Machine Learning Engineer
Responsibilities
- Designing, training, and evaluating machine learning models (supervised, unsupervised, NLP, etc.).
- Building scalable data and ML pipelines using modern tools.
- Collaborating with subject matter experts and analysts to prepare training datasets.
- Deploying models for production (batch or real-time inference).
- Monitoring and maintaining model performance and data quality.
- Optimizing models for performance, interpretability, and cost.
- Documenting ML workflows and ensuring reproducibility.
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Must have requirements
- Experience as a Machine Learning Engineer or in a similar role for 2+ years.
- Proficiency in Python, including hands-on experience with libraries such as scikit-learn, pandas, NumPy, and matplotlib.
- Strong understanding of core ML concepts – regression, classification, clustering, model validation, and performance metrics.
- Practical experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras.
- Proven experience building, training, and deploying ML models using AWS SageMaker.
- Familiarity with AWS Bedrock for working with foundation and generative models (e.g., fine-tuning and orchestration of LLMs).
- Hands-on experience with data preprocessing, feature engineering, and model evaluation.
- Knowledge of SQL and experience working with structured and semi-structured datasets.
- Understanding of ML model deployment (e.g., REST APIs with FastAPI or Flask; model packaging and containerization with Docker).
- Exposure to MLOps practices – pipeline automation, model versioning, monitoring, and reproducibility.
- Familiarity with version control systems (e.g., Git).
- Strong analytical thinking, communication, and problem-solving skills.
- Willingness to stay current with emerging ML techniques, frameworks, and cloud AI tools.
- Level of English – from Upper-Intermediate and above.
- Level of German – from Intermediate+ and above.
Location: Remote - Anywhere
Skills required for this job:
- Docker
- Git
- Machine learning
- NumPy
- Python
- SQL
Skills
- AI
- API
- Automation
- AWS
- AWS Bedrock
- Cloud
- Containerization
- Data Quality
- Deep Learning
- Docker
- FastAPI
- Feature Engineering
- Fine Tuning
- Flask
- Git
- Keras
- LLM
- Machine Learning
- Matplotlib
- MLOps
- Model Deployment
- Model Evaluation
- NLP
- NumPy
- pandas
- Python
- PyTorch
- REST
- SageMaker
- scikit-learn
- SQL
- TensorFlow
- Version Control