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Job Description – AI-ML Engineer
Location - Chennai/Bangalore
Experience - 5-7Year
Budget -24LPA
Check list for AI-ML
Skills
Mandatory / Preferred / Nice to Have
Min 3 years hands on experience on Python advanced with Big Data Analytics
Explanation: Expertise in Python programming and Big Data Analytics, including large-scale data processing, analysis, and automation. Has handled large datasets before.
Mandatory
Min 3 years hands on experience on Extensive Data Stitching
Explanation: Demonstrated data stitching expertise by integrating multi-source datasets into a single, consistent data model, ensuring high accuracy and reliability for downstream analytics or modeling. Capability to come up with innovative ways for signature assessment & correlations of multiple datasets. Capable of making queries faster & efficient, to make them usable for downstream integration.
Mandatory
Hands on experience on Machine Learning & Deep Learning Frameworks (TensorFlow / PyTorch / Scikit-Learn / Hugging Face Transformers etc..)
Mandatory
Extensive experience in effective communication and cross-functional collaboration — a confident, creative, and critical thinker.
Explanation: While knowing everything isn't essential, the ability to navigate a fast-paced work environment with agility is crucial.
Mandatory
AI/ML Modeling Experience:
Explanation: Hands-on experience in AI/ML modeling, including data preprocessing, feature engineering, model training, validation, and optimization. Experience with existing models available in market, pros and cons understanding to use the right model for the right use-case.
Preferred
LLM Expertise:
Explanation: Expertise in developing, fine-tuning, and deploying large language models (LLMs) for real-world applications.
Preferred
Telco Experience:
Explanation: Experience with Telco, specifically Nokia or Ericsson RF, RAN or E2E Expertise.
Nie to Have
Hands-on experience on Agentic AI Frameworks (LangChain, LangGraph, CrewAI, AutoGen etc.), AI Orchestration (Prefect, Airflow, Custom Orchestrators), and Dynamic Workflow Building
Explanation: Proven experience in building multi-agent systems with orchestrated workflows. Ability to design and implement AI agent architectures, dynamic workflow pipelines, agent-to-agent communication, tool integration, and state management using modern Agentic AI frameworks. Experience with workflow orchestration platforms for managing agent execution, task scheduling, and pipeline reliability.
Mandatory
Master's or bachelor's degree or Post Graduate courses/Program or Advance courses or Certification in Data Science or AI
Nice to Have
Knowledge of multiple data base databases like SQL server, Postgres, click house, Presto, Cloud Platforms such as AWS, GCP, Azure, and ML platforms like Sage Maker, Front end Programming language or tools such as JavaScript's/ React/Angular, Tableau / PowerBI, Back end Language Sacala or Spark
Nice to Have
Knowledge or Hands-on experience on Generative AI (LLM, Prompt Engineering, RAG, Fine-Tuning)
Explanation: Experience with large language model integration, prompt engineering techniques, Retrieval-Augmented Generation (RAG) pipelines, and model fine-tuning for domain-specific use cases.
Preferred
Job ID: 148483181
Skills:
Azure ML, Azure Data Lake, Cosmos DB, Python, Azure DevOps, GitHub Actions, CI CD
Skills:
Java Programming Language, CSS, Debugging, Automation, Agile Methodology, HTML, Business Requirements, Application Development, Api, Web Services, Business Process, Python Programming Language, JavaScript Programming Language, Scrum Software Development, SQL Programming Language, Angular Web Framework
Skills:
Machine Learning, Deep Learning, Tensorflow, MLops, Pytorch, Python, Generative AI, Agentic AI architectures, AI ML development libraries, LLMOps, Scikit-learn, Model lifecycle management, RAG AI agents, Orchestration frameworks, Workflow automation, Prompt Engineering, Observability, Monitoring
Skills:
Pytorch, Docker, Azure, Kubernetes, Python, PEFT, Transformers, DPO, Multi-GPU Finetuning, trl, LORA, deepspeed, NLP techniques
Skills:
Java, Gcp, Docker, Terraform, Ansible, Azure, Python, Kubernetes, AWS, CrewAI, LangChain, LLMs, Go, Pinecone, Semantic Kernel, AutoGen, FAISS, Weaviate
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