| Lead/Sr AI Operations (AI Ops) Engineer at Fremont, California, USA |
| Email: [email protected] |
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Please send resume: [email protected] , [email protected], [email protected], [email protected] Lead/Sr AI Operations (AI Ops) Engineer Location-Fremont, CA / Remote Job Type-Long Term AI Ops Engineer with a strong background in Python, API development, Large Language Models (LLM) concepts, ML Ops, Azure Cloud and AI operations with 8-10 years of experience working on advanced AI/ML systems, cloud infrastructure, and API integrations, with a focus on operationalizing AI models and maintaining robust systems for AI-driven applications. This role requires a combination of technical expertise in cloud computing, machine learning, and software engineering. Collaborate with IT operations and business teams to support business user issues, requests, Production support and deployments; advocate best practices and recommend technical solutions for improvements in usability of application and systems performance Required Skills & Qualifications: Experience: 8-10 years of experience in software development, with a focus on AI/ML operations, cloud infrastructure, and DevOps practices. Python: Advanced proficiency in Python, including experience with AI/ML libraries such as TensorFlow, PyTorch, scikit-learn, and Pandas. APIs: Strong experience in designing, developing, and maintaining RESTful APIs for AI/ML model deployment and integration. ML Ops: In-depth understanding of Machine Learning Operations, including model versioning, monitoring, deployment, and automation of ML workflows. LLM Concepts: Familiarity with Large Language Models (LLMs), including experience working with transformer-based models such as GPT, BERT, or T5. Azure Cloud: Hands-on experience with Azure Cloud services (Azure ML, Azure DevOps, Azure Functions, etc.) and cloud infrastructure management. DevOps & CI/CD: Proficient in setting up CI/CD pipelines for AI/ML models and using tools like Jenkins, GitLab, or Azure DevOps for automation. Data Management & Tools: Experience working with data storage and processing tools like Azure Blob Storage, Azure SQL Database, Kafka, or similar. Version Control: Expertise with Git and version control best practices for collaborative development of AI systems. Problem Solving: Strong analytical and troubleshooting skills, with the ability to identify root causes and optimize AI/ML models and systems. Communication & Collaboration: Excellent communication skills and the ability to work effectively in a cross-functional team environment. Preferred Skills: Cloud Certifications: Azure certifications such as Azure Solutions Architect, Azure AI Engineer, or Azure DevOps Engineer. Security & Compliance: Understanding of security best practices in AI model deployment and experience with secure handling of sensitive data in the cloud. Big Data Tools: Familiarity with big data processing frameworks (e.g., Apache Spark, Hadoop) and integration with AI/ML pipelines. Agile Methodologies: Experience working in Agile teams, with knowledge of Scrum, Kanban, or similar frameworks. Education: A Bachelor's or Masters degree in Computer Science, Engineering, Data Science, or a related field is preferred. Keywords: continuous integration continuous deployment artificial intelligence machine learning information technology California Lead/Sr AI Operations (AI Ops) Engineer [email protected] |
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| 10:36 PM 06-Dec-24 |