Hiring: AI/ML Lead

Client: Corover.ai

Experience: 7–10 years

Educational Qualification

- B.Tech./M.Tech./M.S./Ph.D. in Computer Science, AI, or a related field.

Mandatory Experience

- 7–10 years in AI/ML solution development.
- At least 4–5 years leading AI/ML model implementation teams.
- Proven end-to-end delivery experience from prototyping to production deployment.

Mandatory Technical Skills

- AI/ML: CNN, RNN, Transformers, reinforcement learning, transfer learning, and foundation model fine-tuning.
- Model development: TensorFlow, PyTorch, Hugging Face, MLflow, hyperparameter tuning, and neural architecture search.
- Programming: Expert-level Python, R, C++, and CUDA.
- Optimization: Quantization, pruning, knowledge distillation, ONNX, TensorRT, and inference optimisation.
- Cloud: AWS SageMaker, Azure ML, GCP Vertex AI, distributed training, and cloud-native AI.
- MLOps: Kubernetes, Docker, TorchServe, TensorFlow Serving, CI/CD, and production monitoring.
- Specialized AI: NLP, BERT, GPT, LLM fine-tuning, YOLO, ResNet, LSTM, Prophet, and Generative AI.

Key Responsibilities

- Lead model design, prototyping, development, and deployment.
- Develop reusable models for classification, prediction, summarization, and image analytics.
- Define development standards, benchmarks, and validation protocols.
- Guide data scientists on experimentation and hyperparameter tuning.




- Work with MLOps teams on deployment, retraining, and monitoring.
- Lead technical reviews, mentoring, and Responsible AI compliance.

Preferred: Advanced AI/ML certifications, research publications, and open-source contributions. Pay: ₹2,300,000.00 - ₹3,800,000.00 per year

Application Question(s)

- How many years of qualified experience do you have in AI/ML solution development?
- How many years of experience do you have leading AI/ML model development or implementation teams?
- Have you independently led an AI/ML solution from prototyping to production deployment?
- Which deep learning frameworks and model development tools have you used hands-on?
- Do you have hands-on experience fine-tuning Transformers, foundation models, or Large Language Models (LLMs)?
- Do you have hands-on experience optimizing AI/ML models for production inference using techniques such as quantization, pruning, ONNX, or TensorRT?
- Do you have experience deploying and monitoring AI/ML models using Docker, Kubernetes, CI/CD pipelines, or MLOps platforms?
- Which cloud-based AI/ML platforms have you used hands-on?
- Do you have hands-on experience in NLP/LLMs and computer vision, including models such as BERT, GPT, YOLO, or ResNet?
- How soon can you join?
- Current CTC
- Expected CTC

Work Location: In person

📌 AI/ML Lead (Delhi)
🏢 Spinode Technologies
📍 Delhi