
AIML Engineer
4 weeks ago
Position Title: AI/ML Engineer
Company : Cyfuture India Pvt. Ltd.
Industry : IT Services and IT Consulting
Location : Sector 81, NSEZ, Noida (5 Days Work From Office)
Website :
About Cyfuture
Cyfuture is a trusted name in IT services and cloud infrastructure, offering state-of-the-art data center solutions and managed services across platforms like AWS, Azure, and VMWare. We are expanding rapidly in system integration and managed services, building strong alliances with global OEMs like VMWare, AWS, Azure, HP, Dell, Lenovo, and Palo Alto.
Position Overview
We are hiring an experienced AI/ML Engineer to lead and shape our AI/ML initiatives. The ideal candidate will have hands-on experience in machine learning and artificial intelligence, with strong leadership capabilities and a passion for delivering production-ready solutions. This role involves end-to-end ownership of AI/ML projects, from strategy development to deployment and optimization of large-scale systems.
Key Responsibilities
- Lead and mentor a high-performing AI/ML team.
- Design and execute AI/ML strategies aligned with business goals.
- Collaborate with product and engineering teams to identify impactful AI opportunities.
- Build, train, fine-tune, and deploy ML models in production environments.
- Manage operations of LLMs and other AI models using modern cloud and MLOps tools.
- Implement scalable and automated ML pipelines (e.g., with Kubeflow or MLRun).
- Handle containerization and orchestration using Docker and Kubernetes.
- Optimize GPU/TPU resources for training and inference tasks.
- Develop efficient RAG pipelines with low latency and high retrieval accuracy.
- Automate CI/CD workflows for continuous integration and delivery of ML systems.
Key Skills & Expertise
1. Cloud Computing & Deployment
- Proficiency in AWS, Google Cloud, or Azure for scalable model deployment.
- Familiarity with cloud-native services like AWS SageMaker, Google Vertex AI, or Azure ML.
- Expertise in Docker and Kubernetes for containerized deployments
- Experience with Infrastructure as Code (IaC) using tools like Terraform or CloudFormation.
2. Machine Learning & Deep Learning
- Strong command of frameworks: TensorFlow, PyTorch, Scikit-learn, XGBoost.
- Experience with MLOps tools for integration, monitoring, and automation.
- Expertise in pre-trained models,
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