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 an