We're Hiring: Machine Learning Engineer (2-4 Years Experience)

We Are:

NoGood is a leading growth, performance, and creator marketing agency at the intersection of performance science and creative storytelling. We empower impactful brands to achieve sustainable growth through innovative strategies, cutting-edge analytics, and creative experimentation. Our dynamic team combines top-tier talent, technology, and proprietary AI-driven solutions to deliver unparalleled marketing results for industry-leading brands.

Description:

We’re looking for a highly motivated Machine Learning Engineer with 2–4 years of hands-on experience in ML/AI application development. This role is perfect for early-career professionals who thrive in a fast-paced, innovation-driven environment and want to work on real-world applications of machine learning and generative AI.

You Have:

• End-to-End ML Pipeline Development: Design, implement, and maintain scalable ML pipelines — from data preprocessing to model training and deployment.
• LLM Integration: Collaborate on fine-tuning and deploying large language models (LLMs) like GPT, BERT, or open-source alternatives (e.g., LLaMA, Mistral) for NLP-driven applications.
• Data Engineering & Analysis: Work with structured and unstructured data — perform wrangling, cleaning, and feature engineering using tools like Pandas, PySpark, or Dask.
• Model Monitoring & Optimization: Use MLOps tools (e.g., MLflow, Weights & Biases) for experiment tracking, model versioning, and continuous performance monitoring.
• Interactive Visualizations: Develop dashboards and data visualizations using Plotly, Dash, or Streamlit to communicate findings effectively.
• Cloud-native Deployment: Support model deployment using FastAPI or Flask, containerized via Docker, and deployed on cloud platforms (AWS/GCP/Azure).
• Research & Innovation: Stay current with emerging trends in ML and generative AI; evaluate and prototype new models, algorithms, and frameworks.

You Will Do:

• Bachelor’s degree in Computer Science, Machine Learning, Data Science, Engineering, or related field.
• 2–4 years of hands-on experience in ML engineering, data science, or full-stack development involving ML components.
• Proficiency in Python and core ML/data libraries (NumPy, Pandas, Scikit-learn, etc.).
• Working knowledge of TensorFlow, PyTorch for model development.
• Experience with Natural Language Processing and foundational NLP libraries (spaCy, Hugging Face Transformers, NLTK).
• Exposure to modern LLM stacks (e.g., LangChain, LlamaIndex) and prompt engineering.
• Familiarity with version control (Git) and collaborative development practices.
• Experience working with SQL and NoSQL databases.
• [Bonus] Experience with:
• Cloud platforms (AWS , GCP , or Azure )
• CI/CD pipelines and containerization (Docker, Kubernetes)
• Experiment tracking tools (MLflow, W&B)
• Vector databases (Pinecone, Chroma Db)