Job Url: https://www.linkedin.com/jobs/search/?currentJobId=4326776745&distance=25.0&f_AL=true&f_TPR=r7000&f_WT=2&geoId=103644278&keywords=software%20engineer&origin=JOB_SEARCH_PAGE_JOB_FILTER Job Description: Alambda Systems Share Show more options Azure AI Platform Engineer Greater St. Louis · 18 minutes ago · 23 applicants No response insights available yet Remote Matches your job preferences, workplace type is Remote. Contract Easy Apply Save Save Azure AI Platform Engineer at Alambda Systems Azure AI Platform Engineer Alambda Systems · Greater St. Louis (Remote) Easy Apply Save Save Azure AI Platform Engineer at Alambda Systems Show more options Your profile is missing required qualifications Show match details Help me update my profile BETA Is this information helpful? Get personalized tips to stand out to hirers Find jobs where you’re a top applicant and tailor your resume with the help of AI. Try Premium for PKR0 About the job Company Description Alambda Systems specializes in software and web development services, offering expertise in creating marketing websites, providing SEO solutions, developing both web and desktop software, and assisting with database administration. Our team delivers customized IT solutions to meet diverse business needs and enhance operational efficiency. With a strong emphasis on quality and functionality, we aim to empower businesses through innovative software solutions. Role Description This is a contract-based remote role for an Azure AI Platform Engineer. The professional in this role will be responsible for designing, implementing, and troubleshooting Azure-based AI platforms. Daily activities include software development, programming, managing infrastructure, and optimizing database functionalities. Collaboration with cross-functional teams to ensure the delivery of high-quality, scalable, and secure AI solutions is a key part of the role. Role: Azure AI Platform Engineer Duration: 06+ Months status: contract/C2C Location: Remote Description: Job Duties: · Exercise expertise in ideating and developing AI/ML applications on prediction, recommendation, text analytics, computer vision, bots, and content intelligence. · Apply statistical skills and advanced statistical techniques and concepts. · Demonstrate deep knowledge of ML frameworks such as TensorFlow, PyTorch, Keras, Spacy, and scikit-learn. · Leverage advanced knowledge of Python open-source software stack such as Django or Flask, Django Rest or FastAPI, etc. · Deep knowledge in statistics and Machine Learning models, deep learning models, NLP, Generative Adversarial Networks (GAN), and other generative models. · Experience working with RAG technologies and LLM frameworks, LLM model registries (Hugging Face), LLM APIs, embedding models, and vector databases · Employ technical knowledge and hands-on experience with Azure OpenAI, Google Vertex Gen AI, and AWS LLM foundational models, BERT, Transformers, PaLM, Bard, etc. · Display proficiency in programming languages such as Python and understanding of various Python packages. Experience with TensorFlow, PyTorch, or Keras. · Develop and implement GenAI solutions, collaborating with cross-functional teams, and supporting the successful execution of AI projects for a diverse range of clients. · Assist in the design and implementation of GenAI use cases, projects, and POCs across multiple industries. · Work on RAG models and Agents Frameworks to enhance GenAI solutions by incorporating relevant information retrieval mechanisms and frameworks · Create and maintain data infrastructure to ingest, normalize, and combine datasets for actionable insights. · Work closely with customers to understand their requirements and deliver customized AI solutions. · Interact at appropriate levels to ensure client satisfaction and project success. · Communicate complex technical concepts clearly to non-technical audiences. · Conduct training sessions to enhance overall data science skills within the organization. Minimum Skills Required: Required skills: Strong Azure experience Cloud networking Model Development/Model Validation within Azure ML Studio Kubernetes (a priority since Argo is primarily used for managing K8s deployments) API development, with exposure to Bento being strongly preferred Nice-to-have / strongly preferred: Argo (Kubernetes deployment management) Bento (API management)