Machine Learning Engineer

Annapurna; Deutschland; Remote; EUR 70.000 - 100.000; Vollzeit

Zusammenfassung

Annapurna is seeking a highly skilled Machine Learning Engineer specializing in MLOps to join their team in Germany. This remote role focuses on building and maintaining robust, scalable ML pipelines that deliver significant business value. The ideal candidate will collaborate with data scientists and software engineers, ensuring a smooth transition of models from experimentation to production. If you have over 5 years of experience in this field and possess a strong software engineering background, we encourage you to apply.

Qualifikationen

• Experience with model deployment and production-grade ML systems.
• Strong software engineering skills (Python, Bash, REST APIs).
• Familiarity with tools like Prometheus, Grafana for monitoring.

Aufgaben

• Design, build, and maintain end-to-end machine learning pipelines.
• Develop CI/CD pipelines for ML model training and deployment.
• Monitor deployed models for performance and operational issues.

Kenntnisse

MLOps

Python

CI/CD

Monitoring

Problem-Solving

Ausbildung

5+ years of experience in machine learning engineering or MLOps roles

Strong software engineering background

Tools

Docker

Kubernetes

MLflow

Triton

Jobbeschreibung

Direct message the job poster from Annapurna

Principal Consultant - Software & Data at Annapurna Recruitment

Machine Learning Engineer - MLOps & Infrastructure Specialist - Germany - Remote

We are looking for a highly skilled Machine Learning Engineers with deep expertise in MLOps, model deployment, and production-grade machine learning systems.

In this role, you'll bridge the gap between data science and engineering to build robust, scalable ML pipelines and infrastructure that deliver real business value.

You will collaborate with data scientists, software engineers, and DevOps to ensure models move smoothly from experimentation to production, operating reliably at scale.

Key Responsibilities

• Design, build, and maintain end-to-end machine learning pipelines, from data ingestion to model deployment and monitoring.
• Develop and manage CI/CD pipelines for ML model training, testing, and deployment (e.g., GitHub Actions, Jenkins).
• Implement model serving and orchestration using tools like MLflow, Kubeflow, Airflow, Docker, Kubernetes, or Triton.
• Integrate feature stores (e.g., Feast, Tecton) to manage and serve features consistently.
• Monitor deployed models for drift, performance degradation, and operational issues using tools like Prometheus, Grafana, Seldon, or Evidently AI.
• Collaborate closely with data engineers and data scientists to ensure data quality and pipeline reliability.
• Optimize model inference performance for latency, throughput, and cost in production environments.
• Maintain documentation, reproducibility, and version control of datasets, models, and pipelines.

Required Qualifications

• 5+ years of experience in machine learning engineering or MLOps roles.
• Strong software engineering background (e.g., Python, Bash, REST APIs, containerization).
• Experience with MLOps tools and practices, including:
• CI/CD: GitHub Actions, GitLab CI/CD, Jenkins
• Model Serving: TensorFlow Serving, TorchServe, Triton
• Monitoring: Prometheus, Grafana, Seldon Core, Evidently AI
• Feature Stores: Feast, Tecton
• Experience deploying models to cloud platforms such as AWS, GCP, or Azure.
• Deep understanding of data pipelines, ETL/ELT processes, and production data systems.
• Strong problem-solving and debugging skills in distributed computing environments.

Nice to Have

• Experience with real-time inference and streaming systems (e.g., Kafka, Spark, Flink).
• Familiarity with model governance, auditability, and responsible AI practices.
• Exposure to large language models (LLMs), vector databases, and retrieval-augmented generation (RAG) pipelines.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Information Technology

• Industries

  Robotics Engineering, Financial Services, and Retail

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