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

analytics engineer

ai ml engineer fully remote upto 85 hr

Mercor

<div>
 
 About The Job
 
 
 
 
 Mercor
 
 connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include
 
 Benchmark
 
 ,
 
 General Catalyst
 
 ,
 
 Peter Thiel
 
 ,
 
 Adam D'Angelo
 
 ,
 
 Larry Summers
 
 , and
 
 Jack Dorsey
 
 .
 
 
 
 Position:
 
 ML Engineer (Coding Agent Experience)
 
 
 
 Type:
 
 
 Contract
 
 
 
 
 Compensation:
 
 
 $85/hour
 
 
 
 
 Location:
 
 
 Remote
 
 
 
 
 Role Responsibilities
 
 
 
 <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.
 
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 Must-Have
 
 
 
 <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.
 
 
 
 </li>
 </ul>
 
 Preferred
 
 
 
 <ul>
 <li>
 Experience deploying ML systems to production.
 
 
 
 </li>
 </ul>
 
 Compensation &amp; Legal
 
 
 
 <ul>
 <li>
 $400 per accepted task
 </li>
 <li>
 Compensation is tied to accepted work.
 
 
 
 </li>
 </ul>
 
 Application Process (Takes 20&ndash;30 mins to complete)
 
 
 
 <ul>
 <li>
 Upload resume
 </li>
 <li>
 AI interview based on your resume
 </li>
 <li>
 Submit form
 
 
 
 </li>
 </ul>
 
 Resources &amp; Support
 
 
 
 <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
 
 
 
 </li>
 </ul>
 
 PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
 
</div>

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

Zeta Global

<div>WHO WE ARE

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. 


The Role

We&rsquo;re looking for a skilled ML Engineer / Data Scientist with 3+ years of software or applied ML experience to design, build, and improve machine learning solutions in a dynamic cloud environment, primarily on AWS.This role sits at the intersection of data science and engineering: 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. 

<div>
Who you are:
<ul>
<li>Strong foundation in machine learning, statistics and experiment design.</li>
<li>Experience building models for real business or product problems, not only academic benchmarks.</li>
<li>Comfortable working with structured and unstructured data: feature engineering, dataset construction, labeling quality, leakage checks, and train/validation/test discipline.</li>
<li>Able to compare approaches with clear metrics, error analysis, and sound judgment about tradeoffs (accuracy, latency, cost, maintainability).</li>
<li>Interest in modern ML, including classical ML, deep learning, and LLM / GenAI workflows where relevant (fine-tuning, RAG, evaluation, prompt/versioning).</li>
<li>Proficient in Python and able to write clean, modular, testable code.</li>
<li>Experience developing and deploying ML solutions in a cloud environment, especially 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 problem framing experimentation implementation rollout.</li>
<li>Excellent written and spoken English.</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>Master&rsquo;s degree in Science or Engineering (Computer Science, Mathematics, Physics, Statistics, or similar), or equivalent practical experience.</li>
</ul>
Nice to have:
<ul>
<li>Experience with scikit-learn, PyTorch, TensorFlow, XGBoost, or similar modeling stacks.</li>
<li>Familiarity with ML experiment tracking and reproducibility (e.g. MLflow, W&amp;B).</li>
<li>Experience with SQL, data warehouses/lakes, and pipeline tools such as Airflow, dbt, or Spark.</li>
<li>Exposure to feature stores, embedding pipelines, or vector search for retrieval-based systems.</li>
<li>Experience building HTTP/gRPC APIs or lightweight services around model inference.</li>
<li>Working knowledge of Docker, basic orchestration, and CI/CD (e.g. GitLab CI).</li>
<li>Experience in agile, remote and async team environments.</li>
<li>Publications, patents, Kaggle/competition results, or open-source ML contributions.</li>
</ul>
What you might like about this role:
<ul>
<li>Hands-on modeling work with room to explore, benchmark, and improve real systems.</li>
<li>Collaboration on ML patent submissions and participation in weekly ML / research paper review meetings.</li>
<li>A multicultural, engineering-focused team with strong peer support.</li>
<li>High trust and autonomy&mdash;clear goals, freedom in how to reach them.</li>
<li>Internal product impact: meaningful projects that improve developer and user experience, not endless maintenance tickets.</li>
<li>Short approval cycles and solid product partnership.</li>
<li>A healthy meeting policy and emphasis on protecting focus time.</li>
<li>Flexible hours, remote/home office options, and a calm, engineers-only office when on-site.</li>
<li>Competitive compensation, including stock options.</li></ul> 
<div>
</div><div></div><div><div>We&rsquo;re hiring across multiple levels. Title, scope, and compensation depend on experience&mdash;from strong applied ML generalists to senior people who can lead modeling direction and mentor others.

We&rsquo;re especially interested in candidates who are technically strong, intellectually curious, and motivated by difficult, ambiguous problems where good data science and solid engineering both matter. 


PEOPLE &amp; CULTURE AT ZETA

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.
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: https://zetaglobal.com/blog/a-look-into-zetas-ergs/

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 


#LI-NP1</div></div></div></div>

ML Ops Engineer

<div>
 
 &nbsp;
 
 
 
 WHO WE ARE&nbsp;
 
 
 
 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.
 
 
 &nbsp;
 
 
 
 The Role
 
 
 
 We&rsquo;re looking for a skilled&nbsp;
 
 ML Engineer / Data Scientist
 
 &nbsp;with&nbsp;
 
 3+ years of software or applied ML experience
 
 &nbsp;to design, build, and improve machine learning solutions in a dynamic cloud environment, primarily on&nbsp;
 
 AWS
 
 .This role sits at the intersection of&nbsp;
 
 data science and engineering
 
 : 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.
 
 
 &nbsp;
 
 
 
 Who you are:
 
 
 <ul>
 <li>
 Strong foundation in&nbsp;
 
 machine learning,&nbsp;statistics
 
 and&nbsp;
 
 experiment design
 
 .
 </li>
 <li>
 Experience building models for&nbsp;
 
 real business or product problems
 
 , not only academic benchmarks.
 </li>
 <li>
 Comfortable working with&nbsp;
 
 structured and unstructured data
 
 : feature engineering, dataset construction, labeling quality, leakage checks, and train/validation/test discipline.
 </li>
 <li>
 Able to compare approaches with clear&nbsp;
 
 metrics
 
 , error analysis, and sound judgment about tradeoffs (accuracy, latency, cost, maintainability).
 </li>
 <li>
 Interest in&nbsp;
 
 modern ML
 
 , including classical ML, deep learning, and&nbsp;
 
 LLM / GenAI workflows
 
 &nbsp;where relevant (fine-tuning, RAG, evaluation, prompt/versioning).
 </li>
 <li>
 Proficient in&nbsp;
 
 Python
 
 &nbsp;and able to write&nbsp;
 
 clean, modular, testable&nbsp;code
 
 .
 </li>
 <li>
 Experience developing and deploying ML solutions in a&nbsp;
 
 cloud environment
 
 , 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;
 
 problem framing &rarr; experimentation &rarr; implementation &rarr; rollout
 
 .
 </li>
 <li>
 Excellent&nbsp;
 
 written and spoken English
 
 .
 </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>
 
 Master&rsquo;s degree
 
 &nbsp;in Science or Engineering (Computer Science, Mathematics, Physics, Statistics, or similar),&nbsp;
 
 or equivalent practical experience
 
 .
 </li>
 </ul>
 
 
 Nice to have:
 
 
 <ul>
 <li>
 Experience with&nbsp;
 
 scikit-learn,&nbsp;PyTorch,&nbsp;TensorFlow,&nbsp;XGBoost
 
 , or similar modeling stacks.
 </li>
 <li>
 Familiarity with&nbsp;
 
 ML experiment tracking
 
 &nbsp;and reproducibility (e.g. MLflow, W&amp;B).
 </li>
 <li>
 Experience with&nbsp;
 
 SQL
 
 , data warehouses/lakes, and pipeline tools such as&nbsp;
 
 Airflow,&nbsp;dbt, or&nbsp;Spark
 
 .
 </li>
 <li>
 Exposure to&nbsp;
 
 feature stores
 
 , embedding pipelines, or&nbsp;
 
 vector search
 
 &nbsp;for retrieval-based systems.
 </li>
 <li>
 Experience building&nbsp;
 
 HTTP/gRPC APIs
 
 &nbsp;or lightweight services around model inference.
 </li>
 <li>
 Working knowledge of&nbsp;
 
 Docker
 
 , basic orchestration, and CI/CD (e.g.&nbsp;
 
 GitLab CI
 
 ).
 </li>
 <li>
 Experience in&nbsp;
 
 agile
 
 ,&nbsp;
 
 remote
 
 and&nbsp;
 
 async
 
 &nbsp;team environments.
 </li>
 <li>
 Publications, patents, Kaggle/competition results, or open-source ML contributions.
 </li>
 </ul>
 
 
 What you might like about this role:
 
 
 <ul>
 <li>
 
 Hands-on modeling work
 
 &nbsp;with room to explore, benchmark, and improve real systems.
 </li>
 <li>
 Collaboration on&nbsp;
 
 ML patent submissions
 
 &nbsp;and participation in&nbsp;weekly ML / research paper review&nbsp;meetings.
 </li>
 <li>
 A&nbsp;
 
 multicultural, engineering-focused team
 
 &nbsp;with strong peer support.
 </li>
 <li>
 
 High trust and autonomy
 
 &mdash;clear goals, freedom in how to reach them.
 </li>
 <li>
 
 Internal product impact
 
 : meaningful projects that improve developer and user experience, not endless maintenance tickets.
 </li>
 <li>
 
 Short approval cycles
 
 &nbsp;and solid product partnership.
 </li>
 <li>
 A&nbsp;
 
 healthy meeting policy&nbsp;
 
 and emphasis on protecting focus time.
 </li>
 <li>
 
 Flexible hours
 
 , remote/home office options, and a calm, engineers-only office when on-site.
 </li>
 <li>
 
 Competitive compensation
 
 , including&nbsp;stock options.
 </li>
 </ul>
 &nbsp;
 
 We&rsquo;re hiring across
 
 multiple levels
 
 . Title, scope, and compensation depend on experience&mdash;from strong applied ML generalists to senior people who can lead modeling direction and mentor others.
 
 
 We&rsquo;re especially interested in candidates who are&nbsp;
 
 technically strong, intellectually curious, and motivated by difficult, ambiguous problems
 
 &nbsp;where good data science and solid engineering both matter.
 
 
 &nbsp;
 
 
 &nbsp;
 
 
 
 PEOPLE &amp; CULTURE AT ZETA
 
 
 
 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;
 
 
 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;
 
 
 
 ZETA IN THE NEWS!
 
 
 
 https://zetaglobal.com/press/?cat=press-releases&nbsp;
 
 
 &nbsp;
 
 
 
 
 
</div>

Code Compass 🧭

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

Machine Learning Engineer

Project Q

<div><h4 class="jobSectionHeader">New Challenge</h4>
Job Advertisement: Software Product Engineer (m/f/d)
Location: Berlin, Munich, Remote (Germany, EU) 
Working Hours: Full-time 
Start Date: Immediately or by arrangement
About Us
Project Q GmbH (&quot;Q&quot;) is a Germany-based DefenceTech company with offices in Berlin and Munich. We network market-available sensors into a tactical IoT backbone that reliably provides armed forces and security agencies with a cross-domain information superiority-automated, scalable, and cost-efficient.
Our solutions integrate seamlessly into existing defence and safety infrastructures, offering fast data fusion and AI-enhanced analytics to deliver robust situational awareness in dynamic environments. We build platform-agnostic systems that enable real interoperability across domains.
As a Software Product Engineer, you'll join a focused, deeply skilled team to help build and extend our European open-core integration infrastructure. This includes Hydris: our integrate once, deploy everywhere, open source orchestration plane. Hydris, and its growing ecosystem of partner integrations, are where heterogeneous real-world systems like radars, AIS receivers, mesh radios, satellite feeds, AI analytics, and C2 platforms become one coherent picture, in conditions that are bandwidth-constrained, intermittently connected, and unforgiving.
What you'll do
This role is broad by design. You'll be trusted to take problems end to end: talk to users, shape what gets built, write the code, ship it, see how it performs, and decide what comes next. Day to day that means core engine work on Hydris in Go and TypeScript, extending it with features that genuinely move the field, and helping grow the ecosystem of certified integrations. It also means collaborating across our tech org and helping build and extend our integrated, software-defined customer solutions. And it means setting technical standards: how we test distributed behavior, how we version protocols, and how we keep an API-first product backward compatible.
Who this is for
You build software systems. You've shipped real products that people rely on, and you can show them to us. You care about building the right thing the right way, and about seeing it through. You want to travel when needed or possible, to be with the user, to understand their needs, and build directly to those. And you do your best work where the decisions are meaningful and the problems are challenging. This is a role that will demand the excellence you challenge others to show in their own work and conduct.
How you work<ul><li>
Self-starting. You don't wait for a perfectly scoped task; your default is to try something and learn from it.</li><li>
Deeply curious. You'll go down the rabbit hole and come back with something the rest of us didn't know we needed.</li><li>
Builder first. You'd often rather have a rough thing in someone's hands this week than a perfect plan for next quarter.</li><li>
Standard-setting. You join a team to raise its bar. People tend to work a little differently because you're in the room.</li></ul>
You should apply if you have<ul><li>
Taken new products from concept to scaling in-market, and lived with the weight of users, edge cases, and keeping it healthy under load.</li><li>
Worked across the full surface: product sense, design instinct, full-stack, deployments, the documentation that empowers other developers, and the long-term maintenance of what you build.</li><li>
Made calls under uncertainty with incomplete information, and owned the outcomes, good and bad.</li><li>
Earned the respect of engineers you respect. The best people you've worked with would take your call.</li><li>
Built a deep, principled, and broadly applicable skill set through substantial work and study.</li><li>
Eligibility to obtain a security clearance.</li><li>
Comfort working confidently in English.</li></ul>
You'd be a great fit with<ul><li>
Experience building secure systems for adversarial or contested environments, including threat modelling, secure-by-design practices, and hardening against real attackers.</li><li>
Experience with geospatial systems, sensor fusion, AI/ML analytics, or track management.</li><li>
Familiarity with defence or ISR data standards like CoT/TAK, ASTERIX, SAPIENT, MIL-STD-2525.</li><li>
Background in networking, mesh architectures, IoT integration, or systems built for contested or degraded communication environments.</li><li>
Experience on developer-facing open-source infrastructure where adoption depends on the quality of the API and documentation.</li><li>
Professional proficiency in German (and extra bonus points for additional European languages).</li></ul>
We Offer<ul><li>
Be a part of our growth story and help build us a leading technology company.</li><li>
A varied and responsible role in a dynamic company.</li><li>
Flat hierarchies and a pleasant working environment.</li><li>
Opportunities for professional and personal development.</li><li>
Flexible working hours and remote work options.</li><li>
Attractive salary and additional benefits.</li></ul>
Have we sparked your interest? Then we look forward to receiving your CV, including your earliest possible start date, at HR [at] project-q.ai. We look forward to meeting you!<h4 class="jobSectionHeader">
About us</h4>
Q is a European defence-tech company pioneering the Internet of Defence with modular, scalable and interoperable sensor and intelligence solutions.</div>

Software Product Engineer (m/f/d)

ALMETRA

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

Platform Engineer (m/f/d) (AI Startup)

Chapter 2

<div>Chapter 2 is partnering exclusively with a leading digital health startup at the forefront of AI-enabled cardiac telemonitoring. Working with institutions including Charit&eacute;, Mayo Clinic, and UCSF, they are building technology that detects early signs of heart failure deterioration and improves patient outcomes at scale.
They are looking for a Full Stack Engineer to join a small, high-ownership team and take end-to-end responsibility for significant product projects across their AI-enabled platform.
The Role
You will work closely with the Product Lead to scope, build, and ship substantial features across the full stack, from physician and patient interfaces on the frontend to APIs, data modelling, and ML integration on the backend. You won't be handed tickets. You'll shape projects from concept through to post-launch iteration, lead a small squad of engineers, and collaborate directly with clinical partners, sales, and founders.
What You'll Need<ul><li>
M.Sc. in a STEM field with 2+ years of full-stack experience, or 4+ years without</li><li>
Strong Python on the backend, TypeScript/React on the frontend</li><li>
A product and user-focused mindset, you care about UX and make design decisions, not just implementation decisions</li><li>
Comfort operating with high autonomy in a small team</li><li>
Fluent English</li></ul>
Nice to Have<ul><li>
Experience with ML/data pipelines, audio/signal processing, or clinical data</li><li>
Background in regulated software (MDR, ISO 13485, IEC 62304) or healthcare products</li><li>
DevOps and cloud infrastructure experience (GCP, CI/CD)</li><li>
German language skills</li></ul>
What's on Offer<ul><li>
Competitive compensation package with meaningful equity</li><li>
A mission that matters, technology with direct impact on patient outcomes</li><li>
A Berlin-Mitte office and a team built from some of the best engineering and clinical minds in digital health</li><li>
Urban Sports Club membership</li></ul>
If you are a full-stack engineer who wants to own real product work in a clinical environment that is genuinely changing how heart disease is managed, we'd like to hear from you.</div>

Full Stack Engineer

Explore 186+ Ai ml engineer fully remote upto 85 hr in Berlin this July. Find roles across top companies and apply now to boost your career.

186 ai ml engineer fully remote upto 85 hr jobs In Berlin

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

ML Ops Engineer

ML Ops Engineer

Machine Learning Engineer

Software Product Engineer (m/f/d)

Platform Engineer (m/f/d) (AI Startup)

Full Stack Engineer