Remote 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.