AI Engineer

Jobgether SRL; Deutschland; Remote; EUR 41,000 - 49,000; Full time

Benefits offered by this job

Fully remote work arrangement

International and remote working環境

Job summary

Partner Company in Germany is seeking an AI Engineer for a fully remote role focusing on building production-ready ML systems. The position spans data prep, model development, evaluation, deployment, and MLOps across LLMs, NLP, and computer vision, with independent work in a fast-changing environment.

You will design, deploy, and optimize models, train on large datasets, and communicate insights to non-technical stakeholders while collaborating with distributed teams.

Qualifications

• 2–5 years hands-on experience building and deploying ML/AI models in production.
• Strong proficiency in Python.
• Practical experience with PyTorch and/or TensorFlow.
• Experience designing and architecting custom AI/ML models.
• Hands-on knowledge of LLMs, NLP, CV, or related AI domain.
• Understanding of supervised/unsupervised learning, DL architectures, optimization, evaluation metrics.
• Experience with data preprocessing, feature engineering, data mining, labeling pipelines.
• Familiarity with MLOps and model deployment tools such as MLflow, Kubeflow, or SageMaker.
• Knowledge of cloud platforms for training/serving (e.g., AWS Lambda).
• Experience with Docker, Git, and collaborative software practices.

Responsibilities

• Design, develop, and deploy ML/AI systems for real-world applications at scale.
• Build, customize, optimize, and maintain AI models for domain-specific use cases.
• Develop data pipelines for preprocessing, feature engineering, and labeling.
• Prepare high-quality training/evaluation data from large datasets.
• Apply ML techniques across LLMs, NLP, CV, and other AI domains.
• Train, evaluate, optimize, and improve models based on performance.
• Design and maintain deployment and MLOps pipelines for production environments.
• Deploy and serve models on cloud platforms and containerized environments.
• Use Docker, Git, and MLOps tools in collaborative workflows.
• Analyze model performance, identify limitations, and implement improvements.
• Communicate technical concepts and project progress to non-technical stakeholders.

Skills

Python

PyTorch

TensorFlow

LLMs

NLP

Computer Vision

Docker

MLflow

Kubeflow

SageMaker

Tools

Docker

MLflow

Kubeflow

SageMaker

AWS Lambda

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI Engineer based in Germany.

This is a fully remote opportunity for an AI Engineer focused on building production-ready solutions that address real-world challenges at scale. You will combine strong machine learning fundamentals with hands‑on engineering to design, train, optimize, and deploy AI systems. The role offers exposure to diverse AI domains, including LLMs, NLP, computer vision, and other emerging technologies. You will work across data preparation, model development, evaluation, deployment, and MLOps. Success in this position requires both technical depth and the ability to operate independently in a fast‑changing environment. You will also have the opportunity to translate complex AI concepts into clear insights for non‑technical stakeholders.

Accountabilities:

• Design, develop, and deploy machine learning and AI systems for real-world applications at scale.
• Build, customize, optimize, and maintain AI models for domain‑specific use cases.
• Develop and maintain data mining, preprocessing, feature engineering, and data‑labeling pipelines.
• Work with large datasets to prepare high‑quality training and evaluation data.
• Apply machine learning techniques across areas such as large language models, natural language processing, computer vision, and other AI domains.
• Train, evaluate, optimize, and continuously improve machine learning models based on performance results.
• Design and maintain model deployment and MLOps pipelines to support reliable production environments.
• Deploy and serve models using cloud platforms and containerized environments.
• Use Docker, Git, and relevant MLOps tools as part of collaborative software development workflows.
• Analyze model performance, identify limitations, and implement opportunities for improvement.
• Communicate technical concepts, findings, and project progress clearly to non‑technical stakeholders.

Requirements:

• 2–5 years of hands‑on experience building and deploying machine learning or AI models in production environments.
• Strong proficiency in Python.
• Practical experience with PyTorch and/or TensorFlow.
• Experience designing and architecting custom AI or machine learning models.
• Hands‑on knowledge of LLMs, NLP, computer vision, or another relevant AI domain.
• Strong understanding of supervised and unsupervised learning, deep learning architectures, optimization techniques, and model evaluation metrics.
• Experience with data preprocessing, feature engineering, data mining, and data‑labeling pipelines.
• Familiarity with MLOps and model deployment tools such as MLflow, Kubeflow, or SageMaker.
• Knowledge of cloud platforms and services used for model training and serving, such as AWS Lambda.
• Experience with Docker and containerized model deployment.Familiarity with Git and collaborative software development practices.
• Strong analytical, troubleshooting, and problem‑solving abilities.
• Ability to explain complex technical concepts clearly to non‑technical stakeholders.
• Curiosity‑driven mindset, adaptability, and comfort working in an evolving environment.
• Ability to work independently while collaborating effectively with distributed teams.

Benefits:

• Salary of EUR 4,000.
• Full‑time employment.
• Fully remote work arrangement.
• Opportunity to work on real‑world AI and machine learning applications at scale.
• Exposure to LLMs, NLP, computer vision, MLOps, cloud technologies, and production AI systems.
• Opportunity to work with modern machine learning and software engineering tools and practices.
• International and remote working environment.

How the company works:We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through the company?Data Privacy Notice: By submitting your application, you acknowledge that the company will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre‑contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.