Job description
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 skillsto 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+ yearsof hands-on professional experience developing, deploying,and managing Machine Learning models, with a mandatory requirement for productionizing and maintaining modelsin a live environment.
3+ yearsof experience in a customer-facing consulting or solutionsarchitect role, focused on technical implementation and delivery.
Excellent verbal and written communication skillsfor 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
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.