Job Title: Data Engineer - ML Training Data Pipeline Notice period: 0-30 Days Experience : 5+ Years Location: Hyderabad OR Pune We are looking for Data Engineer - ML Training Data Pipeline who can Build and maintain the data pipeline that transforms raw production traces into high-quality training datasets for LLM fine-tuning-ingestion, ...
... Familiarity with data preprocessing, feature engineering, and model optimization techniques. Experience with cloud platforms and distributed computing for scalable ML model training. More About the Opportunity: This role offers a unique opportunity to work with a global leader in the Technology, Information and Internet industry, ...
... prototypes you directly design, build, deploy, optimize, and debug production AI agents end-to-end. You will embed deeply with client environments to build seamless integrations while taking full technical ownership of agent performance in the wild. What You'll Do ● End-to-End AI Agent Architecture: Design, prompt, build, ...
... and response generation.- Architect and implement solutions using Azure, AWS, and/or GCP.- Drive production deployment using CI/CD, Docker, Kubernetes, DevOps, MLOps/LLMOps, and cloud-native practices.- Ensure AI solutions meet enterprise requirements for scalability, security, reliability, performance, observability, governance, ...
... RAG, Agentic AI & End-to-End DeploymentWe are looking for a hands-on Gen AI Engineer who can design, build, deploy, and continuously improve production-grade AI solutions. The ideal candidate should have strong experience across RAG, AI Agents, LLMs, vector databases, Python, FastAPI, cloud deployment, and MLOps/LLMOps.Key ...
... RAG, Agentic AI & End-to-End DeploymentWe are looking for a hands-on Gen AI Engineer who can design, build, deploy, and continuously improve production-grade AI solutions. The ideal candidate should have strong experience across RAG, AI Agents, LLMs, vector databases, Python, FastAPI, cloud deployment, and MLOps/LLMOps.Key ...
... pipelines for AI/ML workloads.- Model Evaluation & Observability : Develop and implement automated evaluation loops using "LLM-as-a-judge" methodologies to assess faithfulness, relevance, and toxicity. Monitor model drift, performance, and reliability using frameworks such as RAGAS, TruLens, and DeepEval.- AI Safety & Governance ...
... pipelines for AI/ML workloads.- Model Evaluation & Observability : Develop and implement automated evaluation loops using "LLM-as-a-judge" methodologies to assess faithfulness, relevance, and toxicity. Monitor model drift, performance, and reliability using frameworks such as RAGAS, TruLens, and DeepEval.- AI Safety & Governance ...
... skills and ability to work effectively in small, agile teams - Bachelor's or Master's in Computer Science or equivalent experience Platform engineering or developer portal experience AI/ML integration experience and familiarity with AI agent development Frontend development skills (React, Vite) Infrastructure as Code experience ...
... workflows, intelligent automation, and integration with an existing Java/Spring backend platform. These roles are hands-on software engineering roles, not primarily ML research roles. The team's initial focus areas include semantic/hybrid search and retrieval and AI-powered operational automation such as intent-driven workflows, ...
... that AI-driven outputs align with specific industry requirements and regulatory standards.- Establish rigorous evaluation frameworks and monitoring protocols to maintain model accuracy, mitigate hallucinations, and ensure the ethical deployment of AI systems.- Mentor junior engineers and foster a culture of technical excellence ...
Job Description :AuxoAI is hiring a Senior Applied AI Engineer to design and deploy production-grade computer vision systems that operate reliably in real-world https://jobeax.com/link/SFg0hEiyYqQPdzCu role focuses on building end-to-end visual intelligence systems, combining deep learning, classical computer vision techniques, ...
Director of Infrastructure Engineering Remote | $350,000–$500,000/year | 1 Opening Lead and scale the platform powering production AI systems. Own the strategy and execution behind cloud infrastructure, developer platforms, and reliability practices — ensuring systems remain secure, observable, and resilient. This is a ...
... LLMs, SLMs, agentic AI, machine learning, AI safety, and responsible AI . WHAT MAKES YOU A GREAT FIT - 3+ years of professional experience in Machine Learning, AI/ML Engineering, Data Science, or a related field. - Strong hands-on experience with Machine Learning, LLMs, and SLMs . - Mandatory experience with LangChain and ...
... Computer Science, Engineering, or a related field. A Ph.D. in AI or Machine Learning is a plus.- Proven experience as an AI Engineer, Machine Learning Engineer, or AI Architect, with a track record of successful AI solution design and implementation.- Streamlit - Python- Generative AI- HuggingFace, OpenAi and any Custom Model ...
... AI engineers to share patterns, reusable components, and avoid duplicated effort across parallel implementations. Quality & Testing. This is owned by the Lead AI Platform Engineer. This is owned by the relevant Field Product Manager. Owned by the relevant Lead Developer for engineering-embedded agents (e.g., The ADLC framework ...
... and adapt. Design, develop, and implement AI agents using platforms like Claude and ChatGPT to automate and optimize internal business workflows. Create and maintain API-based integrations between various internal applications to ensure seamless data flow and process automation. Administer and manage Microsoft 365 applications, ...
... things run in production. What You’ll Build Production AI Ship models that meet defined latency and reliability expectation Add monitoring, rollback, and guardrails before anything goes live Optimise inference across CPU/GPU environments when it matters Integration into Real Systems Plug AI into data-heavy workflows without ...
... Master's degree in Engineering, Computer Science, or related field; PhD or MBA is a plus.- Certifications in enterprise platforms (e.g., SAP, Oracle, Salesforce) and AI/ML technologies are preferred.- Strong understanding of cloud platforms (AWS, Azure, GCP) and modern architecture patterns (microservices, APIs, event-driven).Ideal ...