Machine Learning Engineer

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, WB)Vector databases (Pinecone, Chroma Db)Originally posted on Himalayas

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