AI/ML Engineer

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4 days ago

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Uvation

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Artificial Intelligence • Cybersecurity • SaaS

Uvation is a comprehensive technology services company providing innovative solutions across the IT infrastructure space. They specialize in artificial intelligence and cutting-edge cybersecurity solutions, offering products powered by Dell and Nvidia AI. Uvation delivers various managed services, including IT operations, security operations, and network operations, optimizing performance and enhancing security for businesses. Their services extend into public clouds with partnerships involving major platforms like Oracle Cloud, Google Cloud, and Amazon AWS. Uvation also operates a marketplace offering competitive pricing on a wide range of hardware and software products and provides a rewards program to incentivize customer engagement.

11 - 50 employees

🤖 Artificial Intelligence

🔒 Cybersecurity

☁️ SaaS

📋 Description

• The AI/ML Engineer plays a critical role in designing, developing, and deploying machine learning models and AI-driven solutions to support strategic business initiatives. • Collaborating with cross-functional teams, including software engineering, data analytics, product development, and business stakeholders, to drive intelligent automation, data-driven decision-making, and advanced analytics capabilities. • Design, build, and deploy ML models for classification, regression, NLP, computer vision, or time-series forecasting. • Clean, preprocess, and transform structured and unstructured datasets for training and inference. • Package and deploy models using tools like Docker, Flask/FastAPI, and Kubernetes. • Work with business stakeholders to translate real-world problems into AI/ML use cases. • Stay updated with the latest research, frameworks, and tools in machine learning and AI. • Collaborate with software developers, DevOps, data analysts, and domain experts for end-to-end solution delivery.

🎯 Requirements

• 3–5 years of hands-on experience in machine learning model development and deployment. • Proven track record of solving real-world problems using supervised, unsupervised, or deep learning methods. • Strong knowledge of: Python and ML libraries (scikit-learn, pandas, NumPy, TensorFlow/PyTorch) • Model evaluation, hyperparameter tuning, and pipeline automation • REST APIs for model serving and integration • Familiarity with: MLOps tools (MLflow, Airflow, DVC, Docker, Kubernetes) • Cloud ML services (AWS SageMaker, Azure ML, GCP AI Platform) • NLP or computer vision frameworks (e.g., Hugging Face, OpenCV)

🏖️ Benefits

• Professional development opportunities