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Data Science Engineer (AWS) Job in USA 2026 | Arkisol Inc

NewsNowGh

Data Science Engineer (AWS) Job in USA 2026 | Arkisol Inc Data Science Engineer (AWS) Job in USA 2026 | Arkisol Inc An exciting opportunity is now open for an experienced Data Science Engineer (AWS – NLP & Generative AI) to join a high-impact technology project in Houston, Texas, USA. This role is designed for senior-level professionals with deep expertise in data science, machine learning, and modern AI platforms, and is open to international candidates requiring H-1B visa sponsorship or transfer. The position sits at the intersection of advanced analytics, cloud engineering, and next-generation AI, offering the chance to work on enterprise-scale solutions using NLP, large language models, and AWS cloud infrastructure. For global professionals seeking to advance their US-based career in artificial intelligence and applied machine learning, this role provides both technical challenge and strong long-term market relevance. About the Role This is a senior, hands-on engineering role focused on designing, building, and deploying production-grade AI and machine learning solutions on AWS. You will work across NLP pipelines, generative AI systems, and large-scale data platforms, contributing to real-world business use cases that require reliability, scalability, and performance. The role combines applied research with engineering execution, including model development, cloud deployment, and MLOps practices. You will collaborate with cross-functional engineering and business teams to turn advanced AI concepts into practical, secure, and maintainable solutions in a hybrid enterprise environment. About the Hiring Firm Arkisol Inc is a technology-driven consulting and solutions firm delivering advanced data, cloud, and AI platforms for enterprise clients across multiple industries. The company specializes in high-end digital transformation, cloud-native architectures, and applied artificial intelligence. Arkisol supports international professionals and works with visa programs such as H-1B to attract top global talent for critical, high-skill technology initiatives in the United States. Responsibilities Design and implement end-to-end data science and machine learning solutions on AWS Build, train, fine-tune, and deploy NLP models for tasks such as classification, NER, embeddings, and sentiment analysis Develop and integrate Generative AI and LLM-based systems, including RAG and prompt engineering workflows Architect and manage ML workloads using AWS services such as SageMaker, S3, EC2, Lambda, and Bedrock Develop scalable data pipelines and microservices to support AI and analytics workloads Implement MLOps practices, including CI/CD, monitoring, versioning, and model lifecycle management Collaborate with engineering, product, and business teams to translate requirements into production solutions Optimize performance, reliability, security, and cost-efficiency of deployed systems Requirements 9+ years of professional experience in Data Science, Machine Learning, or AI Engineering Strong hands-on expertise with AWS cloud services, especially SageMaker and related ML tooling Proven experience in NLP and Generative AI / LLM-based systems Advanced proficiency in Python and common ML libraries such as Pandas, NumPy, and Scikit-learn Experience with deep learning frameworks such as PyTorch or TensorFlow Solid understanding of MLOps, production deployments, and cloud-based AI architectures Experience building APIs, microservices, and scalable data platforms Bachelor’s or higher degree (degree certificate required for submission) This role is an outstanding opportunity for senior international AI professionals seeking a US-based, H-1B-eligible position at the forefront of NLP, Generative AI, and cloud-based machine learning. If you are looking to work on cutting-edge AI systems, build high-impact enterprise solutions, and grow your long-term career in the United States, this position offers both technical depth and global career leverage. #J-18808-Ljbffr

Vacancy posted 16 hours ago
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