Machine Learning Engineer | [NSE201]

Machine Learning Engineer | [NSE201]

.Company OverviewAt Avahi, we're redefining what it means to be a premier cloud-first consulting company, recognized for our people, culture, and innovative solutions.
With expertise in Managed Services, Reselling, Staffing, and Professional Services, we are dedicated to delivering exceptional value and putting customers first.As a remote-first, global team spanning North America, Europe, and Southeast Asia, we foster a collaborative and diverse environment where professional growth, creativity, and mutual respect thrive.
Guided by our values—Customer-Centricity, Collaboration, Agility, Innovation, Integrity,



and Diversity & Inclusion—we empower businesses to embrace the full potential of a cloud-first approach.Role SummaryAvahi is seeking a Machine Learning Engineer to design, develop, and deploy AI/ML solutions at scale.
You will work with state-of-the-art deep learning models, large language models (LLMs), and MLOps pipelines, leveraging AWS cloud infrastructure to optimize and productionize AI applications.In this role, you will bridge research and real-world implementation, integrating open-source frameworks like Hugging Face Transformers, Diffusers, and PyTorch into enterprise AI applications.
You will collaborate with data scientists, engineers, and cloud architects to deploy machine learning models efficiently and securely.If you're passionate about AI/ML, cloud computing, and delivering scalable solutions in production environments, we'd love to hear from you.Key ResponsibilitiesMachine Learning & Model DeploymentBuild and optimize AI/ML models for large-scale enterprise applications, focusing on LLMs, GenAI, and deep learning architectures.Implement Retrieval-Augmented Generation (RAG), fine-tuning,



and agentic workflows for real-world AI applications.Deploy models into AWS environments using SageMaker, Lambda, EC2, and containerized solutions.Develop MLOps pipelines for continuous integration, deployment, and monitoring of ML models.Cloud & Infrastructure IntegrationDesign and integrate AI models with AWS cloud infrastructure, ensuring scalability, security, and efficiency.Optimize model performance on GPU-accelerated instances (e.G., EC2, SageMaker, EKS, Lambda with GPU support).Implement serverless and containerized solutions (Docker, Kubernetes) for scalable AI workloads.Software Engineering & DevelopmentDevelop APIs and SDKs to integrate AI models into cloud-native applications.Write high-quality, reusable Python code for AI/ML pipelines.Build developer-friendly documentation, examples, and notebooks to showcase AI/ML solutions.Collaboration & Thought LeadershipWork closely with data scientists,



engineers, and cloud architects to deliver AI solutions.Stay updated on emerging AI trends, LLM advancements, and AWS AI services.Contribute to open-source projects, blog posts, and technical workshops to share expertise

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