining NVIDIA's DGX Cloud AI Efficiency Team means advancing the performance, efficiency, and resiliency of large-scale AI workloads. You will help AI researchers and platform teams understand end-to-end behavior across GPUs, networking, storage, and software stacks. Your work will shape scalable DGX Cloud systems, turn complex measurements into prioritized engineering decisions, and continuously raise the performance and reliability of AI workloads. Join a technically diverse team of infrastructure experts to unlock more efficient AI at scale.

$224k - $431k

NVIDIA is seeking a dedicated and creative Security Engineer to join our GPU System Software team. In this role, you will be instrumental in developing mitigations, conducting security research, and building advanced security platforms and frameworks to identify vulnerabilities in complex systems software. This is an exceptional opportunity to contribute to the security of foundational technologies in gaming, professional graphics, and cloud computing, as well as AI, data centers, and healthcare. You will be part of an inclusive team focused on maintaining an industry-leading security posture for groundbreaking products.

$152k - $288k

We are seeking a Developer Relations Manager to be the primary liaison between our developers, customers, and the Jetson SW stack. This role involves guiding users through the platform, including BSP, security, OTA, real-time workloads, mixed-criticality systems, AI libraries, and agentic AI. You will work directly with developers and customers to help them build and deploy optimized edge AI and robotics solutions on Jetson. Simultaneously, you will gather their challenges and insights to inform our engineering and product teams, directly shaping the platform's roadmap.

$184k - $357k

Our team builds AI-driven software systems for Circuit Design, combining automation algorithms, deep learning models, and agentic workflows to accelerate end-to-end design automation. We are looking for an Applied Machine Learning Engineer to join our integral team in the Circuit Solutions Group. You will work within a multi-functional team on various projects involving pre-silicon and post-silicon custom circuit design, circuit/layout optimization, and Spice correlation. This role involves researching and implementing frontier solutions in electronic design automation and building innovative agentic AI solutions for VLSI design problems. You will be responsible for analyzing problems and datasets, validating hypotheses, and designing and building models and algorithms to achieve desired quality of results.

$116k - $230k

OpenAI

OpenAI is seeking dedicated, experienced, and curious individuals to join its User Operations team as an AI Support Engineer. This role is crucial in supporting customers' adoption of AI and ensuring an exceptional product experience. You will work directly with customers through support tickets and live calls, troubleshooting high-impact issues and resolving novel, often ambiguous technical problems in a fast-paced environment. Your work will directly support mission-critical systems being built on OpenAI's platform, serving as a critical line of defense for customers operating at massive scale. Beyond resolving technical issues, you will help define world-class support in an AGI-driven future, partnering closely with Engineering, Product, and Operations to improve systems, reduce bugs, and elevate the customer experience by leveraging automation, agents, and AI technology.

About HUD HUD's mission is to build reliable, fair and open infrastructure for AI data. We want data to be valuable for the people who create it and trustworthy for the labs that train on it. Our team is a quickly growing group of researchers, engineers and operators building the economy that shapes what AI will become. Backed by $16M from top VCs and YC (W25), our marketplace and platform are used by startups, Fortune 500 companies and frontier labs. About the role We’re looking for a Research Engineer for our Robotics team to develop the datasets and evals that make robotics data useful for training and evaluating embodied AI systems. You’ll translate open-ended research needs into data specifications, build methods to validate data, and run experiments to understand which data and structures improve model performance. Responsibilities - Research the data needs of robot learning and physical AI systems, and turn them into concrete dataset and evaluation specifications - Define data schemas, annotations, ground truth, and quality standards across robotics data types - Design collection and review protocols that external data providers can execute reliably - Build tools and validation workflows to audit datasets, identify quality issues, and give providers actionable feedback - Run experiments and analyze model behavior to understand how data quality, coverage, and structure affect performance - Work with HUD’s research and engineering teams, and when needed with data vendors and buyers, to improve robotics data offerings Experience You may be a good fit if you have: - Experience in robotics, robot learning, embodied AI, or closely related multimodal research - Proficiency in Python and experience building data processing, analysis, or evaluation tools - Experience turning research questions into dataset specifications, experiments, and measurable quality criteria - Strong understanding of what makes robotics data useful for training or evaluation—and where it can be misleading - Attention to detail and the ability to spot subtle errors, coverage gaps, and failure modes in complex data - Experience building research tools or pipelines without a fully prescribed roadmap Strong candidates may also have: - Worked with robot trajectories, demonstrations, video, sensor data, simulation, or other multimodal robotics datasets - Experience with imitation learning, reinforcement learning, or vision-language-action models - Worked in unstructured problem spaces and take ownership from early research through production deployment - Early-stage startup experience and strong communication skills for collaboration across teams and time zones We prioritize technical aptitude and learning potential over years of experience. Motivated candidates are encouraged to apply even if they don't meet all criteria. Team & company details - Team Size: ~25 people currently, mostly full-time in-person, but some remote. - Our team: Our team includes 4 International Olympiad medalists (IOI, ILO, IPhO), serial AI startup founders, and researchers with publications at ICLR, NeurIPS, etc. - Company stage: We have 8 figures in funding and are scaling profitably and quickly to meet very strong demand. Logistics - Employment: Full-time. - Location: We have offices in San Francisco or Singapore but are open to remote candidates who can work hours that 70-80% overlap with either San Francisco or Singapore time zones. - Visa Sponsorship: We provide support for relocation and visas for strong full-time candidates to the US or Singapore. - Timeline: Applications are rolling. The process is 2 technical interviews and a 2-3 day work trial. What we offer - Competitive compensation - 100% covered top-of-the-line medical, dental, and vision (US and Singapore employees) - Lunch and dinner for in-office employees - Company-wide holiday break (Christmas Eve to New Year’s Day) on top of PTO and paid holidays - Other perks including an Equinox membership, 401k, and commuter benefits (US employees) and a health/wellness stipend (Singapore employees) - Unlimited* access to tokens for ChatGPT, Claude Code, Cursor, etc. *By unlimited, we mean no one on our token usage leaderboard has ever hit a limit. So we have no idea what the limit is. - Two top-floor offices in San Francisco’s Union Square and Singapore’s Raffles Place - Annual travel budget to visit either office Compensation Actual offers are adjusted for experience and location, but our base salary bands are - San Francisco (and other major US cities): $135,000 - $230,000 - Singapore: $100,000 - $175,000 - Rest of world: $100,000 - $175,000 Due to high volume, we may not actively respond to every application, but feel free to contact us at [email protected] or elsewhere if we missed your application!

$100k - $230k

PostEra is seeking a Machine Learning Researcher to spearhead the development of an agentic research vertical. This role involves leveraging agentic systems to automate the creation of mechanistic models for biochemical and physiological processes, and to analyze biological data for target validation. You will collaborate closely with chemists and biologists to guide drug discovery decisions using these models. A key focus will be on developing machine learning methods capable of rapid adaptation to new drug discovery challenges with limited labeled data, particularly in molecular and tabular in-context learning and building foundation models from proprietary multimodal data. You will be responsible for the entire research loop, from defining tasks and constructing datasets to training and scaling models, performing rigorous ablations, and translating successful methods into practical capabilities for PostEra's scientists. While prior drug discovery experience is not mandatory, a strong motivation to learn the domain and collaborate with interdisciplinary scientists is essential.

Haven Safety AI is building an enterprise learning intelligence layer for safety, designed to help high-risk organizations learn faster from incidents and prevent future occurrences. The platform integrates with existing EHS systems to enhance incident investigation, assessment, and learning processes. It leverages current incident evidence, company knowledge, historical cases, and an industry knowledge graph, with specialized AI agents analyzing various data points to produce traceable assessments. This role is a build-and-operate position focused on the AI and LLM engineering layer, connecting the evidence base and knowledge graph to the product experiences used by investigators and safety leaders. The work is technically demanding and operationally critical, serving enterprise customers in regulated, safety-critical industries where precision, traceability, evaluation, and human oversight are paramount.

The AI Platform team is building the shared runtime for all AI agents at MeridianLink, encompassing model gateway, orchestration, memory, and observability. This role focuses on the trust and explainability layer of this runtime, developing tracing, evaluation, and explanation capabilities. These features will enable engineers to understand multi-agent workflows and allow product teams to provide customers with appropriate explanations to build trust in agent outputs. This is a hands-on engineering role where you will write code for tracing agent actions, adopt and extend open-source frameworks for explainability and observability, and build primitives for surfacing explanations to end-users. You will work closely with a Staff engineer team lead and architects who will support your growth in this area.

$104k - $178k

The Core ML team is seeking an engineer to map novel algorithms for efficient large-scale AI training and inference to the Cerebras architecture. This role involves determining when these algorithms outperform competing approaches and how their advantages scale with models, workloads, and hardware. You will combine analytical performance modeling, empirical benchmarking, and hands-on prototyping to characterize the efficiency frontiers of emerging ML algorithms. Your work will span kernel-level and end-to-end performance, influencing research directions, implementation on current systems, and future hardware/software capabilities.

The Core ML team is seeking an engineer to bridge the gap between novel machine learning research and efficient execution on Cerebras systems. You will work across ML frameworks, compilers, runtimes, and low-level kernels to implement new algorithmic capabilities, diagnose performance bottlenecks, and transform research prototypes into robust, high-performance demonstrations. Depending on your background, your work may emphasize runtime capabilities such as token orchestration, scheduling, communication, and distributed execution; low-level kernel development for novel ML operations; or a combination of both. This role is crucial for advancing the capabilities of Cerebras' unique AI chip architecture.

Handshake is seeking a Member of Technical Staff to join their AI Engineering team. This role is crucial for building and improving the data systems that power frontier model training. You will be responsible for enhancing how Handshake generates, processes, and prepares complex and sensitive data, including creating high-quality synthetic data and anonymizing acquired data while preserving its value. You will collaborate with researchers, domain experts, legal teams, and customers to transform data-related challenges into experiments, pipelines, and products, influencing the company's technical direction and culture.

$200k - $350k

Anthropic

Anthropic is building reliable, interpretable, and steerable AI systems to be safe and beneficial for users and society. The Cloud Inference team is responsible for scaling and optimizing Claude to serve massive audiences across AWS, GCP, Azure, and other cloud providers. This involves owning the end-to-end product on each platform, from API integration and intelligent request routing to inference execution, capacity management, and operations. Engineers on this team are highly leveraged, driving multiple revenue streams while optimizing compute resources. The role requires product-minded backend engineers who can navigate platform differences, design cross-provider services and abstractions, and make architectural decisions for reliability and cost-effectiveness at massive scale. The work directly contributes to increasing service scale, accelerating the launch of new models and features, and ensuring LLMs meet rigorous safety, performance, and security standards.

$320k - $485k

Anthropic

The Cloud Inference team is responsible for scaling and optimizing Claude to serve massive audiences of developers and enterprise companies across major cloud platforms like AWS, GCP, and Azure. Within this team, the model & inference launch team focuses on the validation pipeline for inference servers and load balancers. This critical infrastructure work ensures that every inference change, including new model launches and performance improvements, is deployed with correctness, performance, and reliability. The goal is to make validation fast, cost-effective, and trustworthy, directly impacting how quickly advanced models and features reach users on all cloud platforms and how efficiently compute resources are utilized.

$320k - $485k

Mirage is seeking an ML Engineer to push the boundaries of large language models for multimodal creative tasks. You'll develop new approaches for building and extending agentic systems that understand and operate over complex, real-world data, particularly video. This role focuses on advancing agent capabilities, improving reasoning and control, and enabling new forms of interaction between language models and time-based media.

$175k - $300k

Mirage is seeking an ML Engineer to build and scale the systems powering their video generation models. This role sits at the intersection of research and systems engineering, focusing on making advanced models faster, more efficient, and capable of ultra-low latency, real-time generation. You will work on novel modeling approaches, training objectives, scaling strategies, and inference optimization and efficiency to bring cutting-edge models into production.

$175k - $300k

Synthesia is seeking a Senior Engineering Manager to lead the delivery of complex engineering projects focused on driving user acquisition, activation, and revenue growth. This role involves breaking down initiatives into manageable stages, making clear trade-offs between speed, experimentation, and scalability, and partnering closely with product and data teams to maximize business outcomes. The successful candidate will also be responsible for scaling the team by identifying and filling skill gaps, attracting and retaining top talent, and fostering a collaborative, high-velocity team culture. The Agents Platform team specifically is responsible for building a highly reliable platform with consistent uptime, low latency, and extensive support for model and voice types, serving as a repeatable platform layer for other teams to build products upon. This work will be done in close collaboration with R&D and the wider Product organization.

From €180k

Tavus is building the human layer of AI, aiming to make human-AI interaction as natural as face-to-face communication. We pioneer research in multimodal AI for modeling human communication (language, audio, video) and generating audio-visual avatar behavior, powering applications from text-to-video avatars to real-time conversational video. We are a Series B company backed by top investors, seeking individuals who thrive in startup environments, can prioritize independently, and are willing to take calculated risks to help pave the path forward.