AI/ML Lead

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 professional 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