AIML Engineer

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: www.cyfuture.com

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, transfer learning, and designing custom architectures.

3. Programming & Software Engineering

- Strong skills in Python (NumPy, Pandas, Matplotlib, SciPy) for ML development.
- Backend/API development with FastAPI, Flask, or Django.
- Database handling with SQL and NoSQL (PostgreSQL, MongoDB, BigQuery).
- Familiarity with CI/CD pipelines (GitHub Actions, Jenkins).

4. Scalable AI Systems

- Proven ability to build AI-driven applications at scale.
- Handle large datasets, high-throughput requests, and real-time inference.
- Knowledge of distributed computing: Apache Spark, Dask, Ray.

5. Model Monitoring & Optimization

- Hands-on with model compression, quantization, and pruning.
- A/B testing and performance tracking in production.
- Knowledge of model retraining pipelines for continuous learning.

6. Resource Optimization

- Efficient use of compute resources: GPUs, TPUs, CPUs.
- Experience with serverless architectures to reduce cost.
- Auto-scaling and load balancing for high-traffic systems.

7. Problem-Solving & Collaboration

- Translate complex ML models into user-friendly applications.
- Work effectively with data scientists, engineers, and product teams.
- Write clear technical documentation and architecture reports.

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