Senior AI Engineer

Data Scientist – ML Consulting (Remote) Must be a US Citizen or Green Card holder to be eligible for this role.   We're looking for a senior Data Scientist to join our customer-facing consulting team. This is a hands-on technical role where you'll lead end-to-end ML implementations for clients — from architecture through production deployment — with a strong emphasis on GenAI, NLP, and MLOps. What You'll Do Lead client engagements — serve as the primary technical consultant, translating complex business problems into production-grade ML solutions and communicating clearly with both technical and non-technical stakeholders. Build and maintain ML pipelines — design robust CI/CD-enabled pipelines with best-in-class MLOps practices: model versioning, testing, monitoring, and automated deployment. Deploy GenAI and NLP applications — implement and optimize LLM-based solutions, including RAG architectures, in live client environments. Manage solution infrastructure — work with Docker, pipeline orchestrators, and database systems to support scalable ML deployments. Leverage distributed computing — apply frameworks like Apache Spark for high-performance, large-scale data processing. Support practice growth — contribute to knowledge sharing, internal technical initiatives, and documentation via partner platforms. Required Qualifications 4+ years of hands-on experience developing, deploying, and maintaining ML models in production environments (productionization experience is a must) 3+ years in a customer-facing consulting or solutions architect role with a focus on technical delivery Strong MLOps experience: model lifecycle management, versioning, monitoring, and automated deployment Proficiency with containerization (Docker) and data pipeline orchestration Proven experience deploying Generative AI and NLP solutions for client applications Excellent written and verbal communication skills Preferred Qualifications Hands-on experience with Databricks MLOps Stacks or similar modern ML platform stacks Familiarity with scalable ML tooling and large-scale data processing frameworks Active engagement with emerging ML fields — LLMs, GenAI application architectures, etc.

Created: 2026-03-07