Machine Learning Engineer

NoGood

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Ready to join one of the fastest-growing agencies in the growth space doing real innovation? You've arrived at the right place! This Software Engineering position is with NoGood's sister company, Goodie AI. Read on to learn more.About Goodie AI:Goodie AI is the pioneering LLM visibility and AI search optimization platform enabling the world’s top brands to own their AI narrative across leading LLMs like ChatGPT, Gemini and Perplexity. Backed by strong funding and validated by active paying customers, we are scaling fast and tackling some of the hardest AI search challenges.We are looking for an exceptional Senior Software Engineer to join our rapidly growing team. You will play a critical role in driving and accelerating the development of cutting-edge AI use cases, working closely with our Product Lead, Designers, and Machine Learning Engineers to design and build scalable, industry-leading AI platforms.After you apply, check out to learn even more!Why join us:

Shape the future of AI search and brand discovery—work at the cutting edge of Answer Engine Optimization (AEO).
End-to-end ownership—drive scalability, speed, and user experience of our AI-Native platform.
Work on high-impact AI applications used by top brands.
Well-funded, fast-growing AI startup with a strong product-market fit.

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)

BEWARE OF FRAUD! Please be aware of potentially fraudulent job postings or suspicious activity by persons that are posing as NoGood team members, recruiters, and HR employees. Our team will contact you regarding job opportunities from email addresses ending in @nogood.io or @higoodie.com. Additionally, we do utilize our ATS- Workable- to help us schedule initial screening calls. Job seeking is hard- we’re sorry that scammers have added this element to your search for something new. Stay vigilant out there!

NoGood