Intelliswift Software - Agentic AI Engineer - Python

Role : AI Engineer Experience : 5 to 10 YearsFull timeMode : WFO 5 Days @ Pune OfficeLocation : PuneKey responsibilities : - Translate business questions into analytic approaches and machine learning solutions.- Design and implement end-to-end ML pipelines : data ingestion, feature engineering, model training, validation, deployment and monitoring.- Develop, validate and productionize supervised and unsupervised models (classification, regression, ranking, time series, clustering).- Implement model evaluation, A/B testing and performance monitoring; iterate based on results.- Apply explainability, fairness and privacy-aware practices to model development, document assumptions and limitations.- Collaborate with software engineering to containerize and deploy models (Docker, Kubernetes) and integrate with APIs or event-driven systems.- Automate CI/CD for ML and analytics workflows; manage model versioning and reproducibility.- Create clear technical documentation and present findings and recommendations to technical and non-technical stakeholders.- Stay current with AI/ML trends and evaluate new tools and frameworks for improved outcomes.Required qualifications : - 4+ years of experience developing machine learning models and analytics solutions in a commercial environment (or equivalent experience).- Strong programming skills in Python and familiarity with ML libraries such as TensorFlow.- Experience with cloud platforms (AWS, GCP, or Azure) and at least one managed ML/data service or managed LLM offering.- Experience with model deployment and MLOps practices (Docker, Kubernetes, model serving frameworks, CI/CD, and GitOps tooling like ArgoCD).- Strong foundational knowledge in machine learning, including linear and logistic regression, support vector machines, decision trees, and neural networks.- Good statistical grounding : hypothesis testing, experimental design, evaluation metrics.- Strong communication skills; ability to explain technical concepts to business partners and influence decisions.Strong preference : - Demonstrable experience deploying LLMs and building RAG pipelines in production.- Experience with cloud-managed LLM services (Vertex AI, SageMaker, Azure OpenAI) GCP familiarity is a plus.- Experience with LangChain, LangGraph, or similar agent frameworks to build multi-agent workflows.- Familiarity with MCP or stateful context management patterns for multi-agent systems.Email your updated Profile to View email address on hirist.com (ref:hirist.tech) Role : AI Engineer Experience : 5 to 10 YearsFull timeMode : WFO 5 Days @ Pune OfficeLocation : PuneKey responsibilities : - Translate business questions into analytic approaches and machine learning solutions.- Design and implement end-to-end ML pipelines : data ingestion, feature engineering, model training, validation, deployment and monitoring.- Develop, validate and productionize supervised and unsupervised models (classification, regression, ranking, time series, clustering).- Implement model evaluation, A/B testing and performance monitoring; iterate based on results.- Apply explainability, fairness and privacy-aware practices to model development, document assumptions and limitations.- Collaborate with software engineering to containerize and deploy models (Docker, Kubernetes) and integrate with APIs or event-driven systems.- Automate CI/CD for ML and analytics workflows; manage model versioning and reproducibility.- Create clear technical documentation and present findings and recommendations to technical and non-technical stakeholders.- Stay current with AI/ML trends and evaluate new tools and frameworks for improved outcomes.Required qualifications : - 4+ years of experience developing machine learning models and analytics solutions in a commercial environment (or equivalent experience).- Strong programming skills in Python and familiarity with ML libraries such as TensorFlow.- Experience with cloud platforms (AWS, GCP, or Azure) and at least one managed ML/data service or managed LLM offering.- Experience with model deployment and MLOps practices (Docker, Kubernetes, model serving frameworks, CI/CD, and GitOps tooling like ArgoCD).- Strong foundational knowledge in machine learning, including linear and logistic regression, support vector machines, decision trees, and neural networks.- Good statistical grounding : hypothesis testing, experimental design, evaluation metrics.- Strong communication skills; ability to explain technical concepts to business partners and influence decisions.Strong preference : - Demonstrable experience deploying LLMs and building RAG pipelines in production.- Experience with cloud-managed LLM services (Vertex AI, SageMaker, Azure OpenAI) GCP familiarity is a plus.- Experience with LangChain, LangGraph, or similar agent frameworks to build multi-agent workflows.- Familiarity with MCP or stateful context management patterns for multi-agent systems.Email your updated Profile to View email address on hirist.co