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senior applied ai ml application engineer f m x

BMW Group

<div><div><p><b>ARE YOU PREPARED FOR THE FUTURE? AI, AI SIR!</b></p><p>
Artificial Intelligence and machine learning are at the cutting edge when it comes to shaping next-gen mobility in areas like automated driving. But it takes real intellectual leadership and expertise to identify and then harness the AI trends and technologies that will transform the way people travel for good.</p><br>
</div><p></p><div><p>In this role, you will build, prototype, and deliver use cases that leverage edge device models. By understanding real user problems, model capabilities are translated into meaningful product experiences that make the voice assistant and in‑car intelligence truly useful. Together with the model engineering product team, you will be a key contributor to our product: the BMW Intelligent Personal Assistant.</p><p><b>
What awaits you?</b></p><ul><li>
You will integrate models that run on edge devices within the infotainment domain.</li><li>
Furthermore, you will prototype &amp; build new GenAI experiences, turning ideas into reality as refined features that will be launched to our customers.</li><li>
You will collaborate with the model engineering team to respect latency, memory, and performance budgets in edge devices and in the cloud.</li><li>
You will work closely with staff engineers to shape our model landscape and tooling infrastructure to deliver customer value.</li><li>
Additionally, you will build evaluation tools for real-world interaction quality, robustness, and failure modes.</li><li>
You will partner with our UX teams to refine design, fallback flows, and safe error handling.</li></ul><p><b>
What should you bring along?</b></p><ul><li>
University degree in Computer Science, Engineering, or a related field.</li><li>
At least five years of proven experience in application engineering with a track record of delivering for a large customer base.</li><li>
Strong engineering experience integrating GenAI &amp; ML models to serve delightful use cases.</li><li>
Solid Python and Java/Kotlin experience.</li><li>
You know how to debug ambiguous GenAI failures and improve behavior through iteration.</li><li>
You are hands-on with a bias for action.</li><li>
You enjoy working on complex problems in an international in-house team of experts.</li><li>
You are comfortable working with constrained, offline, edge-device models and designing around their limitations.</li></ul><p>
Are you ready to shape the future of in-car intelligence with us? Apply now!<br>
Find out more about Artificial Intelligence at the BMW Group here.</p><p><b>
Note: </b>Please apply exclusively online via our career portal. Applications via other channels (esp. e-mail) cannot be considered.</p><p><b>
What do we offer?</b></p><ul><li>
Challenging projects with which we are shaping the mobility of tomorrow together.</li><li>
Wide range of personal and professional development opportunities.</li><li>
Attractive, fair and performance-related remuneration.</li><li>
High level of job security.</li><li>
Annual special payments such as vacation pay, Christmas bonus, and profit sharing.</li><li>
Flexible working hours including 6 weeks annual leave and overtime compensation.</li><li>
Discounted BMW &amp; MINI conditions.</li><li>
Many other benefits at <b>bmw.jobs/benefits</b></li></ul><p></p><p><b><br>
Start date:</b> from now on
</p><p><b>Type of employment:</b> unlimited<br>
<b>Working hours:</b> Full-time</p><p><br>
If you apply, the next stages of the recruiting process include online testing and then an interview with the hiring manager (either virtual or in person).</p><p></p><p><br>
You can find helpful tips on your application and the application process.</p><p>
At the BMW Group, we place great importance on equal treatment and equal opportunities. Our recruiting decisions are based on the personality, experience, and skills of the applicants.</p></div></div><p></p>
<br><div><div>Legal Entity:</div>
<div><div>BMW AG
</div></div><div>Location:</div>
<div>Munich
</div><div>Job Field:</div>
<div>Software Development
</div><div>Job Id:</div>
<div>181974</div>
<div>Publication Date:</div>
<div>27.03.2026</div></div>

Senior Applied AI / ML Application Engineer (f/m/x)

osapiens

<div>
 <strong>
  Department:
 </strong>
 osapiens Terra
 <br/>
 <br/>
 <strong>
  Location:
 </strong>
 M&uuml;nchen
 <br/>
 <br/>
 <strong>
  Description
  <br/>
  <br/>
 </strong>
 <strong>
  About the role
  <br/>
  <br/>
 </strong>
 As a Machine Learning Engineer (m/f/x), you will work on the machine learning systems powering our geospatial analytics platform. You will contribute to the development, deployment, and improvement of production ML models that analyze satellite imagery and detect environmental risks at scale. You will collaborate closely with product managers, software engineers, and geospatial experts to build scalable ML solutions that support real-world sustainability and compliance use cases. Your work may include improving existing deforestation detection models, developing new deep learning approaches for remote sensing data, and building reliable tooling and infrastructure for model training and deployment.
 <br/>
 <br/>
 <strong>
  Your Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Develop, train, and improve machine learning models for geospatial and satellite imagery analysis
  </li>
  <li>
   Contribute to the full ML lifecycle, including experimentation, evaluation, deployment, monitoring, and maintenance
  </li>
  <li>
   Work on production systems that process large-scale satellite and geospatial datasets
  </li>
  <li>
   Collaborate with ML engineers, backend engineers, product teams, and geospatial analysts to deliver reliable analytics products
  </li>
  <li>
   Improve model performance, scalability, and robustness across different geographies and datasets
  </li>
  <li>
   Build and optimize data pipelines, tooling, and workflows for efficient ML development
  </li>
  <li>
   Apply modern deep learning and statistical techniques to remote sensing and environmental data
  </li>
  <li>
   Support rapid experimentation while maintaining production reliability
  </li>
  <li>
   Contribute to technical discussions, code reviews, and engineering best practices
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  You May Be a Good Fit If You
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Have a strong quantitative background in computer science, engineering, mathematics, remote sensing, or a related field
  </li>
  <li>
   Have strong programming skills in Python and hands-on experience with modern deep learning frameworks such as PyTorch or TensorFlow
  </li>
  <li>
   Hands-on experience with MLOps tools such as Weights &amp; Biases, cloud infrastructure including Amazon Web Services, and/or high-performance computing environments
  </li>
  <li>
   Feeling comfortable developing, training, and optimizing machine learning models in production environments
  </li>
  <li>
   Communicate clearly and collaborate effectively across technical and non-technical teams
  </li>
  <li>
   Have experience working with large datasets and distributed data processing workflows
  </li>
  <li>
   Work effectively with AI-assisted development and coding tools
  </li>
  <li>
   Are fluent in English (C1+). German skills are a plus
   <br/>
   <br/>
  </li>
 </ul>
 Nice to have
 <br/>
 <br/>
 <ul>
  <li>
   Experience with computer vision tasks such as segmentation, classification, change detection, or time-series analysis
  </li>
  <li>
   Experience working with remote sensing or satellite data (SAR, optical, LIDAR)
  </li>
  <li>
   Familiarity with geospatial data processing libraries and tools
  </li>
  <li>
   Experience deploying ML systems into production environments
  </li>
  <li>
   Understanding of environmental, climate, or sustainability-related use cases
  </li>
  <li>
   Experience translating complex business or regulatory requirements into data-driven solutions
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Join us for this and more...
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   The opportunity to work on meaningful technology with real-world environmental impact
  </li>
  <li>
   A highly technical and collaborative team environment
  </li>
  <li>
   Modern ML infrastructure and large-scale geospatial datasets
  </li>
  <li>
   Ownership and growth opportunities based on your experience and interests
  </li>
  <li>
   Flexible working environment in our Munich office near Sendlinger Tor
  </li>
  <li>
   Competitive compensation and benefits
  </li>
 </ul>
</div>


Machine Learning Engineer (m/f/x) - Geospatial AI

Agile Robots SE

<div>
 <p>
  <strong>
   The AI Research Division of Agile Robots
  </strong>
  is looking for an
  <strong>
   ML Platform Engineer (m/f/d)
  </strong>
  , who will build and operate the distributed training, deployment, and experimentation infrastructure that research, data, and robotics teams depend on to move models from prototype to production.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Your Responsibilities
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    Training Infrastructure:
   </strong>
   Design and scale distributed training workflows for large models using tools such as PyTorch Distributed, DeepSpeed, and cluster schedulers like SLURM or Kubernetes.
  </li>
  <li>
   <strong>
    ML Platform:
   </strong>
   Build and maintain containerised ML environments that support reproducible experimentation and benchmarking.
  </li>
  <li>
   <strong>
    CI/CD Pipelines:
   </strong>
   Develop and maintain CI/CD pipelines for machine learning systems to enable reliable testing, training, and deployment of models.
  </li>
  <li>
   <strong>
    Lifecycle Management:
   </strong>
   Implement experiment tracking, model versioning, and reproducibility workflows using tools such as ClearML or Weights &amp; Biases.
  </li>
  <li>
   <strong>
    Observability:
   </strong>
   Set up monitoring systems such as Prometheus and Grafana to track model performance and system health and detect drift in production.
  </li>
  <li>
   <strong>
    Cross-Team Collaboration:
   </strong>
   Work with research, data, and robotics teams to connect new models to robust production systems.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Essential Skills
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    Background and Experience:
   </strong>
   Degree in Computer Science, Software Engineering, or a related field, with professional experience building and operating ML or software infrastructure in production.
  </li>
  <li>
   <strong>
    Distributed Training:
   </strong>
   Experience designing and operating distributed training systems on Kubernetes and Docker, using PyTorch Distributed, DeepSpeed, and schedulers such as SLURM.
  </li>
  <li>
   <strong>
    CI/CD For ML:
   </strong>
   Experience building CI/CD pipelines that support reliable model testing, training, and deployment.
  </li>
  <li>
   <strong>
    Cloud Infrastructure:
   </strong>
   Experience operating ML workloads on cloud infrastructure, preferably AWS.
  </li>
  <li>
   <strong>
    Experiment Tracking:
   </strong>
   Hands-on experience with experiment tracking and model versioning using tools such as MLflow or Weights &amp; Biases.
  </li>
  <li>
   <strong>
    Observability:
   </strong>
   Experience with monitoring and drift detection using tools such as Prometheus and Grafana.
  </li>
  <li>
   <strong>
    Software Engineering:
   </strong>
   Python and system design skills, with experience building and operating ML systems beyond the prototype stage.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Beneficial Skills
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    Multimodal Systems:
   </strong>
   Experience with large-scale or multimodal ML systems such as vision-language-action models.
  </li>
  <li>
   <strong>
    Infrastructure As Code:
   </strong>
   Familiarity with infrastructure-as-code tools such as Terraform.
  </li>
  <li>
   <strong>
    ML Orchestration:
   </strong>
   Experience with ML pipeline and orchestration tools.
  </li>
  <li>
   <strong>
    Distributed Compute:
   </strong>
   Exposure to high-performance or distributed compute environments.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What we offer
  </strong>
 </p>
 <ul>
  <li>
   Dynamic high-tech company combined with financial soundness and world class investors.
  </li>
  <li>
   Join an interdisciplinary, international team with 60+ different nationalities in a collaborative work environment.
  </li>
  <li>
   Lots of development opportunities in the context of our continued growth.
  </li>
  <li>
   Challenging tasks and impactful projects alongside experts that enable professional and personal growth.
  </li>
  <li>
   Corporate Benefits Program that covers health, mobility and learning with 100 &euro; net per month.
  </li>
  <li>
   Modern office facilites with a rooftop terrace overlooking Munich, free drinks &amp; fruits, and regular company events contribute to a good working environment.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Agile Robots SE
  </strong>
  is an international high-tech company based in Munich, Germany with a production site in Kaufbeuren and more than 2300 employees worldwide. Our mission is to bridge the gap between artificial intelligence and robotics by developing systems that combine state-of-the-art force-moment-sensing and world-leading image-processing technology. This unique combination of technologies allows us to provide user-friendly and affordable robotic solutions that enable intelligent precision assembly.
 </p>
 <p>
  <br/>
 </p>
 <p>
  This is made possible by our employees, who bring out the best in each and every day with creativity and enthusiasm. Become part of this team and shape the future of robotics with us!
 </p>
 <p>
  We are proud of our diversity and welcome your application regardless of gender and sexual identity, nationality, ethnicity, religion, age, or disability.
 </p>
</div>


ML Platform Engineer (m/f/d)

Siemens

<div><div><p><b>Transform the everyday</b></p></div><div><div><div><div><p>
Siemens builds the systems the physical world runs on: factories, power grids, buildings, trains, hospitals. Industrial and physical AI is a major opportunity in applied AI, and one of the harder ones to get right. There is a generation of AI-powered products to build.</p><p>
We are an applied science organization building the science behind them. The work sits at the intersection of machine learning research, real world data, and production systems running in industrial environments.</p><p>
As Principal Applied Scientist, you lead the science on a major capability area inside the pod. You take ambiguous problems through hypothesis, method selection, experimentation, and into models that run in production. You are hands on with the modeling, and you are accountable for the rigor and the outcome.</p><p>
This is a senior individual contributor role. You will work in close partnership with engineers and product managers who turn your work into product.</p><div><b>
As part of our team, you will have</b></div></div></div><p></p><ul><li>
An attractive remuneration package</li><li>
Appealing Siemens pension benefits</li><li>
Access to employee share plans</li><li>
30 days of paid vacation and a variety of flexible work schedules that allow time off for you and your family</li><li>
2 to 3 days of mobile working per week as a global standard</li><li>
Up tp 30 days workation per year in certain countries</li></ul>
Since each of over 300,000 team members feels that other benefits are particularly important, and we cannot list our entire benefit portfolio here, you can find more information here.<br>
<br>
<p>The individual benefits are subject to regulatory, contractual, or corporate conditions.</p><p>
Y<b>ou&rsquo;ll make an impact by</b></p><ul><li>
Own one or more scientific capability areas end to end, for example perception, computer vision, language and agents, time series, control, planning, or evaluation</li><li>
Take problems from ambiguous product or system requirements through clear research questions, hypotheses, and success metrics</li><li>
Lead applied research projects: literature review, method selection, experimentation, ablation, error analysis, and productization</li><li>
Build and run the evaluation pipelines for the work you own: offline metrics, online experiments, robustness testing in industrial conditions</li><li>
Work with engineers to take models into production grade pipelines: data readiness, training infrastructure, inference, observability</li><li>
Make scientific tradeoffs in front of engineers and product managers, with evidence, and translate them into decisions the team can act on</li><li>
Identify and de-risk scaling challenges in your area: data quality, model drift, latency, throughput, cost, safety</li><li>
Raise the bar on experimentation rigor, reproducibility, and documentation across the team</li><li>
Apply responsible AI practices in your work: bias detection, model risk management, human in the loop controls</li></ul></div></div><div><div><p><b>
This how you'll win us over</b></p><ul><li>
Education</li><li><ul><li>
Master&acute;s degree or an equivalent qualification in Computer Science, Machine Learning, or a related field</li></ul></li><li>
Experience &amp; Skills</li><li><ul><li>
8+ years in applied machine learning, AI research, or data science, with models that shipped to production and made an impact</li><li>
Strong foundation in machine learning theory and practice across training, evaluation, and deployment</li><li>
Demonstrated experience taking research from a paper or prototype into a model that runs reliably in production</li><li>
Proficiency in Python and modern ML frameworks and toolchains</li><li>
Strong partnership track record with engineering teams on data, training infrastructure, and inference</li><li>
Clear written and verbal communication with engineers, product managers, and senior leaders</li></ul></li><li>
Preferred Qualifications:</li><li><ul><li>
Experience applying ML in industrial or physical domains: manufacturing, automation, robotics, energy, mobility, infrastructure, healthcare</li><li>
Deep expertise in one of: multimodal ML, generative AI, retrieval augmented generation, agentic workflows, time series, control, or planning</li><li>
Scientific ML for physical systems: surrogate modeling, operator learning, physics-informed ML, geometry-aware ML, differentiable simulation, AI for semiconductor/EDA</li><li>
Hands-on experience building evaluation pipelines, running online experiments, or instrumenting production monitoring for a model you owned</li><li>
Publications, patents, open source contributions, or significant internal technology transfers</li><li>
Experience mentoring more junior scientists and engineers</li><li>
Experience working with globally distributed research, product, or engineering organizations</li></ul></li><li>
Ways of working: You operate with high autonomy, lead scientific excellence, and collaborate closely across engineering and product teams</li><li>
Languages: business proficiency in English</li></ul><div>
You are much more than your qualifications, and we believe in the potential of every single candidate. We look forward to getting to know you!</div></div></div><p></p><div><div><p><br>
Your individual personality and perspective are important to us. We create a working environment that reflects the diversity of the society and support you in your personal and professional development. Let&rsquo;s get to know your authentic personality and create a better future together with us. As an equal-opportunity employer we are happy to consider applications from individuals with disabilities.</p><p><b>
About us</b></p><p>
To transform the everyday, you need to think outside the box. That&rsquo;s why we at Siemens are looking for innovators who aren&rsquo;t afraid to push boundaries to join our diverse team of tech experts. Got what it takes? Then help us create lasting, positive change!</p><p>
www.siemens.de/careers &ndash; if you would like to find out more about jobs &amp; careers at Siemens.
</p><p>FAQ &ndash; if you need further information on the application process.</p></div></div></div><div></div>

Principal Applied Scientist (f/m/d)

Manex AI

<div><h1 class="jobSectionHeader"><b>AI Software Engineer - Internship (f/m/d)</b></h1><div></div><p><b><br>
About Us</b><br>
Manex AI is on a mission to enable autonomy for the world's leading organizations, currently building the production system for the era of autonomous manufacturing. With our Seed Round raised from Lightspeed and BlueYard and leading manufacturing enterprises relying on our systems, we are now scaling fast. For our world-class team, we are looking for exceptionally driven students who want real ownership early.</p><p><b>
Your Role</b><br>
You will build the software and AI applications that power autonomous manufacturing. You work on our platform &quot;Kosmos&quot; alongside our engineers, shipping features and AI-driven solutions that go straight into live production environments at industry leaders including BMW, Audi, BSH, Stellantis, Still, TDK Electronics, and Co.</p><p>
From your first week, you own pieces of real problems. You write code that goes into production, you see your work run inside real factories, and you learn exactly how technical decisions create measurable impact for some of the most demanding manufacturers in the world.</p><p>
For interns who deliver, this is the fastest path into a full-time engineering role.</p><p><b>
Your Responsibilities</b></p><ul><li><p>
Build software and AI application features within real customer projects</p></li><li><p>
Work alongside senior engineers to troubleshoot, document, and ship solutions</p></li><li><p>
Support the technical integration of our platform into customer environments</p></li><li><p>
Turn concrete customer requirements into working technical solutions</p></li><li><p>
Learn how production processes, IT infrastructure, and AI products come together</p></li></ul><p><b>
Your Profile</b></p><ul><li><p>
Currently studying Computer Science, Information Systems, or similar, towards the end of your Bachelor's or the start of your Master's</p></li><li><p>
Strong hands-on coding ability, proven through your own projects, ventures, or open-source work</p></li><li><p>
An ownership mindset: you take initiative, move fast, and finish what you start</p></li><li><p>
Ideally strong experience in Python, TypeScript and Docker</p></li><li><p>
Fluent in English and ideally in German as well</p></li><li><p>
Based in Munich or willing to relocate for the duration of the internship</p></li></ul><p>
We appreciate your application even if you don't tick all the boxes.</p><p><b>
What We Offer</b></p><ul><li><p>
Real ownership from day one</p></li><li><p>
A fast-track into a full-time role
</p></li><li><p>Direct mentorship from senior engineers and direct access to founders</p></li><li><p>
Hands-on experience onsite with real customers, real production systems, and frontier AI</p></li><li><p>
A fast-paced environment backed by the world's best investors, with the world's leading organizations as customers</p></li></ul><p><br>
Want to build real things at the edge of industrial AI? Apply now.</p></div>

AI Software Engineer - Internship (f/m/d)

<div><h1 class="jobSectionHeader"><b>AI Software Engineer (f/m/d)</b></h1><div>
</div><h2 class="jobSectionHeader"><b>
About Us</b></h2><p>
Manex AI is on a mission to enable autonomy for the world&rsquo;s leading organizations and is currently building autonomous factories. After raising our Seed Round from Lightspeed and BlueYard and winning leading enterprise manufacturing customers, we are now focused on scaling operations across all departments. With our world-class team, we are looking for the key individuals who will help take us to the next level and build a truly outstanding organization.</p><div><br>
</div><h2 class="jobSectionHeader"><b>
Your Role</b></h2><p>
As an AI Software Engineer, you build the applications that make autonomy real on the factory floor. You work embedded inside the production environments of our customers - industry leaders including BMW, Audi, BSH, Stellantis, Still, TDK Electronics, and Co. - where our platform &quot;Kosmos&quot; meets the messy reality of manufacturing. You take the hardest technical problems our customers have and turn them into working software, powered by data and AI, inside their most critical, high-stakes processes.</p><p>
Most of your time goes into building: developing AI-driven applications, designing the integration architectures around them, and shipping solutions that create measurable impact - while becoming a trusted technical contact for our customers along the way.</p><div><br>
</div><h2 class="jobSectionHeader"><b>
Your Responsibilities</b></h2><ul><li><p>
Direct software and AI application development within customer projects</p></li><li><p>
Troubleshoot, document, co-create solutions alongside senior software engineers, and drive product development</p></li><li><p>
Support technical integration of our platform into customer IT landscapes</p></li><li><p>
Learn how production processes, IT infrastructure and AI products intersect</p></li><li><p>
Translate customer requirements into technical solutions and specifications</p></li></ul><div><br>
</div><h2 class="jobSectionHeader"><b>
Your Profile</b></h2><ul><li><p>
Degree in Computer Science, Information Systems, or similar</p></li><li><p>
0 to 4 years professional experience or internships in software engineering or similar</p></li><li><p>
Hands-on experience through projects, ventures, or product development</p></li><li><p>
Curiosity for manufacturing, how factories actually run, newest tech, product development, and beyond</p></li><li><p>
Business-fluent in German and English</p></li><li><p>
Based in Munich or willing to relocate, ready to go all-in with us</p></li></ul><div><br>
</div><h2 class="jobSectionHeader"><b>
What We Offer</b></h2><ul><li><p>
Unique opportunity to become part of a top-tier team with hands-on responsibility and learn how to build lasting collaborations with leading customers</p></li><li><p>
Mentorship &amp; fast learning curve in a high-impact AI-Startup environment, incl. flat hierarchy, direct access to founders, and fast decisions</p></li><li><p>
Top-of-market compensation with equity package</p></li><li><p>
Develop a best-in-class network (funding, industry, and talent) in Europe and the US</p></li><li><p>
A fast-paced environment backed by the world's best investors with the world's leading organizations as customers</p></li></ul><div></div><p><br>
Are you willing to start contributing to European autonomy at scale? Apply now!</p></div>

AI Software Engineer (f/m/d)

techtree

<p>About the Role</p><p>A leading frontier AI company is looking for an <b>Applied AI Engineer</b> to join their Solutions team in Munich.</p><p>This is a customer-facing technical role, but the balance is heavily technical: roughly 20% involves presales support, onboarding, and client guidance - the other 80% is designing, developing, and deploying AI solutions for B2B enterprise clients.</p><p>Your stakeholders are technical. You won't be simplifying things for non-technical audiences - you'll be working directly with data scientists, software engineers, and CTOs on complex, high-impact implementations.</p><p>This is not a consultancy role. You'll operate with the mindset of a startup CTO embedded in a world-class AI team: owning projects end-to-end, shipping working solutions, and collaborating closely with researchers and product engineers on the company's most challenging customer problems.</p><p>What You'll Do</p><ul><li>Deploy AI solutions into production across various industries, delivering measurable business impact</li><li>Build state-of-the-art GenAI applications - from consumer products to industrial use cases</li><li>Develop complex implementations involving fine-tuning, advanced RAG pipelines, agentic workflows, and custom LLM applications</li><li>Participate in presales calls to understand client needs and provide technical guidance</li><li>Collaborate with researchers and product engineers on the team's most demanding customer projects</li><li>Feed customer insights back into product and model development</li></ul><p>How the Team Works</p><ul><li>What matters is what you ship, not the time you spend on it</li><li>No bureaucracy - you talk to whoever you need to, the best idea wins</li><li>Low ego, high standards; direct, honest feedback</li><li>Unstructured environment where people find joy in ambiguity</li></ul><p>About You</p><ul><li>Fluent in English and <b>German</b> (required for this Munich-based role)</li><li>2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products</li><li>Proven experience implementing AI/ML products with APIs, back-end and front-end interfaces</li><li>Hands-on experience with fine-tuning LLMs, advanced RAG, or agentic use cases</li><li>Deep understanding of machine learning concepts and the algorithms underlying LLMs</li><li>Strong Python coding skills</li><li>Able to explain complex technical concepts clearly to technical audiences</li></ul><p>Nice to Have</p><ul><li>Open-source contributions, especially in the LLM space</li><li>Prior experience as a Customer Engineer, Forward Deployed Engineer, Solutions Architect, or Technical PM</li><li>Experience with PyTorch and deep learning</li></ul><p>Compensation</p><ul><li>Base salary + equity</li></ul><p>Job Type: Full-time</p><p>Pay: 61.504,42&euro; per year</p><p>Application Question(s):</p><ul><li>Cover letter</li><li>Expected Salary</li></ul><p>Work Location: In person</p>

Applied AI Engineer

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