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4 days ago
• Programming Languages – Python (FastAPI, Flask, Django)
• Machine Learning Libraries – scikit-learn, XGBoost, TensorFlow or PyTorch
• Data Pipelines – Pandas, Spark, Airflow
• Model Deployment – FastAPI, Flask, Docker, MLflow
• Cloud Platforms – AWS, GCP, Azure (any one)
• Version Control – GitKey ResponsibilitiesDesign and develop machine learning models to address business requirements.Build and manage data pipelines for training and inference workflows.Train, evaluate, and optimize models for accuracy and performance.Deploy models in production environments using containerized solutions.Work with structured and unstructured data from various sources.Ensure robust monitoring, retraining, and versioning of models.Contribute to architecture and design discussions for AI/ML systems.Document processes, results, and deployment procedures clearly.Collaborate with software engineers, data engineers, and business teams.Drive independent problem solving and experimentation to deliver innovative solutions.Work with open-source models – handling, deployment, fine-tuning, and optimization – especially for privacy-focused/on-prem deployments.Apply ML theory to design end-to-end AI architectures beyond simple API consumption.Contribute across multiple AI subdomains including NLP, Computer Vision, Signal/Audio Processing, and Multimodal systems.Stay ahead of emerging AI trends, demonstrating technical curiosity through self-driven projects, research, or open-source contributions.Required Skills and Qualifications4+ years of hands-on experience delivering ML solutions in productionProven track record across multiple AI subdomains (NLP, CV, Generative AI, Signal/Audio, Multimodal)Strong programming skills in Python with deep understanding of ML fundamentalsExperience in supervised & unsupervised learning, regression, classification, clusteringPractical expertise in open-source model handling, fine-tuning, optimization, and deploymentSolid knowledge of data preprocessing, feature engineering, and model evaluationExperience with APIs, containers, and cloud platforms (AWS/GCP/Azure)Familiarity with C I/CD workflows and version control (Git)Self-driven, technically curious, and able to deliver in fast-paced environmentsExcellent English communication skills for collaboration with distributed teamsBachelor's/Master's in Computer Science, Data Science, Engineering, or related field
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