AI/ML Engineer

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Uvation

WebsiteLinkedInAll Job Openings

11 - 50 employees

💼 Consulting

🏥 Healthcare

🤖 Artificial Intelligence

Consulting • Healthcare • Artificial Intelligence

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.

📋 Description

• Design, build, and deploy ML models for classification, regression, NLP, computer vision, or time-series forecasting • Select algorithms and techniques based on business needs and data characteristics • Monitor and improve model performance using metrics and feedback loops • Clean, preprocess, and transform structured and unstructured datasets • Engineer and select features to improve model accuracy and generalizability • Collaborate with data engineers to ensure data quality and accessibility • Package and deploy models using Docker, Flask/FastAPI, and Kubernetes • Implement CI/CD pipelines for ML using MLflow, Airflow, or Kubeflow • Monitor deployed models for drift, latency, and production performance • Translate business problems into AI/ML use cases with stakeholders • Prototype and test AI-driven solutions such as recommendation engines, chatbots, and fraud detection • Contribute to proof-of-concept projects and scale successful models to production • Stay updated on machine learning and AI research, frameworks, and tools • Experiment with LLMs, transformers, and generative AI • Collaborate with software developers, DevOps, data analysts, and domain experts • Document models, experiments, and pipelines • Ensure reproducibility, scalability, and compliance with data governance policies

🎯 Requirements

• 3–5 years of hands-on experience in machine learning model development and deployment • Proven track record solving real-world problems using supervised, unsupervised, or deep learning methods • Strong knowledge of Python and ML libraries including scikit-learn, pandas, NumPy, and TensorFlow/PyTorch • Knowledge of model evaluation, hyperparameter tuning, and pipeline automation • Knowledge of REST APIs for model serving and integration • Familiarity with MLOps tools including MLflow, Airflow, DVC, Docker, and Kubernetes • Familiarity with cloud ML services including AWS SageMaker, Azure ML, and GCP AI Platform • Familiarity with NLP or computer vision frameworks such as Hugging Face and OpenCV • Strong analytical and problem-solving abilities • Excellent verbal and written communication skills • Ability to work independently and within cross-functional teams • Curiosity, adaptability, and willingness to learn continuously