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machine learning engineer

ALMEDIA

<div><p>This isn&rsquo;t your regular job. Almedia is a place where those who want to push harder can accelerate their careers faster than anywhere else. We&rsquo;re aiming to become Germany&rsquo;s second bootstrapped unicorn. Almedia is already Europe&rsquo;s #3 fastest-growing company in 2025 (FT1000).</p><p></p><p>
We are building the future of marketing by rewarding our community of over 70 million users for engaging with our advertisers&rsquo; products. We are offering a new way to acquire users for the biggest companies in the world.</p><p></p><h2 class="jobSectionHeader"><b><br>
Principal Machine Learning Engineer</b><b>
</b></h2><p>You'll take ownership of the hardest ML problems across Almedia's products and growth. This is a hands-on role for someone who identifies what matters most, sets the technical direction, and drives it end to end with minimal oversight.</p><p></p><h2 class="jobSectionHeader"><b>
Types of problems you'll be solving</b></h2><ul><li><p>
Designing and owning the strategy for user reward schemes at scale, across behaviour signals and market dynamics</p></li><li><p>
Architecting real-time personalisation systems for reward values that operate at production scale</p></li><li><p>
Defining how we detect and diagnose underperforming campaigns, and building the systems that act on it</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
Your role</b></h2><ul><li><p>
Own end-to-end delivery of high-impact ML systems: from problem framing through to production and iteration</p></li><li><p>
Set the technical bar for ML across the org, establishing best practices and raising the quality of decisions</p></li><li><p>
Define where ML creates the most business value and align the roadmap accordingly</p></li><li><p>
Apply advanced statistical and causal inference methods with rigour and production-readiness</p></li><li><p>
Partner with product and engineering leadership to shape how technical capability maps to strategic priorities</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
You have</b></h2><ul><li><p>
A strong track record of taking ambiguous, high-impact problems from first principles to production independently</p></li><li><p>
Deep expertise in statistics, causal inference, and experimentation at scale</p></li><li><p>
Mastery of Python and SQL, with extensive hands-on cloud and production systems experience</p></li><li><p>
A history of setting technical direction and raising the bar for engineering teams around you</p></li><li><p>
The communication range to influence both engineers and senior business stakeholders</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
Bonus points for</b></h2><ul><li><p>
Passion for gaming and a strong intuition for player behaviour</p></li><li><p>
Experience in adtech, monetisation platforms, or the gambling industry</p></li><li><p>
Familiarity with gaming KPIs such as pLTV, retention, and ROAS</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
Why Almedia?</b></h2><ul><li><p>
Scale With Almedia: Have a real impact and grow alongside a startup that has been profitable from day one.</p></li><li><p>
High-Growth Environment: We encourage all staff to take ownership of projects and consistently raise the bar.</p></li><li><p>
Do More, Get More: Generous bonus scheme to ensure great, proactive work is valued.</p></li></ul><p></p><p>
We believe in fostering talent, evaluating all skill levels during the hiring process, and providing a clear path for growth. Almedia is an equal opportunity employer. We embrace and celebrate diversity, and encourage individuals from all backgrounds to apply.</p></div>

Principal Machine Learning Engineer

Zeta Global

<div>
 <p>
  &nbsp;
 </p>
 <p>
  <strong>
   WHO WE ARE&nbsp;
  </strong>
 </p>
 <p>
  Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform &ndash; powered by one of the industry&rsquo;s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.
 </p>
 <p>
  &nbsp;
 </p>
 <p>
  <strong>
   The Role
  </strong>
 </p>
 <p>
  We&rsquo;re looking for a skilled&nbsp;
  <strong>
   ML Engineer / Data Scientist
  </strong>
  &nbsp;with&nbsp;
  <strong>
   3+ years of software or applied ML experience
  </strong>
  &nbsp;to design, build, and improve machine learning solutions in a dynamic cloud environment, primarily on&nbsp;
  <strong>
   AWS
  </strong>
  .This role sits at the intersection of&nbsp;
  <strong>
   data science and engineering
  </strong>
  : exploring data, developing models, running rigorous experiments, and bringing the best approaches into production with a reliable, reproducible workflow. If strong Python skills, curiosity about hard modeling problems, and collaborative work in multicultural teams are a fit, this is a chance to do meaningful, end-to-end ML work&mdash;not just notebooks, and not just infrastructure.
 </p>
 <p>
  &nbsp;
 </p>
 <p>
  <strong>
   Who you are:
  </strong>
 </p>
 <ul>
  <li>
   Strong foundation in&nbsp;
   <strong>
    machine learning,&nbsp;statistics
   </strong>
   and&nbsp;
   <strong>
    experiment design
   </strong>
   .
  </li>
  <li>
   Experience building models for&nbsp;
   <strong>
    real business or product problems
   </strong>
   , not only academic benchmarks.
  </li>
  <li>
   Comfortable working with&nbsp;
   <strong>
    structured and unstructured data
   </strong>
   : feature engineering, dataset construction, labeling quality, leakage checks, and train/validation/test discipline.
  </li>
  <li>
   Able to compare approaches with clear&nbsp;
   <strong>
    metrics
   </strong>
   , error analysis, and sound judgment about tradeoffs (accuracy, latency, cost, maintainability).
  </li>
  <li>
   Interest in&nbsp;
   <strong>
    modern ML
   </strong>
   , including classical ML, deep learning, and&nbsp;
   <strong>
    LLM / GenAI workflows
   </strong>
   &nbsp;where relevant (fine-tuning, RAG, evaluation, prompt/versioning).
  </li>
  <li>
   Proficient in&nbsp;
   <strong>
    Python
   </strong>
   &nbsp;and able to write&nbsp;
   <strong>
    clean, modular, testable&nbsp;code
   </strong>
   .
  </li>
  <li>
   Experience developing and deploying ML solutions in a&nbsp;
   <strong>
    cloud environment
   </strong>
   , especially&nbsp;AWS.
  </li>
  <li>
   Comfortable moving from prototype to production: packaging models, building inference paths, monitoring performance, and iterating after launch.
  </li>
  <li>
   Independent engineer who can own work from&nbsp;
   <strong>
    problem framing &rarr; experimentation &rarr; implementation &rarr; rollout
   </strong>
   .
  </li>
  <li>
   Excellent&nbsp;
   <strong>
    written and spoken English
   </strong>
   .
  </li>
  <li>
   Enjoy working closely with engineers, product partners, and other data scientists.
  </li>
  <li>
   Clear communicator who can explain methods, results, and limitations to technical and non-technical audiences.
  </li>
  <li>
   <strong>
    Master&rsquo;s degree
   </strong>
   &nbsp;in Science or Engineering (Computer Science, Mathematics, Physics, Statistics, or similar),&nbsp;
   <strong>
    or equivalent practical experience
   </strong>
   .
  </li>
 </ul>
 <p>
  <strong>
   Nice to have:
  </strong>
 </p>
 <ul>
  <li>
   Experience with&nbsp;
   <strong>
    scikit-learn,&nbsp;PyTorch,&nbsp;TensorFlow,&nbsp;XGBoost
   </strong>
   , or similar modeling stacks.
  </li>
  <li>
   Familiarity with&nbsp;
   <strong>
    ML experiment tracking
   </strong>
   &nbsp;and reproducibility (e.g. MLflow, W&amp;B).
  </li>
  <li>
   Experience with&nbsp;
   <strong>
    SQL
   </strong>
   , data warehouses/lakes, and pipeline tools such as&nbsp;
   <strong>
    Airflow,&nbsp;dbt, or&nbsp;Spark
   </strong>
   .
  </li>
  <li>
   Exposure to&nbsp;
   <strong>
    feature stores
   </strong>
   , embedding pipelines, or&nbsp;
   <strong>
    vector search
   </strong>
   &nbsp;for retrieval-based systems.
  </li>
  <li>
   Experience building&nbsp;
   <strong>
    HTTP/gRPC APIs
   </strong>
   &nbsp;or lightweight services around model inference.
  </li>
  <li>
   Working knowledge of&nbsp;
   <strong>
    Docker
   </strong>
   , basic orchestration, and CI/CD (e.g.&nbsp;
   <strong>
    GitLab CI
   </strong>
   ).
  </li>
  <li>
   Experience in&nbsp;
   <strong>
    agile
   </strong>
   ,&nbsp;
   <strong>
    remote
   </strong>
   and&nbsp;
   <strong>
    async
   </strong>
   &nbsp;team environments.
  </li>
  <li>
   Publications, patents, Kaggle/competition results, or open-source ML contributions.
  </li>
 </ul>
 <p>
  <strong>
   What you might like about this role:
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    Hands-on modeling work
   </strong>
   &nbsp;with room to explore, benchmark, and improve real systems.
  </li>
  <li>
   Collaboration on&nbsp;
   <strong>
    ML patent submissions
   </strong>
   &nbsp;and participation in&nbsp;weekly ML / research paper review&nbsp;meetings.
  </li>
  <li>
   A&nbsp;
   <strong>
    multicultural, engineering-focused team
   </strong>
   &nbsp;with strong peer support.
  </li>
  <li>
   <strong>
    High trust and autonomy
   </strong>
   &mdash;clear goals, freedom in how to reach them.
  </li>
  <li>
   <strong>
    Internal product impact
   </strong>
   : meaningful projects that improve developer and user experience, not endless maintenance tickets.
  </li>
  <li>
   <strong>
    Short approval cycles
   </strong>
   &nbsp;and solid product partnership.
  </li>
  <li>
   A&nbsp;
   <strong>
    healthy meeting policy&nbsp;
   </strong>
   and emphasis on protecting focus time.
  </li>
  <li>
   <strong>
    Flexible hours
   </strong>
   , remote/home office options, and a calm, engineers-only office when on-site.
  </li>
  <li>
   <strong>
    Competitive compensation
   </strong>
   , including&nbsp;stock options.
  </li>
 </ul>
 &nbsp;
 <p>
  We&rsquo;re hiring across
  <strong>
   multiple levels
  </strong>
  . Title, scope, and compensation depend on experience&mdash;from strong applied ML generalists to senior people who can lead modeling direction and mentor others.
 </p>
 <p>
  We&rsquo;re especially interested in candidates who are&nbsp;
  <strong>
   technically strong, intellectually curious, and motivated by difficult, ambiguous problems
  </strong>
  &nbsp;where good data science and solid engineering both matter.
 </p>
 <p>
  &nbsp;
 </p>
 <p>
  &nbsp;
 </p>
 <p>
  <strong>
   PEOPLE &amp; CULTURE AT ZETA
  </strong>
 </p>
 <p>
  Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual&rsquo;s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.&nbsp;&nbsp;
 </p>
 <p>
  We&rsquo;re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:&nbsp; https://zetaglobal.com/blog/a-look-into-zetas-ergs/&nbsp;
 </p>
 <p>
  <strong>
   ZETA IN THE NEWS!
  </strong>
 </p>
 <p>
  https://zetaglobal.com/press/?cat=press-releases&nbsp;
 </p>
 <p>
  &nbsp;
 </p>
 <p>
 </p>
 <span>
 </span>
</div>


ML Ops Engineer

RoboService

<div>
 <p>
  <strong>
   Company Description
  </strong>
 </p>
 <p>
  RoboService solves the "Last Mile" of humanoid robotics. While manufacturers provide the hardware and foundation models, these general-purpose "brains" are not yet ready for the specific, accurate tasks of a production line. We bridge that gap.
 </p>
 <p>
  <br/>
 </p>
 <p>
  We don't build foundation models from scratch; we operationalize them. We take state-of-the-art VLA models and fine-tune them for reliability, speed, and precision in real-world manufacturing environments.
 </p>
 <p>
  <br/>
 </p>
 <p>
  We are not a research lab; we are shipping code that moves atoms. Launched in July 2025 by repeat founders with successful exits, we are looking for engineers who want to take robots out of the lab and onto the factory floor.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Role Description
  </strong>
 </p>
 <p>
  We are looking for an intern / working student who joins our Robotics Machine Learning Engineering team. You will bridge the gap between "remote controlled hardware" and "autonomous robots". We work with robotics manufacturers that provide great hardware and a model infrastructure, but are missing the software to fine-tune the models on a specific task. Your primary focus will be establishing training pipelines - from teleoperation data collection to fine-tuning VLA models and utilizing Reinforcement Learning (RL) to fine-tune complex manipulation tasks.
 </p>
 <p>
  <br/>
 </p>
 <p>
  You won't be writing papers. You will be:
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   Building
   <strong>
    data pipelines
   </strong>
   to capture and analyze training data
  </li>
  <li>
   Fine-tuning
   <strong>
    VLA models
   </strong>
   (open source and proprietary models from our partners)
  </li>
  <li>
   Managing the
   <strong>
    Data Pipeline
   </strong>
   and overseeing the
   <strong>
    Teleoperation
   </strong>
   activities. Manage large datasets required for fine-tuning models.
  </li>
  <li>
   <strong>
    Reinforcement Learning
   </strong>
   (RL): Apply RL techniques to fine-tune robot actions, ensuring robust performance when the robot works on the production line.
  </li>
  <li>
   Utilize high-fidelity simulation environments (
   <strong>
    MuJoCo
   </strong>
   ,
   <strong>
    NVIDIA Isaac Sim, Omniverse
   </strong>
   ) to train and test agents before deploying them to physical hardware. (Sim2Real)
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Qualifications
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    Education
   </strong>
   : Currently pursuing your Master&rsquo;s degree or PhD in Robotics, Computer Science, Data Science, Artificial Intelligence, or a related field.
  </li>
  <li>
   <strong>
    Experience
   </strong>
   : Machine Learning, Deep learning, or embodied AI. Hands-On Robotics Experience.
  </li>
  <li>
   <strong>
    Core ML Skills
   </strong>
   : Strong proficiency in Python and deep learning frameworks (PyTorch, TensorFlow, or JAX). Experience with Transformers and VLA architectures is highly desirable.
  </li>
  <li>
   <strong>
    Simulation
   </strong>
   : Proven experience with physics-based simulators, specifically NVIDIA Isaac Sim or similar (Gazebo, MuJoCo).
  </li>
  <li>
   <strong>
    Data Engineering:
   </strong>
   Ability to analyze and manage large datasets, automate data cleaning, and build training pipelines.
  </li>
  <li>
   Proficiency in
   <strong>
    English
   </strong>
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What We Offer
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   <strong>
    Path to Full-Time
   </strong>
   : After a successful internship, we aim to extend a full-time offer.
  </li>
  <li>
   <strong>
    Berlin based
   </strong>
   : We&rsquo;re an in-person team and we work out of our office in downtown Berlin. If you're not in Berlin yet, be prepared to move here before the start of the job.
  </li>
  <li>
   <strong>
    Access to Cutting Edge Tech
   </strong>
   : Work daily on the latest software and hardware that will shape our future.
  </li>
  <li>
   <strong>
    Impact
   </strong>
   : Work in real projects with manufacturers to bring robots onto manufacturing floors.
  </li>
  <li>
   <strong>
    Startup Environment
   </strong>
   : We are a fast-moving startup with high growth ambitions.
  </li>
  <li>
   <strong>
    Team of Experts
   </strong>
   : We are a team of experts where every voice matters. Work with professionals that are leading their field.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Apply now!
  </strong>
 </p>
</div>


Internship - Data Science & Robotics Machine Learning

Deutsche Kreditbank AG

<div><div><div><div>Senior Data Scientist - Lending &amp; ML (m/w/d)</div>
</div></div><div><div><div><div>DKB AG</div>
<div>Standort: Berlin</div>
<div>unbefristet</div>
<div>Teilzeit/Vollzeit</div>
<div>ab sofort</div></div><br>
<p></p>
<div><div><div><div><h2 class="jobSectionHeader"><b>
Dein Profil</b></h2>
</div><div><ul><li>Ein abgeschlossenes Studium der Mathematik, Physik, (Wirtschafts-)Informatik oder eines anderen quantitativen Studiengangs</li>
</ul><ul><li>Fundierte Python-Kenntnisse mit mind. 3 Jahren praktischer Erfahrung</li>
</ul><ul><li>Erfahrung mit Cloud-Diensten, idealerweise AWS, sowie in der Bereitstellung von Machine Learning Services im Unternehmenskontext</li>
</ul><ul><li>Tiefes Verst&auml;ndnis statistischer Lernverfahren und moderner Machine-Learning-Algorithmen</li>
</ul><ul><li>Pr&auml;gnante und strukturierte Ausdrucksweise</li>
</ul><ul><li>Sehr gute Deutsch- und Englischkenntnisse</li>
</ul></div></div><div><div><h2 class="jobSectionHeader"><b>Deine Aufgaben</b></h2>
</div><div><ul><li>Entwicklung leistungsf&auml;higer Services zur Optimierung von Kreditprozessen auf Basis von Machine Learning Methoden (z. B. RandomForest, xgboost, lightGBM)</li>
</ul><ul><li>Partnerschaftliche Zusammenarbeit mit Fachkolleg*innen, um Use Cases zu identifizieren und datengetriebene L&ouml;sungen mit direktem Mehrwert f&uuml;rs Kreditgesch&auml;ft umzusetzen</li>
</ul><ul><li>End-to-End-Verantwortung f&uuml;r die Entwicklung ML-basierter Services vom Proof of Concept bis zum produktiven Betrieb</li>
</ul><ul><li>Sicherstellung von Qualit&auml;t, Nachvollziehbarkeit und Robustheit der Modelle (z. B. Monitoring, Testing, Dokumentation)</li>
</ul><ul><li>Du erweiterst deine Kenntnisse regelm&auml;&szlig;ig und setzt die jeweils besten verf&uuml;gbaren Methoden f&uuml;r die Modellentwicklung ein</li>
</ul><ul><li>In einem schnell wachsenden Team kannst du deine Skills ausbauen, Verantwortung &uuml;bernehmen und deine Ideen aktiv einbringen</li></ul></div></div></div></div><br>
<p></p>
<div>
<p><i>Die DKB steht f&uuml;r Vielfalt und Chancengerechtigkeit. Egal, woher du kommst, wie alt du bist, welches Geschlecht, welche Genderidentit&auml;t, sexuelle Orientierung oder Religion du hast, ob mit oder ohne Behinderung - wir freuen uns auf deine Bewerbung!</i></p>
</div>
</div></div><div><div><div>Deine Benefits und mehr</div>
<div></div><div><ul><li><div>Attraktive Verg&uuml;tung<br>
(tariflich oder<br>
au&szlig;ertariflich)</div>
</li><div></div><li><div>Flexibles und mobiles<br>
Arbeiten &ndash; tempor&auml;r auch<br>
im EU-Ausland</div>
</li><div></div><li><div>Du hast die Wahl:
<br>
Benefits Pass, Jobticket<br>
oder Jobrad</div>
</li><div></div><li><div>Moderne Technik-<br>
ausstattung und Tool<br>
Stack</div>
</li><div></div><li><div>Individuelle Qualifi-<br>
zierungsm&ouml;glichkeiten</div>
</li><div></div><li><div>Duz-Kultur und kein<br>
Dresscode</div>
</li><div></div><li><div>Externe<br>
Mitarbeitenden-<br>
beratung</div>
</li><div></div><li><div>Angebote zum<br>
Gesundbleiben</div>
</li><div></div><li><div>Weitere Extras wie z.B.<br>
betriebliche Altersvorsorge<br>
und Versicherungsschutz</div>
</li></ul></div></div></div><div></div><div><div><div><div><div><div>Immer f&uuml;r dich ansprechbar</div>
<div>Oleg Chapaykin<br>
Expertise Lead<br>
oleg.chapaykin@dkb.de<br>
Deutsche Kreditbank AG</div></div></div></div></div></div></div><p></p>

Senior Data Scientist - Lending & ML (m/w/d)

SmartBroker

<div><h4 class="jobSectionHeader"><b>Your mission</b></h4><p>
For our significantly growing Data, AI &amp; MarketingTech Department, we are looking for several AI Engineers. Our new data team is established to focus on GenAI use case development for client facing product features as well as for increasing efficiencies of internal processes among other data related topics.<br>
As AI Engineer you are playing a pivotal role in Smartbroker&rsquo;s data &amp; AI journey. You will work at the core of GenAI implementation at the intersection of business, data, and technology, drive innovation and data &amp; AI adoption throughout the organization. Our GenAI use cases are focused on generating significant business value through the usage of most modern AI technologies.<br>
<br>
<b>Job Description</b></p><br>
<ul><li>
Design and develop AI use cases for internal processes or client facing product features using up to date GenAI technologies based on LLMs &amp; RAG</li><li>
Develop and maintain the technical AI and machine learning infrastructure for deploying AI-enabled solutions in the cloud</li><li>
Build AI and data features in close collaboration with product engineering teams</li><li>
Implement end-to-end efficient data and AI pipelines according to our data consumers&lsquo; needs up to consumable data &amp; AI products</li><li>
Own the technical implementation and components of your team as well as their operation and maintenance</li><li>
Act as a consultant for other technical teams with regards to usage of GenAI models, tools, and agents</li></ul><p></p><h4 class="jobSectionHeader"><b>
Your profile</b></h4><p></p><ul><li>
University degree in a technical field: computer science, business informatics, natural sciences, or similar</li><li>
Expert knowledge on state-of-the-art AI use cases, agentic applications and best practices</li><li>
Expert knowledge in machine learning, generative AI, LLMs &amp; RAG, AI agents and related technical tools (OpenAI, LangChain , Langfuse &hellip;)</li><li>
Very good python &amp; SQL programming skills, Java is a plus</li><li>
Deep technical knowledge of modern cloud based AI platforms (GCP/AWS)</li><li>
Deep knowledge of software engineering best practices&mdash;from requirements specification, version control, CI/CD, and testing to deployment and monitoring of data pipelines and services</li><li>
Familiarity with data &amp; AI security, data regulations, data privacy requirements</li><li>
Proactive, solution-oriented mindset, strong sense of ownership</li><li>
Strong English communication and presentation skills, German is a plus</li><li>
Interest in finance and fintech industry and a sense of humor</li></ul><p></p><h4 class="jobSectionHeader"><b>
About us</b></h4><p>
Among other things, the Smartbroker Group operates Smartbroker+ - a multi-award-winning online broker that is the only provider in Germany to combine the extensive product range of traditional brokers with the extremely favourable conditions of neobrokers. The portfolio also includes the digital fund broker SMARTBROKER Finance (formerly: FondsDISCOUNT.de), while the Group also operates four high-reach stock market portals (wallstreet-online.de, boersenNews.de, FinanzNachrichten.de and ARIVA.de). With several hundred million monthly page impressions, the Group is the largest independent financial portal operator in the German-speaking world and also maintains the largest financial community.<br>
The company is one of the pioneers of digital investment. For more than 25 years, we have been committed to breaking down the barriers to investing and enabling user-friendly and cost-effective investment processing.<br>
<br>
Our employees are the key to this success. Due to our strong growth momentum, we have created numerous attractive jobs in recent years. Every day, we strive to build the best team and give our employees the space to develop themselves in the best possible way. A diverse team of top performers ensures that we all learn something new every day. From a small team of around 20 people, we have now grown into a company with around 260 employees (as of 31 December 2023), based in a modern office in Berlin-Kreuzberg.<br>
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We see ourselves as an innovative fintech that is embedded in a successful group of companies and thus combines a personal working atmosphere with the advantages of a financially strong public limited company. We rely on flat hierarchies, individual development and agile processes in all parts of the company. We are proud of the personal cohesion within the team and the above-average length of service of many employees. We are committed to diversity and equal opportunities. We strive to build a team that represents a variety of backgrounds, perspectives and skills. The more inclusive we are, the better our work and our team will be.<br>
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If you want to be part of this fast-growing organisation, apply now to join the Smartbroker Group.<br>
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We encourage women, non-binary and transgender people as well as all members of the LGBTQI+ community, people from marginalised ethnic backgrounds and people with visible or non-visible disabilities to apply if they are looking for an inclusive, diverse and safe working environment.</p></div>

AI Engineer (m/f/d)

Billie

<div><p>We are Billie, the leading provider of Buy Now, Pay Later (BNPL) payment methods for businesses, offering B2B companies innovative digital payment services and modern checkout solutions. We are to create a new standard for business payments and have made it our mission to simplify the purchasing experience for all businesses making it a tool for growth. Our solutions are based on proprietary, machine-learning-supported risk models, fully digitized processes and a highly scalable tech platform. This makes us a deep-tech company building financial products, not the other way around. We love building simple and elegant solutions and we strive for automation and scalability.</p><p>
As part of Decision Science, you will work on the models that decide, in milliseconds, whether a transaction is trustworthy. Your work directly shapes how much fraud we stop, how many good customers we approve, and how much risk the business carries.</p><div></div><p><b><br>
About the role:</b></p><p>
As a Fraud Data Scientist, you will be a core technical contributor within Billie's Decision Science group. You will design and build robust, scalable machine learning solutions that prevent fraud, with a direct and measurable impact on Billie's bottom line. You will own the end-to-end modeling lifecycle: defining the analytical approach, testing hypotheses, and deploying models that capture complex debtor behavior and emerging fraud patterns.</p><div></div><p><b><br>
In more detail, you will:</b></p><ul><li><p>
Design and ship anti-fraud models, taking ownership of project priorities and delivering production-ready solutions.</p></li><li><p>
Model debtor behavioral patterns, identify risk factors, and optimize the logic of Billie's real-time decision engine using quantitative analysis, data mining, and advanced ML.</p></li><li><p>
Balance precision and recall under severe class imbalance, explicitly weighing the cost of false positives (customer friction) against missed fraud (financial loss).</p></li><li><p>
Monitor deployed models for drift and adversarial adaptation, and retrain or recalibrate as fraud patterns shift.</p></li><li><p>
Collaborate with data and software engineers, analysts, and product managers to improve decision logic, integrate new data sources, and extend system functionality.</p></li><li><p>
Own the deployment and operationalization of ML services within real-time latency constraints, working with Engineering on infrastructure requirements such as containerization and event-driven architectures.</p></li><li><p>
Share knowledge across the team and contribute to strong experimentation and coding practices.</p></li><li><p>
Turn technical findings into clear, actionable recommendations through effective data storytelling for both technical and non-technical stakeholders.</p></li></ul><p></p><p><b>
What you bring to the team:</b></p><div></div><p><br>
Must have:</p><ul><li><p>
3-5+ years in a quantitative or machine learning role, ideally in fintech or another high-transaction environment. <b>Direct experience in fraud prevention or risk modeling is strongly preferred.</b></p></li><li><p>
Proven advanced proficiency in Python (e.g. pandas, scikit-learn, xgboost) and SQL (Snowflake, Postgres, or MySQL).</p></li><li><p>
Deep expertise in classification models (classical and deep learning), anomaly detection, and graph-based methods (e.g., graph neural networks, entity-link analysis).</p></li><li><p>
Hands-on experience productionizing ML services, with a strong grasp of modern MLOps concepts such as containerization (Docker/Kubernetes) and event-driven architectures.</p></li><li><p>
Proven ability to manage stakeholders across technical and non-technical functions, aligning technical roadmaps with business priorities.</p></li><li><p>
Sharp problem-solving skills, with the ability to translate complex business challenges into clean, efficient, and scalable technical requirements.</p></li><li><p>
Strong communication skills, with a track record of using data to influence strategy and drive cross-functional engagement.</p></li></ul><p></p><p>
Nice to have:</p><ul><li><p>
Experience with ML orchestration frameworks such as Metaflow, Apache Flink, or similar MLOps tooling.</p></li><li><p>
Experience implementing LLM-based workflows (e.g., agentic pipelines, retrieval-augmented generation, or LLM-assisted feature extraction), particularly applied to fraud detection or risk signals.</p></li></ul><p><b>
What We Offer:</b></p><ul><li><p>
Challenging and impactful work that drives personal and professional growth</p></li><li><p>
One of the best Virtual Shares Incentive Programs in the market, so that everyone at Billie is invested in our success</p></li><li><p>
Flexible work hours and trust in your ability to deliver, empowering you to take control of your work-life balance</p></li><li><p>
A hybrid working approach that allows you to work from home for up to 3 days per week</p></li><li><p>
Enjoy 30 days vacation per year, sabbatical opportunities, and extra child sickness leave for parents.</p></li><li><p>
Our &ldquo;Catch a Ride with Billie&rdquo; program that enables discounted access to Berlin Public Transport (BVG), Deutschland-Ticket, OR JobRad</p></li><li><p>
A yearly development budget to broaden your skill set and horizons</p></li><li><p>
Free German group classes</p></li><li><p>
An English-speaking, multicultural team with more than 40 nationalities</p></li><li><p>
Building meaningful connections with your colleagues through company and team events, interest groups, the Billie run club, game nights, and more, powered by our Formula Fun Team!</p></li></ul><p><i>
Billie is an equal opportunity employer and we do not discriminate on the basis of race, color, religion, sexual orientation, gender identity or expression, national origin, age, disability, or any other protected characteristic. We are committed to creating an inclusive environment where everyone feels they belong. All qualified applicants are welcome and we especially encourage you to apply, even if you don't check every box in the job description.</i></p><p>
For information about data processing see our &quot;Recruiting Privacy Policy and further information&quot;: https://www.billie.io/en/candidate-information</p></div>

Fraud Data Scientist

The Formula

<div><p>Deine Benefits:</p><p></p><div><ul><li><p>
Du arbeitest mit modernsten Technologien.</p></li><li><p>
Du wirst Teil eines Teams aus technikbegeisterten Engineers.</p></li><li><p>
Du begleitest das n&auml;chste Tech-Unicorn im Verteidigungssektor bei der Entwicklung eines der ersten multinationalen Drohnen-Fr&uuml;hwarnsysteme.</p></li><li><p>
Dich erwartet ein multinationales, pragmatisches Hands-on-Team mit starkem Innovationsfokus.</p></li><li><p>
Arbeite im B&uuml;ro in Berlin oder M&uuml;nchen &ndash; oder komplett im Homeoffice von &uuml;berall in der EU.</p></li><li><p>
Abgesehen von einigen Meetings arbeitest du dann, wann es f&uuml;r dich am besten passt.</p></li><li><p>
30 Tage Urlaub.</p></li><li><p>
Krankenversicherungspaket.</p></li></ul></div><p></p><div><p>
Deine Aufgaben:</p></div><p></p><div><p>
Du wirst Teil eines 35-k&ouml;pfigen Teams aus technikbegeisterten Sensorik-, IoT- und Hardware-Engineers. Gemeinsam mit deinen Kolleginnen und Kollegen &uuml;bernimmst du folgende Aufgaben:</p></div><p></p><div><ul><li><p>
Du entwickelst ein Ortungsprodukt der n&auml;chsten Generation mit lernender Kartenarchitektur.</p></li><li><p>
Du baust und implementierst visuelle und akustische Sensorsysteme f&uuml;r die Drohnenerkennung.</p></li><li><p>
Du entwickelst ein Multi-Sensor-Wahrnehmungs- und Fusionssystem f&uuml;r das Drohnen-Fr&uuml;hwarnsystem.</p></li><li><p>
Du l&auml;sst Machine-Learning- und KI-Modelle direkt auf den lokalen Sensoren statt auf Cloud-Servern laufen.</p></li><li><p>
Du konzipierst, baust und wartest skalierbare Modelle und bringst die Modell-Inferenz direkt auf die Drohnen-Erkennungsger&auml;te.</p></li><li><p>
Du implementierst skalierbare Intelligenz mit Low-Latency Intelligence.</p></li><li><p>
Gemeinsam mit den ML-, MLOps- und DevOps-Teams erm&ouml;glichst du schnelle und sichere Deployments.</p></li><li><p>
Du &uuml;berwachst die Systeme, behebst St&ouml;rungen und verbesserst kontinuierlich die Observability.</p></li><li><p>
Wenn du m&ouml;chtest, unterst&uuml;tzt du Eins&auml;tze vor Ort, sammelst Sensordaten und validierst die Technologie in kontrollierten Feldversuchen.</p></li></ul></div><p></p><div><p>
Dein Profil:</p></div><p></p><div><ul><li><p>
Aufgrund von Sicherheitsbestimmungen f&uuml;r diese Rolle ist die Staatsb&uuml;rgerschaft eines EU-Mitgliedstaates Voraussetzung.</p></li><li><p>
Du bist offiziell in einem EU-Land gemeldet.</p></li><li><p>
Mindestens 5 Jahre Berufserfahrung im IT-Bereich (z. B. Engineering).</p></li><li><p>
Mindestens 2 Jahre Vollzeit-Berufserfahrung als <b>Fusion Engineer</b>, idealerweise im Bereich Akustik.</p></li><li><p>
Mindestens 2 Jahre Berufserfahrung im <b>IoT</b>-Bereich.</p></li><li><p>
Flie&szlig;ende Kenntnisse in Python und den relevanten Frameworks.</p></li><li><p>
Gute Erfahrung mit dem <b>Embedded-Linux</b>-&Ouml;kosystem.</p></li><li><p>
Erste Cloud-Erfahrung.</p></li><li><p>
Du hast mindestens 2 Jahre am St&uuml;ck f&uuml;r denselben Arbeitgeber gearbeitet.</p></li><li><p>
Flie&szlig;endes Englisch; jede weitere gesprochene Sprache ist ein Plus.</p></li><li><p>
Du arbeitest gerne im Verteidigungssektor (Defense).</p></li><li><p>
Du bl&uuml;hst in einem dynamischen Startup- bzw. Scaleup-Umfeld auf.</p></li><li><p>
Du bist motiviert, f&uuml;r die n&auml;chsten 3-5 Jahre ausschlie&szlig;lich operativ und hands-on (nicht im Management) zu arbeiten.</p></li><li><p>
Idealerweise Erfahrung mit Flottendaten (Fleet Data), Bash, Golang, C/C++, MLOps, DevOps.</p></li><li><p>
Idealerweise hast du Lust, f&uuml;r 2&ndash;3 Tage pro Quartal zu den Feldversuchen zu reisen.</p></li><li><p>
Du bist mit folgenden Buzzwords vertraut: #sensorfusion #multisensorperception #kalmanfiltering #extendedkalmanfilter #ekf #stateestimation #acoussticsignalprocessing #edgeAI #tinyML #computervision #objectdetectionandtracking #lowlatencyarchitecture</p></li></ul></div><p></p><div><p>
Bei Interesse bewirb dich bitte ausschlie&szlig;lich direkt &uuml;ber unsere Homepage mit deinem aktuellen Lebenslauf sowie den Links zu deinem LinkedIn- und GitHub-Profil.</p></div><div><p>
Bei Fragen kannst du dich jederzeit gerne per E-Mail (nathalie@the-formula.de) oder per WhatsApp (+4915733914408) bei uns melden.</p></div><p></p><div><p><b>
Wir feiern Vielfalt.</b></p><p>
Deshalb begr&uuml;&szlig;en wir ausdr&uuml;cklich alle Bewerbungen &ndash; unabh&auml;ngig von Geschlecht, geschlechtlicher Identit&auml;t oder Ausdruck, sexueller Orientierung, Alter, ethnischer oder sozialer Herkunft, Religion oder Weltanschauung, k&ouml;rperlichen F&auml;higkeiten, Familienstand, &auml;u&szlig;erem Erscheinungsbild oder jeder anderen Eigenschaft, die nach geltendem Recht kein Auswahlkriterium sein darf. Wir sind fest davon &uuml;berzeugt, dass vielf&auml;ltige Perspektiven, Erfahrungen und Lebenswege Teams bereichern und zu besseren Entscheidungen f&uuml;hren.</p></div></div><p></p>

Sensor Fusion Engineer (d/m/w) Acoustic & Computer Vision Deutschland remote

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