ai engineer — genai & agentic solutions (m/w/d) amazon web services

ai/ml engineer - fully remote | upto $85/hr

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

founding software engineer (backend, cloud & ai infrastructure)

data scientist

senior data engineer

ai adoption engineer - m/f/d Jobs in Berlin

ai adoption engineer - m/f/d

ai engineer — genai & agentic solutions (m/w/d) amazon web services Jobs in Berlin

ai/ml engineer - fully remote | upto $85/hr Jobs in Berlin

machine learning intern

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

Code Compass 🧭

<div>
 <p>
  🤖 Machine Learning Engineer &ndash; Computer Vision &amp; Generative AI &ndash; 100%
 </p>
 <p>
  <br/>
 </p>
 <p>
  📍 Berlin, Germany | 💰 &euro;50,000 - &euro;70,000 + Benefits | 🌍 Hybrid Working
 </p>
 <p>
  <br/>
 </p>
 <p>
  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.
 </p>
 <p>
  <br/>
 </p>
 <p>
  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.
 </p>
 <p>
  <br/>
 </p>
 <p>
  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.
 </p>
 <p>
  <br/>
 </p>
 <p>
  ⚙️ Tech Stack:
 </p>
 <p>
  Python, PyTorch, TensorFlow, Computer Vision, Generative AI, Diffusion Models, GANs, Image Processing, Machine Learning, Docker, Cloud Platforms, Production ML Systems, Automation, AI Workflows
 </p>
 <p>
  <br/>
 </p>
 <p>
  🚀 About the Role:
 </p>
 <p>
  <br/>
 </p>
 <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>
 <p>
  <br/>
 </p>
 <p>
  ➕ Nice to Have:
 </p>
 <p>
  <br/>
 </p>
 <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>
 <p>
  <br/>
 </p>
 <p>
  💪 Benefits:
 </p>
 <p>
  <br/>
 </p>
 <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>
 <p>
  <br/>
 </p>
 <p>
  <em>
   ✉️ 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.
  </em>
 </p>
</div>


Machine Learning Engineer

Mercor

<div>
 <strong>
  About The Job
  <br/>
  <br/>
 </strong>
 <strong>
  Mercor
 </strong>
 connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include
 <strong>
  Benchmark
 </strong>
 ,
 <strong>
  General Catalyst
 </strong>
 ,
 <strong>
  Peter Thiel
 </strong>
 ,
 <strong>
  Adam D'Angelo
 </strong>
 ,
 <strong>
  Larry Summers
 </strong>
 , and
 <strong>
  Jack Dorsey
 </strong>
 .
 <br/>
 <br/>
 <strong>
  Position:
 </strong>
 ML Engineer (Coding Agent Experience)
 <br/>
 <br/>
 <strong>
  Type:
 </strong>
 <strong>
  Contract
  <br/>
  <br/>
 </strong>
 <strong>
  Compensation:
 </strong>
 <strong>
  $85/hour
  <br/>
  <br/>
 </strong>
 <strong>
  Location:
 </strong>
 <strong>
  Remote
  <br/>
  <br/>
 </strong>
 <strong>
  Role Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Use frontier AI coding agents to complete and evaluate complex machine learning and AI engineering tasks.
  </li>
  <li>
   Review model-generated implementations involving model training, inference systems, MLOps, and LLM applications.
  </li>
  <li>
   Identify bugs, edge cases, performance issues, and failure modes in AI models.
  </li>
  <li>
   Compare outputs from multiple frontier models and assess their strengths and weaknesses.
  </li>
  <li>
   Apply professional engineering judgment to realistic ML engineering scenarios.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Qualifications
  <br/>
  <br/>
 </strong>
 <strong>
  Must-Have
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   2+ years of professional machine learning engineering experience.
  </li>
  <li>
   Experience building production ML systems, model deployment infrastructure, LLM applications, or AI-powered products.
  </li>
  <li>
   Regular use of AI coding agents such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools.
  </li>
  <li>
   Ability to evaluate model-generated machine learning implementations and technical tradeoffs.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience deploying ML systems to production.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Compensation &amp; Legal
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   $400 per accepted task
  </li>
  <li>
   Compensation is tied to accepted work.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Application Process (Takes 20&ndash;30 mins to complete)
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Upload resume
  </li>
  <li>
   AI interview based on your resume
  </li>
  <li>
   Submit form
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Resources &amp; Support
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  </li>
  <li>
   For any help or support, reach out to: support@mercor.com
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <em>
  PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
 </em>
</div>


AI/ML Engineer - Fully Remote | Upto $85/hr

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

Aleph Alpha

<div>
 Our Mission
 <br/>
 <br/>
 Aleph Alpha is one of the few companies in Europe doing serious foundation model pre- and post-training. We're building models that have general-purpose capabilities, and specifically excel at addressing the needs of our customers.
 <br/>
 <br/>
 We're looking for exceptional Software Engineers to join our model training team. Most of the team is based in Heidelberg .
 <br/>
 <br/>
 Team Culture
 <br/>
 <br/>
 At Aleph Alpha, we foster a culture built on ownership, autonomy, and empowerment. Teams and individual contributors are trusted to take responsibility for their work and drive meaningful impact. We maintain a flat organizational structure with efficient, supportive management that enables quick decision-making, open communication, and a strong sense of shared purpose.
 <br/>
 <br/>
 We believe a strong engineering culture is the key to model training success. We like Extreme Programming and favor trunk-based development. We often mob-program, which keeps us aligned and means we always learn from each other.
 <br/>
 <br/>
 <strong>
  About The Role
  <br/>
  <br/>
 </strong>
 As a Software Engineer in Model Training, you'll work across our full stack. Some weeks you might be optimizing how training loads are scheduled on our cluster and making the pipeline more robust and performant so we can iterate faster. Other weeks, you'll be enabling large-scale code execution for reinforcement learning. And at other times, you might dig deep into our evaluation codebase to lift inference throughput on evals.
 <br/>
 <br/>
 No two days are the same. Things move fast, and your ability to focus and prioritize is what lets you unblock the team day-to-day while designing the high-quality tooling and infrastructure that speeds us up long-term.
 <br/>
 <br/>
 We're still building out our training pipeline and infrastructure. Some pieces exist, some don't, and you'll have real influence on what gets built and how. Your work directly shapes how quickly we can experiment and improve our models.
 <br/>
 <br/>
 <strong>
  Your Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Co-own the training pipeline end-to-end. Design, build, and maintain the infrastructure and components that let us iterate fast on experiments.
  </li>
  <li>
   Build high-quality tooling. Model training is a continuous effort, and we deliberately invest in our tooling and infrastructure to stay successful long term.
  </li>
  <li>
   Collaborate across disciplines. We believe in cross-functional teams. Engineers and researchers work closely so we can learn from each other and iterate faster together.
  </li>
  <li>
   Champion good engineering practices. Working incrementally, maintaining fast feedback loops, and refactoring continuously keep a team successful long-term, especially when moving fast.
  </li>
  <li>
   Shape the direction of the team. Our culture empowers individuals to take ownership. If you see that we'll need more GPUs, a different storage system, or a change to how the team is set up, you should drive this change.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Your profile
  <br/>
  <br/>
 </strong>
 In the model training team, we hire slowly and deliberately. We recognise that we need top talent to deliver the best models, and we value ability over experience: if you think you would be a good fit for this role and training an LLM in Europe excites you, we want to hear from you.
 <br/>
 <br/>
 <strong>
  Requirements
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   A track record of taking initiative to deliver high-impact work.
  </li>
  <li>
   Experience contributing in high-performing teams.
  </li>
  <li>
   Degree in computer science, engineering, or a related field.
  </li>
  <li>
   Willingness to relocate to Germany. Our primary working locations are Heidelberg (preferred) and Berlin, although there is some flexibility to work from other locations in Germany with regular travel to Heidelberg (potentially weekly).
  </li>
  <li>
   Ability to write software that other strong engineers want to read and build on.
  </li>
  <li>
   Desire to take ownership of problems and collaborate with other teams to solve them.
  </li>
  <li>
   Deep interest in how state-of-the-art foundation models work.
  </li>
  <li>
   Strong communication skills, with the ability to convey technical solutions to diverse audiences.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Nice-to-haves
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience working with distributed systems.
  </li>
  <li>
   Experience working with Kubernetes.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  About
  <br/>
  <br/>
 </strong>
 We do not require prior experience in machine learning for this role, but we do value your eagerness to learn. If you have prior experience in ML, we will be particularly excited about:
 <br/>
 <br/>
 <ul>
  <li>
   Experience bringing AI research innovations into production.
  </li>
  <li>
   Experience in areas such as large-scale data processing or distributed computation for foundation model training or inference.
  </li>
  <li>
   Experience with performance engineering: profiling, benchmarking, and optimizing code for throughput, latency, or memory.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Compensation And Benefits
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Become part of an AI revolution!
  </li>
  <li>
   30 days of paid vacation
  </li>
  <li>
   Access to a variety of fitness &amp; wellness offerings via Wellhub
  </li>
  <li>
   Mental health support through nilo.health
  </li>
  <li>
   Substantially subsidized company pension plan for your future security
  </li>
  <li>
   Subsidized Germany-wide transportation ticket
  </li>
  <li>
   Budget for additional technical equipment
  </li>
  <li>
   Flexible working hours for better work-life balance and hybrid working model
  </li>
  <li>
   Virtual Stock Option Plan
  </li>
  <li>
   JobRad&reg; Bike Lease
  </li>
 </ul>
</div>


Senior AI Software Engineer – Model Training (f/m/d)

JetBrains

<div>
 At JetBrains, code is our passion. Ever since we started, back in 2000, we have strived to make the most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.
 <br/>
 <br/>
 The JetBrains Research team explores ways to use machine learning techniques and agentic approaches to help developers and enhance software development processes. Our work aims to improve the state of ML for code by turning the latest academic advances into practical applications.
 <br/>
 <br/>
 Our team is looking for an ML Engineer to participate in a variety of projects in areas such as code completion and generation, AI agents development, and test generation. Though we don&rsquo;t expect the candidate to have experience in all the tasks we work on, we are looking for someone excited to take on the challenge of working in a diverse set of contexts.
 <br/>
 <br/>
 <strong>
  In This Role, You Will
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design and prototype machine learning solutions to improve the software development workflow.
  </li>
  <li>
   Apply existing open-source models or train custom ones as needed.
  </li>
  <li>
   Build training and evaluation pipelines that support fast iteration and ensure reproducibility.
  </li>
  <li>
   Stay up to date with the latest advancements in applying machine learning to source code.
  </li>
  <li>
   Collaborate with colleagues and provide mentorship when appropriate.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  We&rsquo;ll be happy to have you on our team if you:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Have experience designing machine learning systems from scratch.
  </li>
  <li>
   Have a background in natural language processing or code modeling.
  </li>
  <li>
   Have a proven track record of delivering machine learning projects.
  </li>
  <li>
   Know how to design reproducible ML experiments.
  </li>
  <li>
   Enjoy working on projects with high uncertainty.
  </li>
  <li>
   Are proficient in Python, Java, or Kotlin.
  </li>
  <li>
   Have hands-on experience with modern ML frameworks.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  It Would Be Nice If You
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Have experience applying machine learning to programming languages.
  </li>
  <li>
   Have hands-on experience building and improving AI agents.
  </li>
  <li>
   Have experience in A/B testing and general knowledge of statistics
  </li>
  <li>
   Have worked with large-scale data processing pipelines
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  We are an equal opportunity employer
  <br/>
  <br/>
 </strong>
 We know great ideas can come from anyone, anywhere. That&rsquo;s why we do our best to create an open and inclusive workplace &ndash; one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.
 <br/>
 <br/>
 <em>
  We process the data provided in your job application in accordance with the Recruitment Privacy Policy.
  <br/>
  <br/>
 </em>
</div>


Senior ML Engineer (JetBrains Research)

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)

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