
AI/ML Lead
Training Basket · Noida, Uttar Pradesh, India
Strong hiring record · median 19 days open
All reasons
In its favour
- Still listed on the employer's own board
- Lead the design, development, testing, and deployment of AI/ML models and solutions.
- Define AI/ML strategies and technical roadmaps aligned with business objectives.
- Build and optimize machine learning and deep learning models for real-world applications.
- Oversee data preprocessing, feature engineering, model training, validation, and evaluation.
- Work with algorithms for classification, regression, clustering, and predictive analytics.
- Explore and implement Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) solutions.
- Develop scalable AI pipelines and production-ready ML applications.
- Implement MLOps practices for model deployment, monitoring, versioning, and retraining.
- Collaborate with data engineers, software developers, product managers, and business stakeholders.
- Mentor and guide AI/ML engineers and ensure high-quality technical delivery.
- Monitor model performance, accuracy, scalability, and reliability.
- Ensure data privacy, model security, responsible AI practices, and compliance.
- Evaluate emerging AI technologies and recommend suitable tools and frameworks.
- Communicate project progress, technical insights, and business impact to stakeholders.
Requirements
- Strong programming skills in Python.
- Expertise in machine learning libraries such as Scikit-learn, TensorFlow, and PyTorch.
- Strong understanding of statistics, probability, linear algebra, and optimization.
- Experience with data processing and analysis using Pandas, NumPy, and SQL.
- Knowledge of deep learning, NLP, and computer vision.
- Experience with Generative AI, LLMs, prompt engineering, and RAG architectures.
- Familiarity with frameworks such as LangChain or LlamaIndex.
- Experience with model deployment using FastAPI, Flask, or REST APIs.
- Knowledge of MLOps tools, Docker, Kubernetes, and CI/CD pipelines.
- Familiarity with cloud platforms such as AWS, Microsoft Azure, or Google Cloud.
- Strong leadership, problem-solving, communication, and project management skills.
Skills
- Machine Learning
- Deep Learning
- Generative AI
- LLM
- Retrieval-Augmented Generation
- MLOps
- Python
- scikit-learn
- TensorFlow
- PyTorch
- Pandas
- NumPy
- SQL
- NLP
- Computer Vision
- Prompt Engineering
- LangChain
- LlamaIndex
- FastAPI
- Flask
- Docker
- Kubernetes
- AWS
- Azure
- GCP
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