Full-Time Machine Learning Engineer
NoGood is hiring a remote Full-Time Machine Learning Engineer. The career level for this job opening is Entry Level and is accepting Egypt based applicants remotely. Read complete job description before applying.
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We are hiring a Machine Learning Engineer (1–2 Years Experience).
About NoGood: NoGood is a leading growth, performance, and creator marketing agency. We empower impactful brands to achieve sustainable growth.
Role Overview: We are looking for a highly motivated Machine Learning Engineer with 1–2 years of hands-on experience in ML/AI application development. The role involves working on real-world applications of machine learning and generative AI, in a fast-paced, innovation-driven environment.
Responsibilities:
- End-to-End ML Pipeline Development: Design, implement, and maintain scalable ML pipelines.
- LLM Integration: Fine-tune and deploy large language models (LLMs).
- Data Engineering & Analysis: Wrangling, cleaning, and feature engineering using tools like Pandas, PySpark, or Dask.
- Model Monitoring & Optimization: Using MLOps tools for experiment tracking and continuous performance monitoring.
- Interactive Visualizations: Develop dashboards and data visualizations using tools like Plotly, Dash, or Streamlit.
- Cloud-native Deployment: Support model deployment on cloud platforms (AWS/GCP/Azure) using FastAPI or Flask, containerized via Docker.
- Research & Innovation: Stay current with emerging trends in ML and generative AI.
Qualifications:
- Bachelor's degree in Computer Science, Machine Learning, Data Science, Engineering, or related field.
- 1–2 years of hands-on experience in ML engineering, data science, or full-stack development.
- Proficiency in Python and core ML/data libraries.
- Working knowledge of TensorFlow, PyTorch.
- Experience with Natural Language Processing (NLP) libraries (spaCy, Hugging Face Transformers, NLTK).
- Exposure to modern LLM stacks and prompt engineering.
- Familiarity with version control (Git) and collaborative development practices.
- Experience with SQL and NoSQL databases.
- Bonus: Experience with cloud platforms (AWS, GCP, or Azure), CI/CD pipelines, experiment tracking tools, vector databases.