The Role
Lead end-to-end ML implementations for clients, design and maintain production-grade MLOps pipelines, deploy and optimize Generative AI/LLM and NLP solutions, manage infrastructure (Docker, orchestration, distributed compute), and communicate technical results to stakeholders.
Summary Generated by Built In
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.
Skills Required
- 4+ years developing, deploying, and maintaining ML models in production
- 3+ years in a customer-facing consulting or Solutions Architect role
- Strong expertise in the MLOps lifecycle (model versioning, testing, monitoring, automated deployment)
- Hands-on experience with containerization (Docker)
- Hands-on experience with data pipeline orchestration and CI/CD for ML
- Proven track record deploying Generative AI, LLM, RAG, and NLP solutions in production
- Excellent verbal and written communication skills
- Experience with Apache Spark and large-scale distributed data processing
- Hands-on experience with Databricks MLOps stacks
- Deep knowledge of distributed machine learning techniques and large-scale data processing
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The Company
What We Do
Koantek is a Databricks-exclusive system integrator focused on enterprise-scale data and AI transformation, helping clients modernize, migrate, and scale AI solutions.
