Remote Dev Jobs
15 jobs available
MirantisRemote3w ago
Headquarters: Austin, TX, USA Company Description Mirantis is the Kubernetes-native AI infrastructure company, enabling organizations to build and operate scalable, secure, and sovereign infrastructure for modern AI, machine learning, and data-intensive applications. By combining open source innovation with deep expertise in Kubernetes orchestration, Mirantis empowers platform engineering teams to deliver composable, production-ready developer platforms across any environment—on-premises, in the cloud, at the edge, or in sovereign data centers. As enterprises navigate the growing complexity of AI-driven workloads, Mirantis delivers the automation, GPU orchestration, and policy-driven control needed to manage infrastructure with confidence and agility. Committed to open standards and freedom from lock-in, Mirantis ensures that customers retain full control of their infrastructure strategy. https://www.mirantis.com/ Job Description Develop and maintain core positioning, messaging frameworks, and value propositions for Mirantis’ AI infrastructure and cloud-native platform portfolio. Translate highly technical product capabilities — GPU cluster orchestration, multi-cluster Kubernetes management, MLOps pipelines — into audience-specific narratives for practitioners, platform engineers, and C-suite buyers. Own the competitive intelligence function: track competitors including Red Hat OpenShift AI, NVIDIA Base Command, Rancher/SUSE, VMware Tanzu, and emerging AI cloud providers; produce battlecards, comparisons, and win/loss analysis. Produce a steady cadence of high-quality technical content: solution briefs, white papers, blog posts, use case studies, reference architectures, and demo scripts. Partner with solution architects and product managers to develop technical content that educates buyers on AI infrastructure patterns, including LLM inference at scale, GPU scheduling, and developer platform self-service. Support demand generation campaigns with compelling assets a
Tenth Revolution Group · 🇬🇧 London, United KingdomRemote1mo ago
I'm working on an exciting AI engineering project with a leading enterprise focused on deploying agentic GenAI solutions in AWS. Key responsibilities: Deploy and operationalise GenAI solutions in AWS Build highly available SageMaker endpoints with monitoring and alerting Develop Terraform modules for repeatable infrastructure deployments Implement CI/CD and MLOps best practices Produce architecture documentation, configuration guides and operati...
Bridge-it · 🇺🇸 United StatesRemote1mo ago
Are you passionate about DevOps/MLOps and looking to gain hands-on experience building and maintaining cutting-edge infrastructure? Join BridgeItApp.org as a DevOps Engineer Intern and play a key role in developing a revolutionary Generative AI platform that bridges the gap between education and employment. About the Role As a DevOps Engineer Intern , you will be responsible for building and maintaining the DevOps infrastructure, setting up CI/CD pipelines, and ensuring smooth deployment proces…
Insight Global · 🇺🇸 United StatesRemote1mo ago
Job Description Insight Global is seeking a Senior Backend Software Engineer (Infrastructure MLOps) for a leading streaming and media technology client. This engineer will serve as a critical bridge between the Infrastructure and Machine Learning organizations, helping operationalize and scale AI-powered applications that support customer-facing recommendation systems, internal AI assistants, and advanced classification platforms. The ideal candidate brings a strong software engineering foundat…
Auxmoney Gmbh · 🇩🇪 Düsseldorf, GermanyRemote57y ago
Your new team: Do you want to go beyond experimentation and bring machine learning reliably into production, where it creates real business impact? Then our Pricing team is the right place for you. You will work at the intersection of machine learning engineering and pricing, building and operating the systems that power our Dynamic Pricing platform. You will collaborate closely with Data Science, Data Infrastructure, and business stakeholders, and help shape the technical foundation of our pricing capabilities. What you can expect: Production ownership: You take end-to-end ownership of ML models from development and integration to deployment and monitoring in live environments. Reliable deployment: You operationalize machine learning models in a stable and maintainable way, and you proactively address common pitfalls when moving from experimentation to production. Snowflake enablement: You support and implement training workflows in Snowflake-based environments so model development and data platform components work smoothly across the ML lifecycle. Platform engineering: You build and further develop applications and services around our Dynamic Pricing System on Snowflake, enabling ML-driven logic in pricing workflows. Systems thinking: You keep an overview of complex system landscapes, understand dependencies and interfaces, and integrate ML components robustly into existing ecosystems. Cross-functional collaboration: You translate business and analytical requirements into technical solutions and act as a bridge between stakeholders, Data Science, and Data Infrastructure. Working model: You work remotely within Germany or hybrid at our offices in Düsseldorf or Berlin, depending on your preference and team alignment. Your profile MLOps experience: You have strong hands-on experience productionizing machine learning models and operating them reliably in productive systems. Python engineering: You write stable, production-oriented Python code and are confident with so
Actian · Europe - RemoteRemote57y ago
The AI Enablement Team is the catalyst for internal transformation and product acceleration across Actian. In the modern data landscape, AI is not a siloed experimental lab; it is a core capability that must be embedded into our product DNA and our engineering workflows. We are looking for an AI Enablement Lead who will architect, scale, and own our AI enablement strategy end-to-end. You are not a theoretical researcher or a passive prompt engineer; you are a highly practical, technical driver who builds the foundational platforms, tooling, and frameworks that allow other product and engineering teams to deploy AI safely, rapidly, and at scale. You will democratize AI across the organization, establish modern LLMOps/MLOps practices, and directly impact the Actian Data Intelligence Platform by introducing agentic workflows, intelligent data pipelines, and cutting-edge capabilities. Core Responsibilities: Internal AI tooling: Design and maintain the core AI orchestration layers, centralized API gateways, and reusable frameworks (e.g., advanced RAG architectures, agentic frameworks) for company-wide consumption. Product AI Integration: Collaborate directly with core engineering teams to embed production-ready generative AI and machine learning features into the Actian Data Intelligence Platform. LLMOps & Governance Infrastructure: Establish strict guardrails, evaluation frameworks, and monitoring tools to track model performance, bias, data privacy, and security across all AI implementations. Cost & Latency Optimization: Actively monitor and manage cloud and API compute spend (token management, open-source vs. commercial models) and optimize execution latency for production AI features. Cross-Functional Upskilling: Lead workshops, design blueprints, and create documentation to empower non-AI engineering teams to build and maintain their own AI-driven features confidently. Rapid Prototyping (PoC to Production): Drive the engineering execution of high-impact AI proof-of-
Rockstardevelopers GmbH · 🇩🇪 Stuttgart, GermanyRemote57y ago
Du baust produktive KI-Systeme (LLM, RAG, Agenten) für große Kunden im öffentlichen Sektor. Kein Prototyp für die Schublade, sondern Software, die im Regelbetrieb läuft. Wer wir sind Rockstardevelopers, gegründet 2015, Büros in Stuttgart und München. Aus hunderten Projekten für Enterprise- und Mittelstandskunden wissen wir, wie man Software baut, die im Ernstfall trägt. Seit einer Weile verschiebt sich unser Schwerpunkt Richtung KI: LLM-Anwendungen, RAG, Agenten-Systeme, die beim Kunden wirklich produktiv gehen. Genau dafür suchen wir dich. Worum es geht Unsere Kunden sind IT-Dienstleister im öffentlichen Sektor, ein reguliertes Umfeld mit hohen Ansprüchen an Datenschutz und Betriebssicherheit. Dort baust du KI-Lösungen in bestehende Branchenlösungen ein: Dialogsysteme, semantische Suche, RAG-Pipelines, Agenten, alles im echten Produktivbetrieb für viele Nutzer. Projektsprache ist Deutsch. Ein Wort zu Remote, weil es oft die erste Frage ist: Der Alltag läuft remote-first innerhalb der DACH-Region. Ab und zu bist du vor Ort, den Rest der Zeit arbeitest du von dort, wo du gut arbeitest. Aufgaben Produktive Daten- und ML-Pipelines entwickeln Datenaufbereitung und Modelltraining automatisieren Model Serving aufbauen und betreiben, inklusive Monitoring und Alerting ML-Modelle in Fachanwendungen integrieren ML-Modelle überwachen, Model Drift erkennen Technologischen Stack und DevOps-/MLOps-Prozesse weiterentwickeln Qualifikation Das musst du mitbringen Die folgenden sechs Punkte sind harte Voraussetzungen, jeder muss nachweisbar sein. Wenn einer davon fehlt, können wir dich leider nicht ins Rennen schicken. So ehrlich sind wir lieber vorab, als dir Zeit zu stehlen. Mindestens 3 Jahre Erfahrung in CI/CD-Entwicklung Mindestens 3 Jahre Erfahrung in Python-Entwicklung Mindestens 3 Jahre Erfahrung mit Kubernetes und Docker Mindestens 3 Jahre Berufserfahrung als Machine Learning Engineer Mindestens 3 Jahre Projektarbeit in agilen Entwicklerteams Deutsch mindestens auf C1-Niveau
Eraneos · 🇩🇪 Hamburg, GermanyRemote57y ago
What you can expect from us We are a technical, implementation-oriented spin-off of a global management consultancy. Our clients are primarily DAX and Fortune Global 500 companies, which we advise on issues in the areas of analytics, big data and machine learning. Within the group, we take on the development of individual and data-driven solutions in order to transform our clients into AI-powered companies. We offer an international working environment with agile teams and creative startup methods as well as above-average remuneration and numerous additional benefits. With our offices in Hamburg, Munich and Düsseldorf and our hub locations in all other major German cities (Berlin, Frankfurt and Stuttgart), we ensure that all colleagues are integrated into our team of experts across Germany. As an Senior AI Engineer at Eraneos, you’ll combine the worlds of data science, machine learning, software engineering and consulting. Your mission is to develop and operationalize AI models that deliver measurable impact for our clients. You collaborate closely with stakeholders to understand business problems, transform them into data-driven approaches, and translate insights into production-ready end-to-end solutions. You’ll design, implement, and evaluate AI- and ML use cases– from classical ML to cutting-edge LLMs – and ensure their robust deployment and monitoring in real-world environments. Alongside building prototypes, you focus on MLOps practices, software development, and integration, ensuring reproducibility, scalability, and continuous improvement of AI systems. You communicate your results with clarity and confidence to technical and non-technical audiences alike, making complex solutions understandable and actionable. You enjoy thinking beyond the short-term implementation level to create lasting impact for our clients' business. Who you are You have proven experience in data science, statistics, machine learning, software engineering, and / or applied AI projects
Eraneos · 🇩🇪 Hamburg, GermanyRemote57y ago
Das findest Du bei uns Wir sind ein technisches, umsetzungsorientiertes Spin-Off einer global agierenden Managementberatung. Zu unseren Kunden gehören primär DAX und Fortune Global 500 Unternehmen, die wir zu Fragen in den Bereichen Analytics, Big Data und Machine Learning beraten. Wir übernehmen in der Gruppe die Entwicklung von individuellen und datengetriebenen Lösungen, um so unsere Kunden in KI-gestützte Unternehmen zu transformieren. Wir bieten ein internationales Arbeitsumfeld mit agilen Teams und kreativen Startup-Methoden sowie eine überdurchschnittliche Vergütung und zahlreiche Zusatzleistungen. Mit unserem HQ in Hamburg, weiteren Büros in München und Düsseldorf sowie unseren Hub-Standorten in allen weiteren deutschen Großstädten (Köln, Berlin, Frankfurt und Stuttgart) stellen wir sicher, dass alle Kollegen deutschlandweit in unser Expertenteam eingebunden sind. Als Senior AI Engineer bei Eraneos verbindest Du die Bereiche Data Science, Machine Learning, Softwareentwicklung und Beratung. Deine Aufgabe ist es, KI-Modelle zu entwickeln und in Betrieb zu nehmen, die messbare Ergebnisse für unsere Kunden liefern. Du arbeitest eng mit den Stakeholdern zusammen, um geschäftliche Probleme zu verstehen, diese in datengestützte Ansätze umzusetzen und Erkenntnisse in produktionsreife End-to-End-Lösungen zu übertragen. Du entwirfst, implementierst und evaluierst KI- und ML-Anwendungsfälle – von klassischem ML bis hin zu modernsten LLMs – und stellst deren robuste Bereitstellung und Überwachung in realen Umgebungen sicher. Neben der Erstellung von Prototypen konzentrierst Du sich auf MLOps-Praktiken, Softwareentwicklung und Integration, um die Reproduzierbarkeit, Skalierbarkeit und kontinuierliche Verbesserung von KI-Systemen sicherzustellen. Du kommunizierst Deine Ergebnisse klar und selbstbewusst sowohl an ein technisches als auch an ein nicht-technisches Publikum und machen komplexe Lösungen verständlich und umsetzbar. Es macht Dir Spaß, über die kurzfristige Imple
jetbrains · 🇩🇪 Berlin, GermanyRemote57y ago
<p>At JetBrains, code is our passion. Ever since we started, back in 2000, we’ve been striving to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.</p> <p>Today, AI-powered assistance and agents are becoming a core part of how developers work in our IDEs. The ML Workflows Engineering team is dedicated to removing infrastructure challenges, streamlining machine learning operations (MLOps), and enabling teams to focus on the innovative work that matters most – building impactful ML models and intelligent agents. As part of the team, you'll play a key role in designing tools, automation, and pipelines that make machine learning development seamless and intuitive.</p> <p>By integrating cutting-edge MLOps practices and engineering excellence, we aim to maximize productivity and remove the complexity of ML infrastructure so that our teams can push the boundaries of what’s possible in AI.</p> <h1>As part of our team, you will:</h1> <ul> <li>Build tools, automation, and workflows to simplify infrastructure-heavy tasks, empowering AI teams to focus on experimentation and solving core challenges.</li> <li>Develop robust monitoring, logging, and tracing systems to ensure the performance and reproducibility of ML workflows in production.</li> <li>Design, implement, and maintain end-to-end machine learning pipelines to enable the seamless development, training, and deployment of ML models and intelligent agents.</li> <li>Work with large-scale distributed systems, including GPU clusters, to support training, fine-tuning, and evaluation of ML models.</li> <li>Collaborate with product and development teams to transform high-level goals into concrete, scalable, and maintainable systems.</li> <li>Optimize workflows for reproducibility, scalability, and cost-efficiency while keeping ML teams productive and focused on innovation.</li> </ul> <h1>We’ll
jetbrains · 🇩🇪 Berlin, GermanyRemote57y ago
<p>Software engineers and AI agents alike suffer from the same problem: finding that one person or place that will answer their tough, specific question. Many solutions promise to solve this with similarity search in vector databases. Unfortunately, finding the answer is often a puzzle with pieces to be collected across a myriad of contradictory sources and cannot be solved without surgical search and careful reasoning. </p> <p>Spectrum collects data from an organization’s code, docs, and issues, and organizes knowledge in a unified ontology that AI agents can efficiently search through and reason over. We aim to revolutionize the semantic layer space for software-building organizations and move beyond specs that fall out of sync with code, introducing a living spec – one that’s extracted from the whole system and used to keep it aligned. Spectrum is meant to be the single source of truth for all product and architectural knowledge.</p> <p>Spectrum is a resident of JetBrains' startup incubator, with startup speed and autonomy, and backed by 25 years of developer tooling expertise. We are looking for a top-class ML Engineer who will help us shape the future of software development. You will own our AI and ML engineering stack and help define the research agenda for our team. Your technical vision and design decisions will directly shape the product and determine its success.</p> <h1>Your responsibilities will include:</h1> <ul> <li>Designing and building the ML/LLM solution for data ingestion, knowledge extraction, retrieval, and subsequent reasoning.</li> <li>Creating the datasets, metrics, and pipelines that drive measurable improvements across the system.</li> <li>Architecting and improving agents for context retrieval, knowledge extraction, and data alignment, which includes prompt engineering, model selection, and inference optimization.</li> <li>Establishing MLOps practices, including orchestration, observability, and experiment tracking.</li> <li>Collaborating
NebiusRemote57y ago
<div class="content-intro"><p><strong>About Nebius:</strong></p> <p>Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.</p> <p>Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.</p> <p>Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.</p></div><h3><strong>The role</strong></h3> <p>We seek an experienced Specialist Solutions Architect to support AI-focused customers leveraging Nebius services. In this role, you will be a trusted advisor, collaborating with clients to design scalable AI solutions, resolve technical challenges and manage large-scale AI deployments involving hundreds to thousands of GPUs.</p> <p>You’re welcome to work on-site in Amsterdam or remotely from any other EU country.</p> <p><strong>Your responsibilities will include:</strong></p> <ul> <li>Designing customer-centric solutions that maximize business value and align with strategic goals.</li> <li>Building and maintaining long-term relationships to foster trust and ensure customer satisfaction.</li> <li>Delivering technical presentations, producing whitepapers, creating manuals and hosting webinars for audiences with varying technical expertise.</li> <li>Collaborating with engineering and product teams to effectively prioritize and relay customer feedback.</li> </ul> <p><strong>We expect you to have:</strong></p> <ul> <li>3+ years of experience with cloud technologies in MLOps engineering, Machine Learning engineering or s
Clera · remoteRemote57y ago
About the Role This is a founding-team opportunity at a small, fast-moving healthtech AI company building evidence infrastructure for safety-critical medical imaging AI. As a Founding Forward-Deployed ML Engineer , you will sit at the intersection of research, product deployment, and clinical operations — working directly with hospital partners to evaluate and deploy medical imaging AI in real-world clinical settings. You will play a central role in bridging the gap between benchmark performance and clinical reliability, translating AI models into trusted tools for patient care. This is a high-ownership, high-impact role suited to someone who is equally comfortable writing code, navigating clinical environments, and driving cross-functional projects to completion. Work arrangement: Hybrid, on-site in Sunnyvale, CA. Travel to hospital partner sites required as needed. Visa sponsorship: Not available. What You'll Do Build reproducible evaluation pipelines and validation workflows for medical imaging AI in clinical settings. Lead forward-deployed engagements by working on-site with hospital partners to integrate models into clinical workflows. Analyze model generalization, failure modes, and uncertainty to inform clinical reliability assessments. Integrate ML models into clinical imaging systems and radiology pipelines (DICOM/PACS). Translate clinical needs into technical requirements and drive cross-functional projects through to completion. Support regulatory submissions and clinical evaluations (FDA pathways such as 510(k) and De Novo) and maintain related documentation. Ensure data privacy and regulatory compliance (HIPAA) across all ML deployments. Establish and maintain MLOps practices for deployment, monitoring, and ongoing evaluation. What We're Looking For Required (dealbreakers): 2+ years of Machine Learning / Engineering experience. Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field — or equivalent practical experience. Requi
Virtual Solution Ag · in GermanyRemote57y ago
Deine Aufgaben Du gestaltest den Einsatz von Künstlicher Intelligenz in unserem Unternehmen und unseren Softwareprodukten. Gemeinsam mit Product Management, Entwicklung und Fachbereichen identifizierst du Einsatzmöglichkeiten, bewertest Technologien und entwickelst skalierbare KI-Lösungen – von der Idee bis zum produktiven Betrieb. Dabei verantwortest Du die technische KI-Strategie sowie den Aufbau einer zukunftsfähigen AI- und LLM-Plattform. Du entwickelst und verantwortest die technische KI-Strategie sowie eine AI-Referenzarchitektur Du bewertest, wählst aus und integrierst geeignete KI-Technologien, LLMs und AI-Plattformen Du identifizierst und konzipierst KI-Anwendungsfälle und AI-Features für bestehende und neue Softwareprodukte Du baust eine unternehmensweite AI-Plattform auf und entwickelst sie weiter, inklusive RAG-, Agenten- und Workflow-Lösungen Du definierst Standards für Prompt Engineering, Testing , Qualitätssicherung und Governance Du berätst und unterstützt Management, Produktteams und Fachbereiche beim Einsatz von KI Du begleitest Pilotprojekte, Schulungen sowie die Einführung von Best Practices Du berücksichtigst Datenschutz, Sicherheit, Compliance und regulatorische Anforderungen im KI-Einsatz Dein Profil Du hast mehrjährige Erfahrung in der Softwareentwicklung oder Softwarearchitektur sowie fundierte Kenntnisse moderner Softwarearchitekturen und Cloud-Technologien Du verfügst über praktische Erfahrung mit Generative AI, Large Language Models, APIs und Python oder einer vergleichbaren Programmiersprache Du kennst dich mit relevanten KI-Technologien wie OpenAI, Anthropic, Gemini, Open-Source-Modellen, RAG, Vector Databases, AI-Agenten, MCP oder Prompt Engineering aus Du hast idealerweise Erfahrung m it LLM O ps / ML Ops , Evaluierungsframeworks, Fine-Tunin g, Kuberne tes sowie regulatorischen Anforderungen (z. B. EU AI Act, DSGVO) Du behältst Prozesse im Blick, entwickelst sie kontinuierlich weiter und bringst idealerweise Erfahrung mit Enterprise A
virtual7 GmbH · HomeofficeRemote57y ago
Als IT-Dienstleister treiben wir die Digitalisierung des öffentlichen Sektors voran und schaffen echten Mehrwert für Millionen Menschen in Deutschland. Wir können vieles richtig gut, aber eben noch nicht alles. Darum suchen wir immer wieder neue Kolleg:innen, die mit ihren Ideen, ihrem Können und Engagement etwas bewegen wollen. Fühlst du dich angesprochen? Dann gestalte Deine Welt zum Besseren und werde Teil unseres Customer Cluster Environment, Transportation & Energy. DEINE MISSION Als AI Solution Architect (m/w/d) gestaltest du die KI-/ML-Gesamtarchitektur für komplexe Enterprise-Umgebungen auf Azure. Du verbindest fundiertes Know-how in ML-Engineering, RAG-Architekturen und MLOps mit einem starken Verständnis für Governance, Compliance und technische Führung. Damit trägst du dazu bei, KI-Lösungen produktionsreif, skalierbar und regelkonform umzusetzen. Deine Aufgaben: Entwurf und Weiterentwicklung der KI-/ML-Gesamtarchitektur auf Azure als Enterprise-KI-Plattform Technische Leitung von ML-Pipeline-Projekten, insbesondere in den Bereichen Training, Deployment, Monitoring und Drift Detection, sowie Konzeption und Optimierung von RAG-Architekturen, beispielsweise hinsichtlich Chunking, Retrieval, Guardrails und Context Orchestration Definition von MLOps-Strategien einschließlich CI/CD für Modelle, Experiment-Tracking und Model Registry Technische Führung und Koordination eines interdisziplinären Teams aus ML/AI Engineers, LLM Engineers und MLOps Engineers Beratung zu AI Governance, Responsible AI und EU-AI-Act-Compliance sowie Stakeholder-Management durch Architekturpräsentationen gegenüber IT-Leitung und Fachbereichen DAS IST UNS WICHTIG Fundierte Erfahrung mit Azure-basierten KI-/ML-Lösungen, insbesondere mit Azure Machine Learning und Azure OpenAI Service; Kenntnisse weiterer Azure AI Services sind von Vorteil. Darüber hinaus bringst du praktische Erfahrung mit MLOps-Konzepten und entsprechenden Werkzeugen mit, beispielsweise MLflow, Kubeflow oder Azure ML Pipe