5 Kserve Jobs

Senior xOps Specialist AIOps, MLOps & DataOps Architect Location: Chennai, Pune Employment Type: Fulltime - Hybrid Experience Required: 12-15 years Job Summary: We are seeking a Senior xOps Specialist to architect, implement, and optimize AI-driven operational frameworks across AIOps, MLOps, and DataOps. The ideal candidate will design and enhance intelligent automation, predictive analytics, and resilient pipelines for large-scale data engineering, AI/ML deployments, and IT operations. This role requires deep expertise in AI/ML automation, data-driven DevOps strategies, observability frameworks, and cloud-native orchestration. Key Responsibilities – Design & Architecture AIOps: AI-Driven IT Operations & Automation Architect AI-powered observability platforms, ensuring predictive incident detection and autonomous IT operations. Implement AI-driven root cause analysis (RCA) for proactive issue resolution and performance optimization. Design self-healing infrastructures leveraging machine learning models for anomaly detection and remediation workflows. Establish event-driven automation strategies, enabling autonomous infrastructure scaling and resilience engineering. MLOps: Machine Learning Lifecycle Optimization Architect end-to-end MLOps pipelines, ensuring automated model training, validation, deployment, and monitoring. Design CI/CD pipelines for ML models, embedding drift detection, continuous optimization, and model explainability. Implement feature engineering pipelines, leveraging data versioning, reproducibility, and intelligent retraining techniques. Ensure secure and scalable AI/ML environments, optimizing GPU-accelerated processing and cloud-native model serving. DataOps: Scalable Data Engineering & Pipelines Architect data processing frameworks, ensuring high-performance, real-time ingestion, transformation, and analytics. Build data observability platforms, enabling automated anomaly detection, data lineage tracking, and schema evolution. Design self-optimizing ETL pipelines, leveraging AI-driven workflows for data enrichment and transformation. Implement governance frameworks, ensuring data quality, security, and compliance with enterprise standards. Automation & API Integration Develop Python or Go-based automation scripts for AI model orchestration, data pipeline optimization, and IT workflows. Architect event-driven xOps frameworks, enabling intelligent orchestration for real-time workload management. Implement AI-powered recommendations, optimizing resource allocation, cost efficiency, and performance benchmarking. Cloud-Native & DevOps Integration Embed AI/ML observability principles within DevOps pipelines, ensuring continuous monitoring and retraining cycles. Architect cloud-native solutions optimized for Kubernetes, containerized environments, and scalable AI workloads. Establish AIOps-driven cloud infrastructure strategies, automating incident response and operational intelligence. Qualifications & Skills – xOps Expertise Deep expertise in AIOps, MLOps, and DataOps, designing AI-driven operational frameworks. Proficiency in automation scripting, leveraging Python, Go, and AI/ML orchestration tools. Strong knowledge of AI observability, ensuring resilient IT operations and predictive analytics. Extensive experience in cloud-native architectures, Kubernetes orchestration, and serverless AI workloads. Ability to troubleshoot complex AI/ML pipelines, ensuring optimal model performance and data integrity. Preferred Certifications (Optional): AWS Certified Machine Learning Specialist Google Cloud Professional Data Engineer Kubernetes Certified Administrator (CKA) DevOps Automation & AIOps Certification

Roles and Responsibilities Design and develop data science solutions using Python. Experience in machine learning and deep learning frameworks (PyTorch, TensorFlow) Develop machine learning models using TensorFlow or PyTorch and deploy them on Kubernetes, MLflow, and KServe clusters. Familiarity with machine learning deployment and MLOps tools Experience working with model repositories and fine-tuning frameworks like Hugging Face. Experience with frameworks like LangGraph/LangChain. Design and implement AI agent workflows. Develop end-to-end intelligent pipelines and multi-agent systems (e.g., LangGraph/LangChain workflows) that coordinate multiple LLM-powered agents to solve complex tasks. Create graph-based or state-machine architectures for AI agents, chaining prompts and tools as needed. Build and fine-tune generative models. Develop, train, and fine-tune advanced generative models (transformers, diffusion models, VAEs, GANs, etc.) on domain-specific data. Deploy and optimize foundation models (such as GPT, LLaMA, Mistral) in production, adapting them to our use cases through prompt engineering and supervised fine-tuning.

We are looking for experienced Senior and Principal Machine Learning Engineers across two teams: InstructLab and OpenShift AI . In this role, you will build, optimize, and scale machine learning models while contributing to innovative AI-driven solutions, and assisting users in understanding ML predictions. During the hiring process, we'll work with you to determine the best team placement based on your background and interests. While the core job requirements remain consistent, your day-to-day responsibilities will align with your chosen team's objectives. Successful applicants must reside in a country where Red Hat is registered to do business. What you will do Specific responsibilities will vary based on team placement, but may include: Design and implement machine learning systems Develop and optimize ML models for production use Create and maintain ML infrastructure and pipelines Ensure ML systems are scalable and maintainable Collaborate with data scientists to productionize models Collaborate closely with researchers, software developers, and upstream AI/ML communities Mentor and guide other team members What you will bring Experience in AI development, deep learning, machine learning libraries (e.g. pytorch, scikit-learn), prompt engineering, and/or fundamental mathematics Experience in feature engineering Experience in Go or Python development Experience in Kubernetes, OpenShift, Docker, or other cloud-native technologies Experience in agile development, Jira, and Git Ability to quickly learn and use new tools and technologies Excellent written and verbal communication skills The following skills are valued and may influence team placement: Masters or PhD in Machine Learning (ML) or Natural Language Processing (NLP) Active participation in KServe, TrustyAI, Kubeflow, or other open source communities Specialized expertise in specific AI domains (NLP, Computer Vision, MLOps, etc.)

MIN 2 yrs exp as Team Leader -Field collection banking process on paper excluding AM/DM exp Bucket Collections -Field collection Client /Team/ SLA / Attrition/ Shrinkage WFO shivaji Nagar Bangalore- Must Know-English and kannada Required Candidate profile call,whatsapp cv Amit 8178259405/Neha 8287267407 MIN 2 yrs exp as Team Leader -Field collection process on paper excluding AM/DM exp Perks and benefits Salary no constraint for suitable candidate

MIN 2 yrs exp as Team Leader -Field collection banking process on paper excluding AM/DM exp Bucket Collections -Field collection Client /Team/ SLA / Attrition/ Shrinkage WFO shivaji Nagar Bangalore- Must Know-English and kannada Required Candidate profile call,whatsapp cv Amit 8178259405/Neha 8287267407 MIN 2 yrs exp as Team Leader -Field collection process on paper excluding AM/DM exp Perks and benefits Salary no constraint for suitable candidate