Software Engineer Ml Infrastructure Jobs

Senior AI Engineer Location: London (Hybrid) | Practice Area : Technology & Engineering | Type: Permanent Empower the next frontier of AI with Capco. Shape, build, and deliver future-ready generative systems. The Role We’re looking for a Senior AI Engineer (Senior/Principal Consultant) to join our Technology Delivery team. In this role, you’ll combine deep expertise in AI/ML engineering and software development to design, build, and deploy advanced generative AI and agentic systems for leading financial services clients. You’ll work hands-on across the full AI engineering lifecycle, from architecting intelligent multi-agent systems to deploying scalable production-grade AI applications within enterprise environments. As a senior consultant, you’ll also collaborate closely with multidisciplinary teams and client stakeholders to drive innovation, accelerate adoption, and deliver measurable business impact. What You’ll Do Architect and develop autonomous AI systems leveraging multi-modal large language models across text, image, audio, and video Design and implement agentic workflows using prompt engineering, Retrieval-Augmented Generation (RAG), APIs, and enterprise data integrations Fine-tune, optimize, and deploy large language and multi-modal models with a focus on scalability, reliability, and low-latency performance Build scalable MLOps pipelines and cloud-native AI applications to support secure, production-grade deployments Collaborate with clients and cross-functional teams to shape AI engineering strategy and accelerate GenAI adoption across complex environments What We’re Looking For Bachelor’s degree or higher in Computer Science, Artificial Intelligence, Engineering, or a related STEM discipline Proven hands-on experience deploying LLMs and multi-modal AI models within enterprise or large-scale production environments Strong software engineering expertise in Python, including backend development, API design, and distributed systems Solid understan

About Us Are you ready to build the future of supply chain? At Gather AI, we’re not just creating software; we’re pioneering a new era of warehouse intelligence. We’ve developed a groundbreaking, vision-powered platform that uses autonomous drones and existing equipment to capture real-time data, completely digitizing workflows that have historically been manual and error-prone. This means facilities operate smarter, safer, and more efficiently, ultimately redefining “on-time, in full” delivery. If you’re looking for an opportunity to contribute to truly transformative technology and make a significant impact in a vital industry, Gather AI is the place for you. We’re leading the charge in the rapidly evolving robotics industry, and we invite you to join us in reshaping the global supply chain, one intelligent warehouse at a time. About the Team Our Autonomy team builds the software that makes Gather AI’s MHE Vision and drone products work in live warehouse environments. MHE Vision turns forklifts and other material handling equipment into real-time inventory sensors, using onboard cameras and compute to scan locations and report inventory data as equipment moves through the facility. It’s a technically demanding product line operating at the intersection of embedded systems, computer vision, and large-scale warehouse deployments. About the Role We’re looking for a Staff Autonomy Engineer (MHE Vision) to own the core autonomy software stack for our MHE Vision platform. You’ll lead the design and implementation of the perception, localization, and scanning pipelines that run on vehicle-mounted hardware in production warehouses, and you’ll do it on real systems with real constraints. This is a Staff-level individual contributor role with significant technical ownership. You’ll work directly with hardware, field deployment, and ML teams to build software that performs reliably in environments that are noisy, dynamic, and unforgiving of edge cases. Your work will directl

About Us Are you ready to build the future of supply chain? At Gather AI, we’re not just creating software; we’re pioneering a new era of warehouse intelligence. We’ve developed a groundbreaking, vision-powered platform that uses autonomous drones and existing equipment to capture real-time data, completely digitizing workflows that have historically been manual and error-prone. This means facilities operate smarter, safer, and more efficiently, ultimately redefining “on-time, in full” delivery. If you’re looking for an opportunity to contribute to truly transformative technology and make a significant impact in a vital industry, Gather AI is the place for you. We’re leading the charge in the rapidly evolving robotics industry, and we invite you to join us in reshaping the global supply chain, one intelligent warehouse at a time. About the Team Our Autonomy team builds the software that makes Gather AI’s MHE Vision and drone products work in live warehouse environments. MHE Vision turns forklifts and other material handling equipment into real-time inventory sensors, using onboard cameras and compute to scan locations and report inventory data as equipment moves through the facility. It’s a technically demanding product line operating at the intersection of embedded systems, computer vision, and large-scale warehouse deployments. About the Role We’re looking for a Staff Autonomy Engineer (Drone) to own the core autonomy software stack for our drone platform. You’ll lead the design and implementation of the perception, localization, and scanning pipelines that run on vehicle-mounted hardware in production warehouses, and you’ll do it on real systems with real constraints. This is a Staff-level individual contributor role with significant technical ownership. You’ll work directly with hardware, field deployment, and ML teams to build software that performs reliably in environments that are noisy, dynamic, and unforgiving of edge cases. Your work will directly shape th

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is seeking a talented Physical Design Engineer to implement high-performance blocks for our industry-leading CPU and AI/ML architectures. You'll own the complete implementation flow from synthesis to tapeout, working alongside world-class engineers to push the boundaries of performance, power, and area. If you're passionate about crafting silicon that powers the future of AI computing and thrive on solving complex design challenges, we want you on our team. This role is hybrid , based out of Austin, TX or Santa Clara, CA or Fort Collins, CO . We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A hands-on engineer with deep expertise in SOC/ASIC physical design and a track record of successful tapeouts. Passionate about optimizing PPA through innovative implementation techniques and close RTL collaboration. Strong problem solver who excels at debugging complex issues across design hierarchies. Collaborative team player who thrives in fast-paced, technically challenging environments. Experience in power grid design and EMIR What We Need BS/MS/PhD in EE/ECE/CE/CS with proven experience in synthesis, PnR, and timing closure on tape

Lead AI Engineer (Senior/Principal Consultant) Location: London (Hybrid) | Practice Area : Technology & Engineering | Type: Permanent Empower the next frontier of AI with Capco. Shape, build, and deliver future-ready generative systems. The Role We’re looking for a Lead AI Engineer (Senior/Principal Consultant) to join our Technology Delivery Team. You’ll combine your expertise in AI/ML engineering and software development to build and deploy cutting-edge generative AI and agentic systems across the financial services sector. As a hands-on leader, you’ll architect AI solutions, embed them within enterprise environments, and drive impactful outcomes through advanced engineering, scalable pipelines, and deep cross-functional collaboration. What You’ll Do Architect and develop autonomous AI systems integrating multi-modal LLMs (text, image, audio, video) Design agentic workflows enabling AI agents to interact with data sources and APIs using prompt engineering and RAG Fine-tune, optimize, and deploy large language and multi-modal models with a focus on performance and latency Build scalable MLOps pipelines and full-stack applications to support robust, production-grade AI deployments Guide multidisciplinary teams and clients through strategic decisions in AI engineering and GenAI adoption What We’re Looking For Bachelor’s degree or higher in Computer Science, AI, or related STEM fields Hands-on experience deploying LLMs and multi-modal models at scale Strong engineering background in Python with proven backend and API development skills Solid understanding of scalable MLOps, observability, and cloud-native AI deployment Excellent communication, problem-solving, and project management skills in agile environments Bonus Points For Experience with agentic frameworks (e.g., LangChain, LlamaIndex) Experience in deep learning frameworks and front-end development Familiarity with Langfuse, Langsmith, or other LLM observability tools Understanding of Model Context Protocol

Leidos is looking for our next TS/SCI-cleared Elastic Search Engineer to join a high-energy team building and deploying a cutting-edge technology stack to support our client’s mission to centralize and standardize Tasking, Collection, Processing, Exploitation and Dissemination (TCPED) of Open Source Intelligence (OSINT) across the DoD and IC enterprise. We integrate off the shelf and newly development software to sustain and enhance the TCPED platform. We leverage cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross-domain transfer systems to provide cutting edge data exploitation, enrichment, triage, and analytics capabilities to Defense and Intelligence Community members. DTP advances the state of the art in mission-focused big data analytics tools and micro-service development spanning the breadth of Agile sprints to multiyear research and development cycles. As an Elastic Search Engineer, you’ll be a member of our platform engineering team and help develop, deploy and maintain nosql databases as foundational elements of our microservice eco-system using a Kubernetes as foundational platform. You’ll also support the adoption of GitOps best practices across cross-functional engineering teams. In this fast-paced environment, you’ll collaborate closely with systems engineering, architecture, development, security, operations, and integrations teams. Work is conducted on-site at our client location in Bethesda, MD. Key Responsibilities Include: Deploy, triage, debug, and maintain production class databases like Elasticsearch and Redis Design and support database configuration management strategies across air-gapped network fabrics Partner with Systems Engineers to architect solutions for new capabilities Contribute to operational monitoring capabilities to provide proactive system notifications Contribute technical input to engineering document

NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for more than 25 years. Today, we are tapping into the unlimited potential of AI to define the next era of computing. As an NVIDIAN, you will address challenges spanning architecture, silicon, firmware, software, and production — and excellent judgment matters as much as technical depth! Every major NVIDIA silicon product family—from the chips powering AI and datacentre systems to gaming, professional, embedded, and automotive platforms—passes through our productization work on its way to production. NVIDIA’s Silicon Co-Design Productization team works from pre-silicon strategy and feature development through bring-up, characterization, correlation, and optimization. Our charter spans power & performance modelling, bring up & tuning of low-power features, power & thermal controllers , and system-level optimization that ultimately shape how NVIDIA products are configured, binned, specified, and shipped. What you'll be doing Drive silicon power productization from pre-silicon planning through bring-up and production, including test strategy, feature readiness, characterization, and optimization. Partner with architecture and design teams to identify improvements, validate features, and help translate them into production-ready solutions. Correlate measured silicon behaviour with pre-silicon expectations, investigate gaps, and drive complex issues to root cause. Build power and performance models and characterization methodologies that decide silicon binning, product specifications, productization decisions, and customer guidance. Use AI/ML and data-driven methods to analyse characterization & telemetry data, identify anomalies & trends , and accelerate issue debug across silicon, board, power delivery, firmware,

Production engineering is a field that involves crafting, building, and maintaining large-scale production systems with high efficiency and availability. It encompasses various areas, including software and systems engineering practices, storage, data management, and services. Professionals in the role of Production Engineers hold specialized knowledge and expertise across various domains, including storage architecture, high-performance distributed storage, data management, systems, networking, coding, database management, prioritization, continuous delivery and deployment, along with open-source cloud-enabling technologies such as Kubernetes, containers, and virtualization. Their responsibilities include ensuring storage architectures are reliable, scalable, and efficient. They optimize data placement and access patterns. They manage large-scale distributed storage systems and ensure low-latency data access for HPC and AI/ML workloads. Storage Production Engineers at NVIDIA ensure that our internal and external-facing GPU cloud services meet reliability and uptime goals as promised to the users while enabling developers to make changes to the existing system through careful preparation and planning while keeping an eye on capacity, latency, and performance. This role also requires a mindset focused on automating storage operations, improving data access efficiency, and optimizing storage performance. Much of our software development focuses on optimizing operations through automation, enhancing system responsiveness, and improving the efficiency of storage and production systems. Since Production Engineers are responsible for the big picture of how our systems interface with each other, we use a breadth of tools and approaches to tackle a broad spectrum of challenges. Practices such as proactive storage performance monitoring, automated fault detection and remediation, scalable data redundancy methods, and integration of intelligent

About the Team Our team builds classification and evaluation systems that give post-training and research teams fast, reliable feedback on model behavior. We combine machine learning and production engineering to make these capabilities accurate, efficient, and useful at scale, helping researchers assess changes and improve models and products. We work closely with research teams to develop useful measurements and make them practical to run. Our work spans classifier development, rigorous evaluation, and efficient production inference, with ownership from initial experimentation through deployment and continued improvement. About the Role We’re looking for a machine learning engineer to develop new classification and evaluation capabilities and bring them into production. You’ll help turn open-ended questions about model behavior into well-defined ML problems, build methods that address them, and establish how reliably those methods work. This role combines traditional machine learning, model evaluation, and real-time engineering. You’ll own classifiers throughout their lifecycle, including supervised fine-tuning, distillation, evaluation, deployment, and production inference. You’ll work closely with researchers to identify valuable problems and with software engineers to make promising approaches useful at scale. In this role, you will: Build, deploy, and operate production classification and evaluation systems that provide useful feedback to post-training and research teams. Optimize production inference, including model serving, batching, caching, throughput, latency, compute utilization, and cost. Train and optimize classifiers using supervised fine-tuning and distillation, validating quality and efficiency before deployment. Own the reliability and observability of deployed classifiers, diagnose production issues, and improve their performance over time. Design rigorous evaluations that assess accuracy, calibration, generalization, and potential measurement bi

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. We are looking for experienced EDA/CAD engineer with hands-on AI, ML, or LLM experience who is excited to shape the next generation of AI-assisted workflows for custom memory development. In this role, you will apply your expertise in IC design, layout, verification, simulation, and design automation to identify and deliver high-value solutions that improve engineering productivity, quality, and cycle time. This position offers the opportunity to build on a strong CAD foundation while growing into a broader AI-focused role over time. Responsibilities Design, develop, and deploy software, automation, and AI-assisted solutions that improve IC design workflows across layout, verification, simulation, and tape-out activities Develop and enhance AI-assisted tools, agents, and automation that improve engineering productivity and design team efficiency Collaborate with worldwide design, layout, verification, and CAD teams to identify high-impact use cases for automation and AI enablement Build and maintain CAD tools, workflow integrations, and supporting technical content for design teams Support evaluation, qualification, deployment, and integration of EDA tools and AI-enhanced workflows Explore and apply generative AI and machine learning techniques to practical custom IC design and design enablement challenges Contribute to scalable software development practices, including code quality, testing, maintainability, and documentation Required Qualific

We are hiring a Senior Machine Learning Engineer to contribute to cutting-edge Research & Development. As innovators in speech technology, our mission is to Understand Every Voice - a vision that has propelled us to be world leaders of Voice AI. Fuelled by innovation, inclusivity, and a passion for making a global impact through world-leading Speech AI, we're looking for an experienced Senior Machine Learning Engineer to accelerate our efforts towards exceptional speech solutions. Our Modelling Team trains diverse models, including large self-supervised ones, supporting Speechmatics towards being the most accurate speech recognition system globally. It also ensures their deployment into production, working with the latest developments in ML, but also with the best engineering practices for software engineering and model serving. What you’ll be doing: Work on complex R&D projects, with a diverse group of engineers, to achieve ambitious goals. Stay current with the latest developments in Machine learning. Execute high-impact projects to ensure team success. Work collaboratively across departments and mentor team members (where appropriate). Who we are looking for: Demonstrated experience in collaboratively pursuing ambitious R&D agendas. Precise attention to detail, but is also aware of how the big picture relates to company goals, and where the field of Machine Learning is headed towards. Understanding of the modern Machine Learning stack, for example: - Knowledge of contemporary transformer architectures (e.g., GQA, KV-caching) and best practices. - Experience in distributed training techniques. - Familiarity with optimisation strategies for model inference (e.g., dynamic batching, flash attention, speculative decoding). With preferred backgrounds covering some of the following: - Publications in top-tier conferences. - Contributions to popular open-source repositories. - Technical writing skills as evidenced by relevant publications or blogs. We en

We are hiring a Senior Machine Learning Engineer to contribute to cutting-edge Research & Development. As innovators in speech technology, our mission is to Understand Every Voice - a vision that has propelled us to be world leaders of Voice AI. Fuelled by innovation, inclusivity, and a passion for making a global impact through world-leading Speech AI, we're looking for an experienced Senior Machine Learning Engineer to accelerate our efforts towards exceptional speech solutions. Our Modelling Team trains diverse models, including large self-supervised ones, supporting Speechmatics towards being the most accurate speech recognition system globally. It also ensures their deployment into production, working with the latest developments in ML, but also with the best engineering practices for software engineering and model serving. What you’ll be doing: Work on complex R&D projects, with a diverse group of engineers, to achieve ambitious goals. Stay current with the latest developments in Machine learning. Execute high-impact projects to ensure team success. Work collaboratively across departments and mentor team members (where appropriate). Who we are looking for: Demonstrated experience in collaboratively pursuing ambitious R&D agendas. Precise attention to detail, but is also aware of how the big picture relates to company goals, and where the field of Machine Learning is headed towards. Understanding of the modern Machine Learning stack, for example: - Knowledge of contemporary transformer architectures (e.g., GQA, KV-caching) and best practices. - Experience in distributed training techniques. - Familiarity with optimisation strategies for model inference (e.g., dynamic batching, flash attention, speculative decoding). With preferred backgrounds covering some of the following: - Publications in top-tier conferences. - Contributions to popular open-source repositories. - Technical writing skills as evidenced by relevant publications or blogs. We en

CSQ427R248 As a Forward Deployed Engineer (FDE), you will embed directly with our most strategic customers to design and deliver custom fullstack applications and solutions on the Databricks Data Intelligence Platform and other common software stacks. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. This is a hands-on, customer-facing role for software engineers, developers, and builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for solving complex problems that drive measurable outcomes. The impact you will have: Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices. Application Engineering: Design and develop applications spanning backend, frontend, and integrations, bringing data and AI to life for enterprise users leveraging the Databricks platform. Solution Delivery: Deliver production-grade systems from data ingestion and transformation through ML/AI model integration to user-facing applications and enablement. Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact. Cross-Functional Collaboration: Partner with Sales, Product, and Field Engineering to ensure a seamless customer journey from pre-sales through post-deployment. Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap. What we look for: Engineering Depth: Strong background in software engineering with experience across backend, frontend, and systems integration. Proficiency in Python, SQL, Java/Scala, JavaScript/TypeScript, and modern frameworks. Application D

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We’re looking for a Field Application Engineer who’s wired for AI/ML, fluent in real-world problem-solving, and excited to build with the people actually using what we make. You will collaborate closely with the sales team and enterprise customers, leveraging your deep technical knowledge in AI to drive the adoption of our products and solutions. This is a customer-facing role that requires both technical expertise and excellent communication skills to convey complex technical concepts to non-technical stakeholders. This role is remote based out of North America with preference near one of our main hubs Santa Clara, CA; Boston, MA; or Toronto,ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are You’ve lived in the AI/ML trenches, whether as a field engineer, a solutions architect, or the one tapped in when things needed to “just work.” You speak both machine and human. Whether it’s a researcher or a skeptical executive, you know how to break things down and bring them to life. You’re fired up about generative models, LLMs, and the edge of what’s possible when software meets purpose-built silicon. Work directly with customers in mee

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . This is a 12-week internship during summer 2027. You'll join Coinbase's Machine Learning team and work alongside senior engineers building ML models and pipelines that make our platform more secure, personalize user experiences, and unlock new use cases for crypto. As an MLE intern, you'll take ownership of a research-to-production project, applying cutting-edge ML techniques to real-world problems at blockchain scale. What you'll do: Develop, deploy, and operate machine learning models and pipelines at production scale Drive an end-to-end research project applying modern ML techniques to solve a defined business problem Partner with senior engineers and product teams to identify new ML applications for blockchain and crypto use cases Present findings and recommendations to cross-functional stakeholders at the conclusion of your internship Required Skills and Experience: Currently pursuing a Ph.D. with published or in-progress research in machine learning, deep learning, or a closely related field Demonstrated proficiency building and training models using ML frameworks such as PyTorch or TensorFlow Experience applying ML techniques including supervised learning, unsupervised learning, or reinforcement learning to structured or unstructured datasets Familiarity with software engineering fundamentals including version control, testing, and writing production-qua