Software Engineer Ml Infrastructure Jobs

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. About the Role EnCharge AI is seeking a Senior NPU Architect to join our Architecture Team. In this role, you will collaborate with a team of NPU and system architects, hardware engineers, and software teams to define and optimize key features in our AI accelerator with the cutting-edge in-memory computing technology. You will contribute to designing a holistic AI HW/SW solution that has the best performance and efficiency on the market for the latest AI/ML workloads, such as LLMs, diffusion models, CNNs, and more. Responsibilities Define and develop the spec, architecture, and micro-architecture of key architecture modules (such as the in-memory compute unit, on-chip network, and memory orchestration units) based on the requirements of the workloads and software deployment flow Contribute to the modeling of aforementioned key architecture modules in our C++ simulation framework to ensure a functional implementation of the features Collaborate with the design verification team to deliver a strategy and infrastructure for the testing of the architecture features within said modules Work with the software team and other architects to analyze the performance and efficiency of the architecture modules for key workloads, identify performance bottlenecks, and guide architectural decisions Stay up to date with the latest trends and research in AI workloads, architectures, an

The Opportunity A dobe Brand Intelligence forms the basis of Content Supply Chain, helping enterprises develop, control, and enhance on-brand content at scale . Through the integration of enterprise context, extensive brand knowledge, and AI agents, ABI develops smart workflows that assist global brands in providing flawless and personalized customer experiences across all platforms. We are seeking an exceptionally qualified Principal Scientist to lead the software architecture for ABI. This is an outstanding opportunity for a seasoned software architect to build and scale large, distributed software platforms, transforming AI innovation into production-ready systems. Impact You’ll Make Define the long-term software architecture and technical vision for ABI. Build the foundational platform delivering AI capabilities consistently across Adobe applications, web experiences, and enterprise ecosystems. Drive architectural decisions for backend services, web applications, APIs, and platform infrastructure. Partner with the ML team to operationalize AI models into scalable, secure, enterprise-ready software systems. Direct engineering strategy across multiple teams while offering mentorship to senior engineers and technical leaders. What You’ll Do Define the comprehensive architecture for ABI, including backend services, frontend applications, SDKs, APIs, and integration systems. Architect and build highly scalable distributed systems with high availability, low latency, and operational resilience. Build scalable APIs and platform capabilities that enable seamless connection with Adobe Creative Cloud applications and other third-party platforms. Lead the development of modern web applications and shared frontend frameworks for Adobe Brand Intelligence experiences. Integrate AI capabilities into production through effective orchestration

Technical Lead / Platform Solution Architect Mission Value: Serve as the technical authority across a complex, multi-vendor AI and software platform, helping the government team make sound architecture decisions, resolve cross-platform integration challenges, and establish repeatable patterns that accelerate mission delivery. Role Description Defense Unicorns is seeking a senior Technical Lead / Platform Solution Architect to embed with a government team and serve as the go-to technical subject matter expert across the platform architecture. This individual will connect the mission, engineering, security, data, AI, and vendor perspectives into a coherent technical approach and become a trusted technology advisor to the mission hero. The role is intentionally hands-on and strategic. The Technical Lead will work across Kubernetes/OpenShift, GitLab and CI/CD, AI/agent infrastructure, enterprise data services, cloud infrastructure, security controls, and integration patterns. They will guide technical decisions, challenge assumptions, identify architectural risks early, and help the team move from prototype to operational capability. The ideal candidate can move fluently between executive-level mission conversations and deep technical discussions with engineers and OEM teams. Responsibilities Own the end-to-end technical architecture and serve as the primary technical SME across the platform ecosystem. Become a trusted technology advisor to the mission hero, translating mission objectives into pragmatic technical choices and providing clear recommendations, tradeoffs, and risk assessments. Create and maintain the architectural “big picture” across application, platform, AI, data, networking, security, identity, and integration layers. Lead technical integration across commercial and government technologies, including Kubernetes/OpenShift, GitLab, AI/ML services, enterprise data platforms, and supporting security tooling.Identify architectural dependencies, integration r

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic trains and serves frontier AI models on some of the largest and most diverse accelerator fleets in the world, and the hardware those models run on is one of the most direct levers we have on capability, cost, and reliability. Our Hardware Systems team owns the system-level architecture of that compute — from the package boundary out through boards, racks, interconnect, power, cooling, and the datacenter interface. We're hiring senior hardware systems architects and technical leads who can work broadly across the hardware stack and go deep where it's needed, and who have the judgment to make and own directional calls — what to build, what to buy, what to co-design with a partner. You'll set architecture, write the specs that partners and internal teams build against, and own the validation and qualification strategy that proves the result. The skillsets we need span power, cooling, mechanical, interconnect, signal integrity, data and control plane, system management, reliability and serviceability — applied across networking, compute, storage, and accelerator systems. You'll work closely with our ML performance, infrastructure software, supply chain, and datacenter teams, and directly with hardware vendors and partners across the stack. And because this is Anthropic, you'll have Claude as a genuine collaborator — we expect this team to push on what AI-assisted hardware design and review can look like. Key responsibilities Own system path-finding and architecture for your domain across the breadth of compute Anthropic deploys — from concept and requirements through spec, design review, and deployment — and act a

GAQ127R143 Databricks is building the future of data and AI and world-class engineering requires world-class talent solutions. We are looking for a strategic, technical Compensation Lead to partner directly with our R&D founders, and Engineering VP leadership. In this role, you won't just execute traditional pay practices; you will design first-principles equity and cash strategies to attract, retain, and motivate the sharpest systems, platform, and AI engineers on the planet. Reporting to the Director of Compensation, you will bridge deep quantitative analysis with high-stakes executive advisory, ensuring our compensation philosophy reinforces an owner mindset across our core technology and product teams. The Impact you will have: Scope of the role • R&D Solutioning & Strategic Advisory (40%): Co-create custom incentive models, specialized technical compensation structures, and high-impact retention frameworks tailored specifically to hyper-competitive R&D skill sets. • Lifecycle Compensation Management (30%): Own the end-to-end execution of merit, refresh equity, and promotion cycles across global engineering cohorts, serving as the primary advisor for strategic executive hires and key retention scenarios. Build and leverage automation and AI solutions to efficiently support complex and nuanced cases. • Enterprise Framework Development (30%): Scale Databricks’ global compensation structure, refining market pricing models, pay-for-performance mechanics, and equity strategies. What you'll bring R&D Compensation Mastery • Technical Domain Depth: Deep understanding of the competitive landscape for core engineering, infrastructure, and AI/ML talent—including aggressive startup equity structures, tech-sector refresh strategies, and specialized software compensation models. • First-Principles Thinking: Ability to look beyond standard survey data to build custom, business-aligned compensation solutions from scratch. • Advanced Analytics: Mastery of Exc

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: Design and implement novel research ideas, ship state of the art models to production, and maintain deep connections to academia and the government. We have one of the highest ratio of compute to engineers in the world. We do not delineate strongly between engineering and research. Everyone will contribute to writing production code and conducting research depending on individual interest and organizational needs. We have all the compute, data, and talent available for you to do your best work. Key Responsibilities: Design, build and scale agentic AI systems for serving mission critical use cases. Research, implement, and experiment with ideas on our supercompute and data infrastructure. Learn from and work with the best researchers in the field. Execute across the full AI stack and ship products to serve public interest. Qualifications: Canadian citizenship and eligibility for security clearance ( required for this role ). Extremely strong software engineering skills. Proficiency in Python and related ML frameworks. Experience training, evaluating, and using (as an end-user) LLMs. Experience using large-scale dis

Principal Architect Location: Washington, DC About the Role We are seeking a Principal Architect to drive the design, development, and deployment of our agentic AI products in a fast-paced, collaborative, extremely high-visibility environment. In this role, you will lead a team of 50+ engineers, providing both strategic and technical guidance. You’ll be responsible for high-impact architectural decisions, cross-company collaboration, and executive level engagements. What You’ll Do Team Leadership: Lead and mentor a high-performing engineering team of 80+, fostering a culture of technical excellence and ownership. Technical Direction: Guide your team through complex challenges involving LLMs, AI agents, and large-scale distributed systems. Executive Stakeholder Engagement: Represent Scale AI in high-stakes negotiations and strategic discussions with senior external partners, demonstrating strong technical competence and credibility. Strategic Planning & Communication: Develop and communicate a compelling vision for Scale AI’s technology applied to your program. Provide regular updates to senior leadership and key stakeholders on progress, risks, and opportunities. Culture & Teamwork: Foster a culture of speed, unity of purpose, resilience, and teamwork. Lead through uncertainty with determination and adaptability. What We’re Looking For 10+ years of software engineering experience, including 5+ years in a technical leadership or staff role. Deep understanding of modern AI/ML technologies, including experience working with LLMs and AI agents. Proficient in one or more modern programming languages (Python, JavaScript/TypeScript) Hands-on experience with Kubernetes and cloud infrastructure (AWS, GCP, or Azure). Strong product and business sense, with a track record of aligning engineering efforts with company goals. Ability to operate effectively in ambiguous, fast-changing environments and guide your team to do the same. Experience in execu

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. ABOUT THE TEAM + ROLE We are building an elite team, applying frontier technologies to the world's biggest financial problems. We're looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn't a place for complacency, it's where ambitious people do the best work of their careers. We're a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. The AI Platform & Agentic Apps team builds the agent platform behind every AI agent at Robinhood — today giving a growing number of engineers and employees an AI teammate that ships code, queries data, and runs operational workflows on their behalf. We're building toward the same platform powering the agents millions of customers interact with directly, in real time. These agents don't just answer questions; they're designed to take real action across carefully curated meta harnesses. This is agentic AI at real scale, in a regulated financial environment, and it will change how Robinhood works. We move fast, raise the bar, and care deeply about building things that matter! As Engineering Manager, you will lead the charge in developing critical infrastructure for Agentic applications spanning Robinhood products. You will guide the engineering organization in leveraging Large Language Models (LLMs) to create real, scalable products that act in the world on behalf of Robinhood's customers and employees. This role calls for a visionary leader with a strong software engineering background, a passion for developing platforms, and deep expertise in applied ML at scale. You'll p

About BlockTech BlockTech is a fast-paced algorithmic trading firm trading crypto derivatives and spot across global venues, 24/7, with our own capital. Crypto is one of the few markets where a researcher can still move the edge. The data is abundant, the microstructure is novel, and the loop between an idea and live PnL is short. High-frequency options trading is where we're strongest, and we're widening our scope to include more mid-frequency work. We're looking for a senior Quantitative Researcher with a mid-frequency background to join our Amsterdam trading floor. The role You'll be in charge of developing our mid-frequency capabilities, owning the research agenda end to end, from hypothesis and dataset construction through model training and backtesting to live deployment. You'll sit with traders, researchers, and analysts, and raise the bar for research across the floor. You will: Own price-prediction, signal, execution, and anomaly-detection models across crypto derivatives and spot markets from idea to live PnL Shape our research, backtesting, and trading infrastructure together with engineers, so good ideas reach production quickly and safely Own models in production: monitor live performance, diagnose decay, and iterate on what you ship Set research direction alongside traders, deciding which trades are worth making and why Raise the research bar by mentoring colleagues, reviewing work, and setting standards for rigour What we're looking for 3+ years of quantitative research experience at a hedge fund, trading firm, or similar, with mid-frequency models you've taken live A strong academic foundation in a quantitative discipline (mathematics, physics, statistics, or computer science) Fluency in Python and the modern ML stack (PyTorch and/or TensorFlow, scikit-learn, NumPy, pandas) A deep grasp of overfitting, validation design, and feature engineering. You can explain why a model works, not just that it does Software engineering instincts: you write product

The ML Observability team builds cutting-edge tools to monitor, explain, and improve AI systems in production, particularly those leveraging Large Language Models (LLMs) and generative AI. We provide robust, scalable observability for AI workloads, including drift detection and model evaluation, and behavior tracing, enabling customers to ship AI with confidence. As a Staff Engineer, you’ll lead the development of new features and foundational capabilities within Datadog’s LLM Observability product. You will shape product direction, drive experimentation, and apply your deep understanding of both AI systems and software engineering to solve open-ended problems in the fast-moving AI landscape. Your work will directly impact how our customers monitor, troubleshoot, and optimize LLM-based applications in production. Join us in building the foundational tools that make AI systems observable, understandable, and reliable in the real world. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Drive design and implementation of LLM observability features. Ideate, prototype, and scale new product features to provide insights and drive improvements for generative AI systems Work cross-functionally with other eng teams, product, UX, and applied science to iterate fast and find product-market fit Develop and extend tools for tracing, evaluating, and debugging LLMs Influence architecture decisions and mentor engineers to build resilient, high-performance systems Stay close to customer pain points and use those insights to guide product and engineering priorities Stay current with industry trends and advancements in machine learning and observability, driving innovation within the team Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or r

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. About the role Synthesia Roleplay Sessions is a training tool that lets people practice real conversations with AI avatars. Instead of just watching training videos, learners do interactive roleplay exercises, like practicing a sales pitch or handling a customer complaint with an AI coach. The AI gives instant feedback so people know what they did well and what to improve. Managers can use a dashboard to track which employees have completed their training, see how well they performed, and measure if the training actually improved their skills. The whole platform is built around learning by doing rather than just passive video watching. For your ML engineer role, you'd be building the AI engine that makes the coaching work. That means creating the models that listen to what learners say during roleplay, score their performance, generate helpful feedback in real time, and decide how the AI avatar should respond next based on what the learner does. This is an applied ML position, not a research one . We expect you to have a good understanding of ML but on the other side to be a good product-focused software developer as you will be expected to work on different products. Please bring with you: Ability to apply your

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. Who We Are: Shape the future of Roblox’s virtual economy. The Economy ML team is building the machine learning backbone that powers Roblox’s Marketplace, Developer Monetization, and Payments ecosystems. From intelligent pricing and personalized storefronts to dynamic layout optimization and avatar understanding, we’re reimagining how the Roblox economy drives user engagement, monetization, and creator success at scale. As a Principal Software Engineer (Data Systems) , you will architect, build and deploy high-scale, reliable real-time and batch data systems for personalization, search and recommendation across various product surfaces in Marketplace, Developer Monetization and Payments. You will be involved in key data projects from architecting event taxonomies and logging interfaces to real-time feature serving across multiple search and recommendation surfaces. What You’ll Do Act as data engineering lead for Economy ML, setting standards for batch vs streaming feature pipelines, table design, observability, and documentation used across the Economy group. Work as a hands-on contributor on our data systems to power content recommendation, search and personalization across Economy product

Fanatics Commerce is the global leader in licensed sports merchandise, operating a vertically integrated platform that designs, manufactures, and delivers officially licensed apparel, jerseys, headwear, and collectibles for major leagues, teams, and events worldwide. With more than 900 e-commerce sites and a global omnichannel presence across digital, in-venue, and retail, Fanatics Commerce reaches fans in over 180 countries and powers official fan experiences for many of the world's most iconic sports properties. At Fanatics, we bring our BOLD Leadership Principles to life every day - building championship teams, obsessing over fans, acting with entrepreneurial speed, and delivering with a determined and relentless mindset. About the team The AI/ML Platform pod builds Fanatics' internal AI platform: the paved road for every team building with LLMs, MCPs, and agents. Gateway, agent runtime, registry, retrieval, evaluation, and cost analytics, all running on a petabyte-scale lakehouse with enterprise-grade governance. You'll join a pod that owns this platform end to end. This is a Staff-level role, and a hands-on one. You will choose the architecture, define the standards other teams build to, and stay in the code, shipping the hardest parts yourself. The decisions you make are ones the organization lives with for years. Responsibilities • Own the end-to-end architecture of the AI control plane: gateway, agent runtime, registry, retrieval, evaluation, and cost. Set technical direction, sequence the roadmap, and make the build-versus-buy calls. • Build the enterprise LLM gateway: multi-provider routing, failover, caching, rate limiting, token optimization, and key management, with a path to self-hosted open-weight models where cost, latency, or data residency call for it. • Build the Agent/MCP ecosystem on a managed runtime such as AWS BedrockAgentCore: enterprise systems exposed as governed tools over MCP, a control-plane registry for discovery,

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Mapping team at Lyft is tasked with building a digital representation of the physical world - a map. We collect and serve the freshest and most accurate mapping data possible, along with algorithms, models, platform services, and map-based user experiences that power Lyft’s current and future transportation offerings. Mapping represents a huge opportunity for Lyft’s business, but also a big challenge. We build and scale systems that deal with large data storage, real-time data processing, machine / deep learning pipelines, routing and ETA models, driver and passenger location tracking, and more. We built beautiful and magical user experiences on top of all those services, and compete with companies that have been in the mapping business for decades. To strengthen our efforts, we are hiring a Senior ML Engineer who will work end-to-end on creating and improving new capabilities to detect changes in the environment and reflect them in our Lyft map using a wide variety of input sources from the Lyft fleet. For this we are looking for someone who values software engineering best practices, loves the algorithmic and geospatial side of the challenge and is data-driven from start to end. Our technology stack ranges from basic machine learning models to large language models and running them at scale on millions of images. You will work with incredibly passionate and talented colleagues from machine learning, data science, and engineering on projects that delight our passengers and drivers – powered by an up to date map. Responsibilities: Partner with Engineers, Data Scientists, Product Managers, and Business Partners to apply machine learning for business and user impact Perform data analysis and build proof-of-concept to explore and propose ML solutions to both new and existing proble

About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! In September 2026 we raised a $350 million Series E at a $3.5 billion valuation , and we are scaling our engineering and research teams to meet demand. The role Frontier AI data is expensive to make and hard to measure. Every task we deliver is tested against the strongest models, often through many long-running agent rollouts. Your job is to make that process faster, cheaper, and more rigorous with ML and AI You will be one of the early members of ML & Research Engineering at Snorkel. You will study how frontier-grade data is generated and evaluated, form hypotheses, validate them against real production data, and ship the winners at scale. You will shape the discipline's direction, its standards, and the team that grows around it. What you'll work on Efficient agentic evals. Cut the cost of long-horizon agent evaluation with adaptive sampling, statistically grounded early stopping, model cascades, caching, and cheap-first gating. AI model routing. Route every eval and judge call to the cheapest model that clears the quality bar, with fallback, monitoring, and cost attribution. Fine-tuned small models. Fine-tune and serve open-weight models (LoRA and other parameter-efficient methods) where they match frontier quality, and know when they don't. Predictive difficulty. Build models that estimate how hard a task is for frontier systems before running a single rollout. Measurement for AI data. Build golden datasets, quantify the accuracy and calibratio