Posted:1 day ago|
Platform:
On-site
Full Time
Responsibilities Build and fine-tune models for NLP, computer vision, predictions, and more. Engineer intelligent pipelines that are used in production. Collaborate across teams to bring AI solutions to life (not just in Jupyter Notebooks). Embrace MLOps with tools like MLflow, Docker, and Kubernetes. Stay on the AI cutting edge and share what you learnmentorship mindset is a big plus. Champion code quality and contribute to a future-focused dev culture. Requirements 3-4 years in hardcore AI/ML or applied data science. Pro-level Python skills (R is cool too, but Python is king here). Mastery over ML frameworks: scikit-learn, XGBoost, LightGBM, TensorFlow/Keras, PyTorch. Hands-on with real-world data wrangling, feature engineering, and model deployment. DevOps-savvy: Docker, REST APIs, Git, and maybe even some MLOps sparkle. Cloud comfort: AWS, GCP, or Azure - take your pick. Solid grasp of Agile, good debugging instincts, and a hunger for optimization. This job was posted by Sampurna Pal from AmpleLogic. Show more Show less
AmpleLogic
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