Koantek

Senior AI Engineer

United States · REMOTE · FREELANCE
Publiée le 19 juillet 2026 · Candidature traitée sur le site de l’entreprise
AI-EngineeringData-ScienceMLOpsMachine-Learning-EngineeringTechnical-ConsultingSenior-AI-EngineerSenior-AI-EngineeringSenior-Lead-AI-EngineerSenior-AI-Software-EngineerSenior-AI-ML-EngineerSenior-Software-AI-EngineerSenior-Applied-AI-EngineerSenior-AI-Analytics-EngineerSenior-ML-EngineerSenior-AI-Data-Engineer

Sr AI Engineer / Data Scientist / MLOps Consultant Location: United States – Remote Employment Type: Full-Time and Contract ​ Weare seeking an experienced and highly technical Data Scientist to join ourcustomer-facing consulting team. This remote role requires a blend of advancedMachine Learning (ML) expertise, deep knowledge of MLOps principles, and aproven track record in client-facing implementation. The successful candidatewill be instrumental in designing, deploying, and maintaining production-gradeML solutions, including advanced Generative AI and Natural Language Processing(NLP) models, for our diverse client base.Key Responsibilities • Serve as a primary technicalconsultant, leading and executing end-to-end ML project implementationsdirectly with clients, translating complex business problems into robusttechnical solutions. • Exhibit excellent communication, presentation, andstakeholder management skills to clearly articulate technical findings, proposals, andproject status to both technical and non-technical audiences. • Design, build, and maintainproduction-grade ML pipelines, focusing on continuous integration, continuousdelivery (CI/CD), and advanced MLOps practices to ensure reliability andscalability of models. • Implement and optimizecutting-edge Generative AI and NLP applications, demonstrating hands-onexperience with technologies like Retrieval Augmented Generation (RAG) andLarge Language Models (LLMs) in a production setting. • Manage underlying solutioninfrastructure, demonstrating proficiency in technologies such as Docker,pipeline orchestrators, and database systems. • Leverage expertise indistributed computing frameworks, specifically in scalable machine learning andhigh-performance data processing (e.g., using technologies like Apache Spark). • Contribute to the strategicgrowth of the ML Practice Team, including participation in technicalassignments and knowledge transfer activities. • Ensure all client engagementsand training activities are properly documented and reported via designatedpartner platforms. Required Qualifications • 4+ years of hands-on professional experience developing, deploying,and managing Machine Learning models, with a mandatory requirement for productionizing and maintaining modelsin a live environment. • 3+ years of experience in a customer-facing consulting or solutionsarchitect role, focused on technical implementation and delivery. • Excellent verbal and written communication skills for effective client andinternal team interaction. • Expertise in MLOps lifecyclemanagement, including model versioning, testing, monitoring, and automateddeployment best practices. • Demonstrable experience withinfrastructure management, encompassing containerization (Docker) and datapipeline orchestration. • Deep understanding ofprogramming for data-intensive and scalable ML applications. • Proven experience indeploying and managing Generative AI and NLP solutions for client applications. Preferred Qualifications • Hands-on experience withmodern ML platform stacks, such as Databricks MLOps Stacks. • Knowledge of specific toolsand techniques used in scalable machine learning and large-scale dataprocessing. • Demonstrated commitment tocontinuous learning in emerging ML fields, such as LLMs and GenAI applicationarchitectures. Requirements • Hands-on experience withmodern ML platform stacks, such as Databricks MLOps Stacks. • Knowledge of specific toolsand techniques used in scalable machine learning and large-scale dataprocessing. • Demonstrated commitment tocontinuous learning in emerging ML fields, such as LLMs and GenAI applicationarchitectures. Originally posted on Himalayas

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