(junior) fullstack engineer (m/f/d) for a new product

ai engineer (m/f/d)

site reliability engineer

ai & analytics engineer

ai enablement engineer

ai engineer

ai infrastructure engineer

Cortea

<div>
 
 About Us
 
 
 
 We&rsquo;re
 
 Cortea
 
 , a Berlin startup
 
 transforming audits with AI
 
 . Manual, document-heavy audits waste expert time while demand keeps rising. Our
 
 AI-powered software and specialized AI agents
 
 remove the repetitive work so auditors can focus on judgment.
 
 
 Backed by top-tier VCs with &gt;15m funding, with a working product and paying customers, we&rsquo;re rapidly scaling.
 
 
 We value
 
 first-principles thinking, speed, trust, and kindness
 
 . We build side by side
 
 in our Berlin office
 
 .
 
 
 
 Your Role
 
 
 
 We are looking for an
 
 Engineer with strong data engineering and AI systems experience
 
 to build the data, evaluation, and observability foundation for production-grade LLM agents used in complex audit workflows.
 
 
 This role sits at the intersection of
 
 backend engineering, data engineering, AI infrastructure, and LLM operations
 
 . You will work hands-on in our backend and agent architecture, building the systems that help us evaluate, monitor, debug, optimize, and continuously improve AI agents in production.
 
 
 This is
 
 not
 
 a traditional analytics, BI, or dashboarding role. You should expect to write production code, design infrastructure, work inside backend systems, and directly improve the quality, cost, reliability, and performance of LLM-based agents.
 
 
 
 What You&rsquo;ll Do
 
 
 
 You will help building and operating the technical infrastructure around our AI agents, with a focus on data infrastructure, evaluation, observability, and optimization. Your work will include:
 
 
 <ul>
 <li>
 Building online and offline evaluation systems for LLM agents, including pipelines that use golden datasets, ground-truth data, human review workflows, and experiment results.
 </li>
 <li>
 Creating automated quality gates so changes to prompts, context, models, or agent logic can be tested before reaching production.
 </li>
 <li>
 Analyzing large volumes of agent traces and executions to identify failure modes, quality regressions, latency issues, reliability gaps, and cost optimization opportunities.
 </li>
 <li>
 Working with columnar data stores and analytical databases such as BigQuery, ClickHouse, or similar technologies.
 </li>
 <li>
 Building reliable data retention and replay mechanisms for long-term analysis of production agent behaviour.
 </li>
 <li>
 Creating observability tooling for trace analysis, experiment monitoring, production dashboards, logging, tracing, and debugging.
 </li>
 <li>
 Working inside our core backend and agent architecture, including building new agents or improving existing agents when needed.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 You will fit into this role if you:
 
 
 <ul>
 <li>
 Have strong Python and/or backend engineering experience.
 </li>
 <li>
 Have strong SQL skills and are comfortable working with large datasets.
 </li>
 <li>
 Have deployed and operated systems in the cloud, ideally on GCP.
 </li>
 <li>
 Have practical experience designing data pipelines, ETL/ELT workflows, event-processing systems, or feedback loops for production data.
 </li>
 <li>
 Are comfortable working with analytical databases, data warehouses, columnar stores, and high-volume event or trace data.
 </li>
 <li>
 Understand system design, reliability, observability, monitoring, logging, debugging, and operational trade-offs.
 </li>
 <li>
 Can work in complex existing systems and quickly build a mental model of how they operate.
 </li>
 <li>
 Bring senior-level engineering judgment: you can make architectural decisions, communicate trade-offs, and build systems that other engineers can extend.
 </li>
 <li>
 Are comfortable with ambiguity, able to reason from first principles, and excited to build infrastructure for AI systems that are actively used in production.
 
 
 </li>
 </ul>
 Nice-to-haves that are a plus:
 
 
 <ul>
 <li>
 Building infrastructure around LLM-based products or agentic systems, including optimizing LLM usage, context windows, reasoning tokens, or model selection.
 </li>
 <li>
 Working with production traces from complex distributed systems.
 </li>
 <li>
 Building internal platforms for engineers, domain experts, or operations teams.
 </li>
 <li>
 Using workflow orchestration systems such as Temporal or similar.
 </li>
 <li>
 Familiarity with audit, finance, compliance, or other high-accuracy domains.
 </li>
 <li>
 Experience in an early-stage startup or fast-moving engineering environment.
 
 
 </li>
 </ul>
 
 No one checks every box. If you&rsquo;ve shipped retrieval systems and like owning evaluations and pipelines, let&rsquo;s talk.
 
 
 
 
 What we offer
 
 
 
 <ul>
 <li>
 High impact &amp; growth: Shape strategy at a scaling AI startup from day one
 </li>
 <li>
 Mission-driven culture: Ambitious team valuing first-principles thinking and bold ideas
 </li>
 <li>
 Attractive compensation: competitive salary plus significant equity
 </li>
 <li>
 Personal development: Learning budget for courses and conferences
 </li>
 <li>
 Startup perks: Flexible vacation, team lunches, retreats, central Berlin office
 
 
 </li>
 </ul>
 
 Interview process
 
 
 
 <ul>
 <li>
 First Call &mdash; Intro to Cortea with our Talent Partner Adriana
 </li>
 <li>
 Second Call &mdash; Technical interview with Jendrik
 </li>
 <li>
 Third Call &mdash; Deep dive into our culture with our Co-Founder Philipp
 </li>
 <li>
 On-site Day (Berlin) &mdash; Meet the team and work on a real problem together
 
 
 </li>
 </ul>
 
 We&rsquo;re an equal-opportunity team and encourage women and underrepresented groups to apply.
 
 
 
</div>

Software Engineer, Data & AI Platform (m/f/x)

Cortea AI

<div><h1 class="jobSectionHeader">About us</h1>
We&rsquo;re Cortea, a Berlin startup transforming audits with AI. Manual, document-heavy audits waste expert time while demand keeps rising. Our AI-powered software and specialized AI agents remove the repetitive work so auditors can focus on judgment.
Backed by top-tier VCs with &gt;15m funding, with a working product and paying customers, we&rsquo;re rapidly scaling.
We value first-principles thinking, speed, trust, and kindness. We build side by side in our Berlin office.<h1 class="jobSectionHeader">
Your Role</h1>
We are looking for an Engineer with strong data engineering and AI systems experience to build the data, evaluation, and observability foundation for production-grade LLM agents used in complex audit workflows.
This role sits at the intersection of backend engineering, data engineering, AI infrastructure, and LLM operations. You will work hands-on in our backend and agent architecture, building the systems that help us evaluate, monitor, debug, optimize, and continuously improve AI agents in production.
This is not a traditional analytics, BI, or dashboarding role. You should expect to write production code, design infrastructure, work inside backend systems, and directly improve the quality, cost, reliability, and performance of LLM-based agents.<h1 class="jobSectionHeader">
What you&rsquo;ll do</h1>
You will help building and operating the technical infrastructure around our AI agents, with a focus on data infrastructure, evaluation, observability, and optimization. Your work will include:<ul><li>
Building online and offline evaluation systems for LLM agents, including pipelines that use golden datasets, ground-truth data, human review workflows, and experiment results.</li><li>
Creating automated quality gates so changes to prompts, context, models, or agent logic can be tested before reaching production.</li><li>
Analyzing large volumes of agent traces and executions to identify failure modes, quality regressions, latency issues, reliability gaps, and cost optimization opportunities.</li><li>
Working with columnar data stores and analytical databases such as BigQuery, ClickHouse, or similar technologies.</li><li>
Building reliable data retention and replay mechanisms for long-term analysis of production agent behaviour.</li><li>
Creating observability tooling for trace analysis, experiment monitoring, production dashboards, logging, tracing, and debugging.</li><li>
Working inside our core backend and agent architecture, including building new agents or improving existing agents when needed.</li></ul><h1 class="jobSectionHeader">
Qualifications</h1>
You will fit into this role if you:<ul><li>
Have strong Python and/or backend engineering experience.</li><li>
Have strong SQL skills and are comfortable working with large datasets.</li><li>
Have deployed and operated systems in the cloud, ideally on GCP.</li><li>
Have practical experience designing data pipelines, ETL/ELT workflows, event-processing systems, or feedback loops for production data.</li><li>
Are comfortable working with analytical databases, data warehouses, columnar stores, and high-volume event or trace data.</li><li>
Understand system design, reliability, observability, monitoring, logging, debugging, and operational trade-offs.</li><li>
Can work in complex existing systems and quickly build a mental model of how they operate.</li><li>
Bring senior-level engineering judgment: you can make architectural decisions, communicate trade-offs, and build systems that other engineers can extend.</li><li>
Are comfortable with ambiguity, able to reason from first principles, and excited to build infrastructure for AI systems that are actively used in production.</li></ul>
Nice-to-haves that are a plus:<ul><li>
Building infrastructure around LLM-based products or agentic systems, including optimizing LLM usage, context windows, reasoning tokens, or model selection.</li><li>
Working with production traces from complex distributed systems.</li><li>
Building internal platforms for engineers, domain experts, or operations teams.</li><li>
Using workflow orchestration systems such as Temporal or similar.</li><li>
Familiarity with audit, finance, compliance, or other high-accuracy domains.</li><li>
Experience in an early-stage startup or fast-moving engineering environment.</li></ul>
No one checks every box. If you&rsquo;ve shipped retrieval systems and like owning evaluations and pipelines, let&rsquo;s talk.<h1 class="jobSectionHeader">
What we offer</h1><ul><li>
High impact &amp; growth: Shape strategy at a scaling AI startup from day one</li><li>
Mission-driven culture: Ambitious team valuing first-principles thinking and bold ideas</li><li>
Attractive compensation: competitive salary plus significant equity</li><li>
Personal development: Learning budget for courses and conferences</li><li>
Startup perks: Flexible vacation, team lunches, retreats, central Berlin office</li></ul><h1 class="jobSectionHeader">
Interview process</h1><ul><li>
First Call &mdash; Intro to Cortea with our Talent Partner Adriana</li><li>
Second Call &mdash; Technical interview with Jendrik</li><li>
Third Call &mdash; Deep dive into our culture with our Co-Founder Philipp</li><li>
On-site Day (Berlin) &mdash; Meet the team and work on a real problem together</li></ul>
We&rsquo;re an equal-opportunity team and encourage women and underrepresented groups to apply.</div><div></div>

voize

<div>
 🎤 Why voize? Because we&rsquo;re more than just a job!
 
 
 At voize,
 
 we believe the greatest gift to frontline workers is time - time to care, connect, and be present.
 
 Today, that time is lost to
 
 busywork and complex systems
 
 that pull them away from what matters most:
 
 people
 
 .
 
 
 
 Our vision is to change that by building AI companions
 
 that seamlessly take over digital workflows. We don't replace humans with technology -
 
 we amplify their impact.
 
 
 
 Our mission is backed with a
 
 $50M Series A funding led by Balderton Capital, with support from HV Capital, Y Combinator and other leading VCs. Today, 2,000+ facilities trust voize, and over 200,000 users rely on our AI companion
 
 to ease their daily workload.
 
 
 As a dynamic team, we combine first-in-class technology with meaningful social impact.
 
 And now, we&rsquo;re looking for you to join us on this mission!
 
 
 
 💡 Your Mission: Transform voize into an AI-native organisation
 
 
 As our
 
 AI Enablement Engineer
 
 , you will define, operationalise, and scale how artificial intelligence is adopted. You build the infrastructure, guardrails, and enablement systems that help every team at voize adopt AI in a way that is
 
 safe, reliable, and actually improves work loops
 
 . You&rsquo;ll turn scattered individual hacks into repeatable practices. Your core mission is to transform voize into an AI-first company and enable everyone to become truly AI-native.
 
 
 🚀 Your Daily Business - No two days are alike
 
 
 If you're energised by being a first-of-its-kind hire and enjoy turning experimentation into durable operating systems, this role is for you.
 
 
 <ul>
 <li>
 Build the AI infrastructure: Design and maintain voize's internal AI productivity suite, connecting agents, data, and workflows to enable cross-functional automation and decision-making
 </li>
 <li>
 Enable and educate: Build AI fluency across the organisation through onboarding sessions, workshops, playbooks, and function-specific best practices
 </li>
 <li>
 Set guardrails: Establish and enforce standards for AI governance, safe use, data handling, and compliance in partnership with Security and IT
 </li>
 <li>
 Consult &amp; ship with teams: Partner with teams and leadership to embed AI into workflows, build agents and automations, and translate business needs into prioritised AI initiatives
 </li>
 <li>
 Drive change: Help people and management completely rethink how companies are run &mdash; managing the transition towards an organisation where humans and AI agents work side by side
 </li>
 <li>
 Turn usage into learning: Analyze tool usage and adoption signals, spot fatigue patterns, and iterate on what actually changes outcomes.
 </li>
 <li>
 Build the context layer: Help create and maintain an LM-readable context layer with a sensible update process so agents and humans operate on shared truth.
 
 
 </li>
 </ul>
 🤝 Your Skillset - What you bring to the table
 
 
 <ul>
 <li>
 5+ years of experience in a fast-paced tech or SaaS environment, with hands-on ownership of cross-functional initiatives including AI or advanced technology adoption
 </li>
 <li>
 Strong technical fluency in LLM-based systems (prompts, agents, retrieval patterns, embeddings, APIs) and experience designing and integrating AI workflows across tools and data platforms
 </li>
 <li>
 Engineer mindset - you can build, debug, and ship (not only strategy) along side of tech &amp; non-technical teams.
 </li>
 <li>
 Proven enablement track record - you've trained and enabled non-technical teams and driven adoption at scale, developing playbooks, learning content, and feedback loops
 </li>
 <li>
 Entrepreneurial and process-oriented mindset with strong communication skills, sound judgement, and comfort operating in ambiguity
 </li>
 <li>
 English required; some level of German is a strong plus.
 </li>
 <li>
 Location: Berlin required. (We&rsquo;re open to candidates that want to relocate)
 
 
 </li>
 </ul>
 🌱 Growing together - what you can expect at voize
 
 
 <ul>
 <li>
 We are a fast-growing startup, that means you will tackle challenges, grow quickly, and make a real impact, giving frontline workers more time for people
 </li>
 <li>
 We foster an open, collaborative culture with regular team events, whether you work from our Berlin office or work from home.
 </li>
 <li>
 Become a co-creator of our success with stock options
 </li>
 <li>
 Generous perks: 30 vacation days plus your birthday off, Germany Transport Ticket, Urban Sports Club, regular company off-sites, and access to learning platforms such as Blinkist and Audible, plus free language courses
 </li>
 <li>
 You decide when you work best, that means flexible working hours and a good hybrid set-up.
 
 
 </li>
 </ul>
 ✨
 
 Ready to talk?
 
 Apply now! 🚀
 
 
 We look forward to your application and can't wait to meet you - no matter who you are or what background you have!
</div>

AI Enablement Engineer (m/f/d)

Capgemini

<div><div><div><div>Wenn du dich f&uuml;r Capgemini entscheidest, w&auml;hlst du ein Unternehmen, in dem du die M&ouml;glichkeit hast, deinen Karriereweg selbst zu gestalten. Du wirst von einem kollaborativen Netzwerk von Kolleg*innen auf der ganzen Welt unterst&uuml;tzt und inspiriert und kannst neu definieren, was m&ouml;glich ist. Schlie&szlig;e dich uns an und unterst&uuml;tze die f&uuml;hrenden Organisationen der Welt, den Wert von Technologie zu erschlie&szlig;en und eine nachhaltigere, inklusivere Welt zu gestalten.
<div><div><div><h2 class="jobSectionHeader">Deine Rolle</h2>
</div><div>Souver&auml;ne KI‑Plattformen sind die Grundlage f&uuml;r sichere und leistungsf&auml;hige KI‑Anwendungen. Als AI Platform Engineer (w/m/d) gestaltest du die technische Basis f&uuml;r LLM‑Inferenz, Daten‑/Vector‑Stores und moderne AI‑Workloads &ndash; automatisiert, skalierbar und compliant. Diese Stelle ist in Vollzeit sowie in Teilzeit zu besetzen.
<ul><li>Du konzipierst, automatisierst und betreibst KI‑Plattformen mit Kubernetes, IaC und GitOps &ndash; von Netzwerk &amp; Security bis zu CI/CD.</li>
<li>Du integrierst und konfigurierst AI‑Komponenten (z. B. LLM‑Serving, RAG‑Pipelines, Vector‑Datenbanken) und optimierst Performance &amp; Kosten.</li>
<li>Du verantwortest Observability (Monitoring/Logging/Tracing) und Sicherheit (Secrets, Zertifikate, SSO/IAM, Hardening) f&uuml;r produktive Umgebungen.</li>
<li>Du arbeitest eng mit DevOps, Architekt*innen und AI‑Teams zusammen und entscheidest technologisch &uuml;ber Plattform‑Bausteine.</li>
<li>Du baust mit uns den Managed Service f&uuml;r den Plattformbetrieb (SLIs/SLOs, On‑Call, Incident‑Prozesse) auf und entwickelst ihn weiter.</li>
</ul></div></div><div><div><h2 class="jobSectionHeader">Dein Profil</h2>
</div><div><ul><li>Mehrj&auml;hrige Erfahrung im DevSecOps/Platform‑Engineering in produktiven Umgebungen; Automatisierung liegt dir im Blut.</li>
<li>Sehr gute Kenntnisse in Kubernetes, Python und Infrastructure as Code (Terraform, Ansible o. &auml;.) inkl. GitOps‑Workflows.</li>
<li>Praxis im Betrieb verteilter Systeme inkl. Multi‑Service‑Orchestrierung (z. B. Reverse Proxies), Observability und Security‑Hardening.</li>
<li>Erste oder vertiefte Erfahrung mit KI‑Plattform‑Bausteinen: LLM‑Inferenz (z. B. vLLM/Triton), RAG, Vector‑Datenbanken und Frameworks (z. B. Langchain, Pydantic, FastAPI).</li>
<li>Motivation, souver&auml;ne KI‑Plattformen aktiv mitzugestalten und neue Technologien schnell zu erlernen; Deutsch &amp; Englisch mind. C1.</li>
</ul></div></div><div><div><h2 class="jobSectionHeader">Was du bei uns sch&auml;tzen wirst</h2>
</div><div><ul><li>Wir legen gro&szlig;en Wert auf die Vereinbarkeit von Arbeit und Privatleben. Deshalb hast du bei uns die M&ouml;glichkeit, hybrid aus dem Office, von zu Hause oder an anderen Capgemini Standorten in Deutschland zu arbeiten. Gleichzeitig bietet Capgemini dir flexible Arbeitszeitmodelle.</li>
<li>Dein Einstieg bei uns: In den ersten 12 Monaten deiner unbefristeten Festanstellung startest du mit unserem Einsteigerprogramm GetStarted direkt durch. Die Mischung macht&acute;s: Die Arbeit in Top-Projekten, professionelle Trainings, die enge Betreuung durch pers&ouml;nliche Mentor*innen und der Austausch mit Managern sowie Kolleginnen und Kollegen aus aller Welt bilden die perfekte Grundlage f&uuml;r deine IT-Karriere.</li>
<li>Wir &uuml;bernehmen eine f&uuml;hrende Rolle, wenn es darum geht, Technologie verantwortungsvoll f&uuml;r nachhaltigen Fortschritt einzusetzen. Unser Ziel ist es, Kunden dabei zu helfen, bis 2030 10 Millionen Tonnen CO2-&Auml;quivalente einzusparen.</li>
</ul></div></div><div><div><h2 class="jobSectionHeader">Deine Benefits</h2>
</div><div><div><ul><li>Flexible Arbeitszeit- und Auszeitmodelle</li>
<li>Mobiles Arbeiten &ndash; auch hybrid von Zuhause aus</li>
<li>Jobfahrrad-Programm</li>
<li>Mobilit&auml;tsbudget</li>
<li>Vielf&auml;ltiges Weiterbildungsangebot</li>
<li>Internationales Netzwerk</li>
<li>Kooperation mit dem pme Familienservice</li>
<li>Deferred Compensation &ndash; im Alter gut abgesichert</li>
<li>Verl&auml;ngerte Entgeltfortzahlung im Krankheitsfall</li>
<li>Gesundheitsangebote</li>
<li>Attraktiver Arbeitsplatz f&uuml;r Menschen mit Handicap</li>
<li>Kontakthalteprogramm fareWelcome!</li>
<li>Work-life-balance</li>
<li>Mitarbeiterrabatte</li>
<li>Team- und Sportevents</li>
</ul></div><div>S&auml;mtliche in der Anzeige genannten Nebenleistungen geben lediglich einen ersten &Uuml;berblick ohne Anerkennung einer Rechtspflicht. Sie richten sich nach den jeweils g&uuml;ltigen Betriebsvereinbarungen, Policies, betrieblichen Regelungen und Anspruchsvoraussetzungen zum Zeitpunkt des Eintritts in das Unternehmen.
</div></div></div><div><div><h2 class="jobSectionHeader">Bewirb dich jetzt</h2>
</div><div>F&uuml;r den ersten Schritt in Richtung Zukunft brauchst du nur drei Minuten Zeit und deinen aktuellen Lebenslauf.
Bitte sende keine Bewerbungen per E‑Mail. Bewerbungen werden ausschlie&szlig;lich &uuml;ber unser Online‑Bewerbungssystem entgegengenommen. Eingehende Bewerbungen per E‑Mail werden aus Datenschutzgr&uuml;nden ungelesen gel&ouml;scht. Bei Fragen steht dir Athina Deligkiozi unter career.de@capgemini.com zur Seite. Diese Anzeige ist online, solange die Stelle verf&uuml;gbar ist.
Capgemini lebt Vielfalt am Arbeitsplatz. Diversit&auml;t sorgt in unserem Unternehmen f&uuml;r Inspiration und Innovation. Wir freuen uns besonders &uuml;ber Bewerbungen von qualifizierten Talenten, unabh&auml;ngig von Herkunft, Nationalit&auml;t, Geschlecht, Hautfarbe, ethnischer und sozialer Herkunft, Religion, Alter, Behinderung, sexueller Orientierung und Lebensphase.
</div></div></div>Capgemini ist ein globaler Partner f&uuml;r die KI-gest&uuml;tzte Gesch&auml;fts- sowie Technologietransformation. Das Unternehmen schafft messbaren Mehrwert f&uuml;r seine Kunden, indem es die Zukunft von Organisationen gestaltet und im Zusammenspiel von KI, Technologie sowie dem Mensch Realit&auml;t werden l&auml;sst. Seit fast 60 Jahren steht Capgemini f&uuml;r Verantwortung wie auch Vielfalt und besch&auml;ftigt 420.000 Mitarbeitende in &uuml;ber 50 L&auml;ndern. Das End-to-End-Leistungsspektrum gr&uuml;ndet auf einer umfangreichen Branchenexpertise, einem starken Partner-&Ouml;kosystem sowie Kompetenzen in den Bereichen Strategie, Technologie, Design, Engineering und Operations. Die Gruppe erzielte 2024 einen weltweiten Umsatz von 22,1 Milliarden Euro.</div></div></div></div>

AI Platform Engineer (w/m/d)

Neural Frames

<div>
 
 Neural Frames is a leading AI music video generator, turning any song into a fully produced music video in minutes. We're bootstrapped, profitable, and growing fast at over $5M ARR.
 
 
 
 Our ambition is to build a category-defining company, helping tens of millions of audio creators to visualize their content and promote it online.
 
 
 
 As a profitable company, there is no VC drama. We are a small, ambitious group of people, striving to build something creators love.
 
 
 Tasks
 
 <ul>
 
 <li>
 Own the systems that turn songs into videos: video generation pipelines, model orchestration, queue management, and the infrastructure that keeps it all running at scale.
 </li>
 
 <li>
 Design and build backend services in Python that orchestrate multiple AI providers (we work with fal, BytePlus, OpenRouter, AWS and others) and gracefully handle their quirks, failures, and pricing trade-offs.
 </li>
 
 <li>
 Improve reliability, latency, and cost across the generation stack. Every second shaved off a render and every cent saved per video compounds across millions of generations.
 </li>
 
 <li>
 Build the infrastructure for new product surfaces working closely with the founder and tech lead on architecture decisions.
 </li>
 
 <li>
 Instrument and monitor what you ship. You'll have real visibility into how your code performs in production and the autonomy to fix what's broken.
 </li>
 
 <li>
 Contribute to the AI/ML side of the stack: prompt engineering, model evaluation, fine-tuning pipelines, and experimenting with new models as they ship.
 </li>
 
 </ul>
 
 Requirements
 
 <ul>
 
 <li>
 You've shipped production Python backends that handled real load - async workloads, queues, retries, the unglamorous stuff that makes systems actually work.
 </li>
 
 <li>
 You're comfortable working with AI APIs and have opinions about how to wrangle them: cost, latency, failure modes, model selection.
 </li>
 
 <li>
 You think in systems. When something breaks, your instinct is to find the root cause, not patch the symptom.
 </li>
 
 <li>
 You have high agency. You see a bottleneck, you fix it. You don't wait for a ticket.
 </li>
 
 <li>
 Bonus points: experience with video/audio processing pipelines (ffmpeg, GStreamer, etc.), GPU orchestration, multi-provider AI infrastructure, or distributed systems at scale.
 </li>
 
 <li>
 You're genuinely excited about generative AI and where it's heading. You probably have a side project or two that proves it.
 </li>
 
 <li>
 You're based in Berlin and can join us in the office on at least four days a week.
 </li>
 
 </ul>
 
 Benefits
 
 
 VSOPs &amp; Profit Sharing. Bi-weekly team lunches, regular team events, an annual summer offsite, learning &amp; development support, productivity tools, a one-time headphone budget, Deutschlandticket, and a &euro;5,000 referral bonus.
 
 
 
 neural frames is dedicated to creating an equitable, inclusive, and supportive work environment that brings people together from diverse backgrounds, experiences, and perspectives. Our strength is in our differences. We're proud to be an equal opportunity employer and welcome all applicants as we're committed to promoting a culture of opportunity for all.
 
</div>

Backend Software Engineer // AI Music Video Platform

Code Compass 🧭

<div>
 
 🤖 Machine Learning Engineer &ndash; Computer Vision &amp; Generative AI &ndash; 100%
 
 
 
 
 
 📍 Berlin, Germany | 💰 &euro;50,000 - &euro;70,000 + Benefits | 🌍 Hybrid Working
 
 
 
 
 
 Our client is a technology-driven organisation developing intelligent software solutions that leverage artificial intelligence, automation, and advanced data processing to solve complex business challenges at scale.
 
 
 
 
 
 Operating at the intersection of machine learning, software engineering, and product innovation, they are investing heavily in next-generation AI capabilities and expanding their engineering team to support the continued evolution of their platform and services.
 
 
 
 
 
 This role is ideal for a Machine Learning Engineer who enjoys taking cutting-edge AI solutions from research to production and wants to work on technically challenging projects with tangible real-world impact.
 
 
 
 
 
 ⚙️ Tech Stack:
 
 
 Python, PyTorch, TensorFlow, Computer Vision, Generative AI, Diffusion Models, GANs, Image Processing, Machine Learning, Docker, Cloud Platforms, Production ML Systems, Automation, AI Workflows
 
 
 
 
 
 🚀 About the Role:
 
 
 
 
 <ul>
 <li>
 As a Machine Learning Engineer, you will:
 </li>
 <li>
 Develop, train, and optimise machine learning models focused on computer vision and generative AI applications
 </li>
 <li>
 Build and deploy scalable ML solutions into production environments
 </li>
 <li>
 Design automation solutions that reduce manual effort and improve operational efficiency
 </li>
 <li>
 Monitor model performance, identify improvement opportunities, and enhance reliability and accuracy
 </li>
 <li>
 Collaborate closely with engineering, product, and operational teams to deliver practical AI-driven solutions
 </li>
 <li>
 Research emerging technologies and rapidly evaluate their suitability for business applications
 </li>
 <li>
 Contribute to the evolution of production-grade machine learning infrastructure and workflows
 </li>
 </ul>
 
 
 
 
 ➕ Nice to Have:
 
 
 
 
 <ul>
 <li>
 Several years of hands-on experience within machine learning and computer vision
 </li>
 <li>
 Strong Python development skills with experience using frameworks such as PyTorch or TensorFlow
 </li>
 <li>
 Practical experience working with generative AI technologies including diffusion models and GANs
 </li>
 <li>
 Understanding of ML deployment, scalability, performance optimisation, and production environments
 </li>
 <li>
 Experience with Docker and cloud-based infrastructure
 </li>
 <li>
 Knowledge of creative AI tools and visual content workflows
 </li>
 <li>
 Experience working with image-based products, digital content platforms, or related industries
 </li>
 <li>
 Strong analytical thinking combined with a pragmatic, solution-oriented mindset
 </li>
 <li>
 Ability to communicate effectively in an international and cross-functional environment
 </li>
 </ul>
 
 
 
 
 💪 Benefits:
 
 
 
 
 <ul>
 <li>
 Opportunity to work on cutting-edge AI and machine learning technologies
 </li>
 <li>
 Highly collaborative and innovative working environment
 </li>
 <li>
 Flexible working arrangements with hybrid options
 </li>
 <li>
 Exposure to challenging technical problems with real-world impact
 </li>
 <li>
 Professional development support, training, and continuous learning opportunities
 </li>
 <li>
 Modern working environment with strong team culture and regular social activities
 </li>
 </ul>
 
 
 
 
 
 ✉️ Due to the volume of applications, we may not be able to respond to everyone individually. However, we genuinely appreciate every application and will contact shortlisted candidates directly.
 
 
</div>

Machine Learning Engineer

ALMETRA

<div>Platform Engineer
We're looking for a (Senior) Platform Engineer to own and evolve our infrastructure &mdash; with a focus on developer experience and the chance to get hands-on with AI systems.
What you'll do<ul><li>
Design and maintain cloud infrastructure on AWS using Terraform</li><li>
Own and improve CI/CD pipelines for fast, safe deployments</li><li>
Manage and scale Kubernetes clusters</li><li>
Improve developer experience &mdash; making it easy for teams to ship and debug</li><li>
Implement monitoring, logging and alerting for full observability</li><li>
Configure and optimise CDN infrastructure</li></ul>
You are<ul><li>
8-10 years of experience in DevOps, SRE or platform engineering roles</li><li>
Expertise in AWS</li><li>
Proficient with Terraform and infrastructure-as-code workflows</li><li>
Experienced in building and maintaining CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins or similar)</li><li>
Solid understanding of Kubernetes &mdash; deployment, networking, scaling and troubleshooting</li><li>
Strong sysadmin fundamentals &mdash; Linux, networking, storage and configuration management</li><li>
Comfortable working with relational databases (PostgreSQL, MySQL) and time series databases (TimescaleDB, Prometheus)</li><li>
A clear communicator who works well across engineering and data science teams</li><li>
Pragmatic and reliable &mdash; you know when to move fast and when to be careful</li></ul>
Nice to have<ul><li>
Experience supporting ML infrastructure &mdash; model deployment, GPU workloads or training pipelines</li><li>
Background in CDN configuration (CloudFront, Fastly, Cloudflare)</li><li>
Familiarity with streaming data or video processing systems</li><li>
Interest in MLOps and bridging the gap between ML research and production</li></ul>
Why this role matters
You'll keep our systems running smoothly and help the team ship with confidence. And if you're curious about ML, you'll get real exposure to production AI systems.
#LI-SP1 #LI-Hybrid
What we offer
Employee Share Options Program for all permanent employees*
An increasing benefits list: currently includes Urban Sports club and quarterly team retreats.
Be on the forefront in defining what artificial intelligence means in manufacturing
Gain hands-on experience in working in an AI-first software company
Supportive and inclusive culture that values diversity and promotes the advancement of underrepresented groups within the company
Collaborate with a diverse (currently more than 10 nationalities) and talented team, working on cutting-edge projects with real-world impact
Network with professionals and leaders in the field, opening doors to potential future career opportunities
We have a very flat hierarchy, open 360&deg; feedback, and flexible working hours
Ethics: We are committed to developing ethical AI software 
 
Don't meet all the requirements?
Almetra is committed to creating a workplace that is diverse, fair, and inclusive. We encourage candidates from all backgrounds, even if they do not meet every qualification, to submit their application. We firmly believe that having a team with diverse perspectives only strengthens our company and drives innovation. Our commitment also extends to providing an accessible environment for everyone, including those with disabilities. Please let us know if you require any accommodations during the application process or while working with us, and we will do our best to support you.<ul><li> 
Only full-time, permanent roles are eligible for stock options. Part-time roles, contract roles, work-student, internships and freelance roles are not eligible for stock options.</li></ul>
Compensation Range: &euro;70K - &euro;85K</div>

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