Senior AI Engineer / Data Scientist

Senior AI Engineer / Data Scientist (Consulting)

Location: United States (Remote)
Employment Type: Full-Time / Contract
Experience Level: Senior

About the Role:
We are seeking an experienced, highly technical Senior AI Engineer / Data Scientist to join our customer-facing consulting team. This remote role requires a unique blend of advanced Machine Learning (ML) expertise, deep knowledge of MLOps principles, and a proven track record in client-facing implementation.

You will design, deploy, and maintain production-grade ML solutions, including advanced Generative AI and NLP models, for our diverse client base.

Key Responsibilities:

* Technical Consulting: Lead end-to-end ML implementations directly with clients, translating business problems into robust technical solutions.
* MLOps and Pipelines: Design, build, and maintain production-grade ML pipelines with a strong focus on CI/CD, automation, and scalability.
* GenAI and NLP Deployment: Implement and optimize cutting-edge Generative AI applications (such as LLMs and RAG) in live production settings.
* Infrastructure and Data Scale: Manage underlying infrastructure using Docker, pipeline orchestrators, and distributed computing frameworks like Apache Spark.
* Stakeholder Management: Clearly communicate technical findings, proposals, and project status to both technical and non-technical audiences.

Required Qualifications:

* 4+ years of professional experience developing, deploying, and maintaining ML models in a live production environment (Mandatory).
* 3+ years of experience in a customer-facing consulting or Solutions Architect role.
* Strong expertise in the MLOps lifecycle (model versioning, testing, monitoring, and automated deployment).
* Solid hands-on experience with containerization (Docker) and data pipeline orchestration.
* Proven track record of deploying Generative AI and NLP solutions for client applications.
* Excellent verbal and written communication skills.

Preferred Qualifications:

* Hands-on experience with modern ML platform stacks, specifically Databricks MLOps Stacks.
* Deep knowledge of large-scale data processing and distributed machine learning techniques.
* A strong commitment to continuous learning in emerging ML fields and GenAI application architectures.