AI/ML Technologist

Qualifications

Minimum QualificationsBachelor degree with 12+ years or Master degree with 10+ years in any of the following field: Computer Science or Data Science and Engineering, Electronics or Electrical Engineering, Applied mathematics, or related technical disciplines.Skills: Strong programming skills in Python, with the capability to debug complex asynchronous systems.Machine Learning Expertise:

In-depth knowledge of machine learning techniques, including regression, classification, LDA, Naive Bayes, Logistic Regression, and SVM.

Deep Learning and Generative AI:

• Solid understanding of ML/DL techniques, algorithms, and tools. Experience with CNN, RNN (LSTM), and Transformers ( BERT, BART, GPT/T5, Megatron, LLMs).
• Practical experience with Retrieval-Augmented Generation (RAG) and LLM-based applications.
• Familiarity with LLM function calling, Information Retrieval, Vector Databases, Embedding, and Re rank models.
• Hands-on experience with large language model (LLM) agentic pipelines.
• Knowledge of various prompt techniques, including zero-shot, few-shot, Chain-of-Thought, Tree-of-Thought, and React. Database and Tools:
• Experience with database and tools such as SQL, MongoDB, Graph DB, and Elastic Search in native AI applications.

ML Ops:

• Proven experience in deploying and maintaining high-scale AI-based systems.
• Understanding of scalable deployment of multiple microservices involving LLM-driven RAG and Agent applications in a production environment.
• Familiarity with Docker, Helm, Kubernetes, etc.
• Experience with the end-to-end software lifecycle, release packaging, and CI/CD pipeline.

Preferred Skills:

Good understanding of Computer Architecture and x86 architecture. Experienced in Platform Software Development and Validation.

Behavioral traits:Excellent written and oral communication skills.Be able to clearly communicate technical details and concept.