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Gazelle Global

Machine Learning Engineer

Gazelle Global
Germany · Full-time · Mid-Senior

Role : Senior AI/MLOPs Engineer (Lead)


Main Skills : Model Lifecylcle Mgmt, MLOPs, Feature Engineering, DevOPs Automation (IaC Tools like Terraform, Cloud Formation), Python, PySpark, AWS SageMaker, SQL, No SQL

Type : Permanent


Programming Expertise:

  • Strong proficiency in Python, with experience in frameworks like PySpark, Pandas, and NumPy.
  • Skilled in developing RESTful APIs using Python frameworks such as FastAPI, Flask, or Django.


Machine Learning and AI:

  • 5–8 years of hands-on experience in AI/ML, including designing, training, and deploying models.
  • Proficient with ML frameworks such as TensorFlow, PyTorch, Keras, or Scikit-learn.
  • Strong knowledge of machine learning and neural network architectures, including Ensemble Models, SVM, CNN, RNN, and Transformers.


NLP and Generative AI:

  • Expertise in Natural Language Processing tools like NLTK, SpaCy, Hugging Face, and Gensim.
  • Proven experience in implementing Text Analytics, Generative AI models, and NLP solutions.


MLOps and Infrastructure:

  • Hands-on experience with AWS (required), particularly SageMaker for model training, deployment, and lifecycle management.
  • Proficiency in cloud platforms like AWS, Azure, or GCP, with a focus on scalable and automated MLOps pipelines.
  • Experience with MLOps tools such as MLflow, SageMaker Pipelines, Airflow, or Kubeflow.
  • Knowledge of microservices architecture and containerization technologies like Docker and Kubernetes.


5Feature Engineering and Data Management:

  • Expertise in data preprocessing, feature extraction, and transformation for machine learning pipelines.
  • Strong SQL and NoSQL database experience, including MongoDB, PostgreSQL, or Neo4j.


DevOps Automation:

  • Skilled in automating workflows for ML model deployment and lifecycle management.
  • Knowledge of Infrastructure-as-Code (IaC) tools like Terraform or CloudFormation.
  • Experience with CI/CD pipelines for deploying ML models in production.


Soft Skills:

• Strong problem-solving abilities with a proactive and collaborative mindset.

• Excellent communication skills to work effectively with cross-functional teams.

• Bachelor’s or higher degree in Computer Science, Information Technology, Data Science, or a related field.

Key Skills

Ranked by relevance

python mlops aws machine learning terraform cloud sql natural language processing containerization microservices restful apis postgresql tensorflow fastapi pytorch docker devops pandas mlflow nosql flask keras cicd gcp ai
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Posted
Jan 24, 2025
Type
Full-time
Level
Mid-Senior
Location
Germany

Industries

Staffing Recruiting IT Services IT Consulting

Categories

Information Technology

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