Sr AI Engineer / Data Scientist

Koantek LLC; Chesterfield (MO); On-site; USD 90,000 - 130,000; Full time

Job summary

A consulting firm is looking for an experienced Data Scientist to join their customer-facing team, focusing on advanced Machine Learning and MLOps principles. The remote position requires hands-on experience with ML model development, implementation of Generative AI, and strong client interaction skills. Applicants should have over four years of experience in a relevant role, showcasing proficiency in technologies like Docker and Apache Spark. This role involves leading projects with Fortune 500 clients and contributes to both technical and business growth.

Qualifications

• 4+ years of hands-on experience in ML model development and management.
• 3+ years in a client-facing consulting role.
• Excellent verbal and written communication skills.
• MLOps lifecycle management expertise.
• Experience with Docker and data pipeline orchestration.
• Deep understanding of programming for scalable ML applications.
• Experience in deploying Generative AI solutions.

Responsibilities

• Lead end-to-end ML project implementations with clients.
• Design and maintain production-grade ML pipelines.
• Implement and optimize Generative AI and NLP applications.
• Manage solution infrastructure and technologies.
• Contribute to the growth of the ML Practice Team.

Skills

Machine Learning

MLOps

Client communication

Generative AI

NLP

Docker

Apache Spark

Tools

Databricks MLOps Stacks

Job description

Chesterfield, United States | Posted on 04/07/2026

Location: United States – Remote

Employment Type: Full-Time and Contract

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

Key Responsibilities

• Serve as a primary technical consultant, leading and executing end-to-end ML project implementations directly with clients, translating complex business problems into robust technical solutions.
• Exhibit excellent communication, presentation, and stakeholder management skills to clearly articulate technical findings, proposals, and project status to both technical and non-technical audiences.
• Design, build, and maintain production-grade ML pipelines, focusing on continuous integration, continuous delivery (CI/CD), and advanced MLOps practices to ensure reliability and scalability of models.
• Implement and optimize cutting-edge Generative AI and NLP applications, demonstrating hands‑on experience with technologies such as Retrieval Augmented Generation (RAG) and Large Language Models (LLMs) in a production setting.
• Manage underlying solution infrastructure, demonstrating proficiency in technologies such as Docker, pipeline orchestrators, and database systems.
• Leverage expertise in distributed computing frameworks, specifically in scalable machine learning and high-performance data processing (e.g., using technologies like Apache Spark).
• Contribute to the strategic growth of the ML Practice Team, including participation in technical assignments and knowledge transfer activities.
• Ensure all client engagements and training activities are properly documented and reported via designated partner platforms.

Required Qualifications

• 4+ years of hands‑on professional experience developing, deploying, and managing Machine Learning models, with a mandatory requirement for productionizing and maintaining models in a live environment.
• 3+ years of experience in a customer‑facing consulting or solutions architect role, focused on technical implementation and delivery.
• Excellent verbal and written communication skills for effective client and internal team interaction.
• Expertise in MLOps lifecycle management, including model versioning, testing, monitoring, and automated deployment best practices.
• Demonstrable experience within infrastructure management, encompassing containerization (Docker) and data pipeline orchestration.
• Deep understanding of programming for data‑intensive and scalable ML applications.
• Proven experience in deploying and managing Generative AI and NLP solutions for client applications.
• Hands‑on experience with modern ML platform stacks, such as Databricks MLOps Stacks.

Preferred Qualifications

• Knowledge of specific tools and techniques used in scalable machine learning and large‑scale data processing.
• Demonstrated commitment to continuous learning in emerging ML fields, such as LLMs and GenAI application architectures.

Additional Responsibilities

• Work on frontier AI and data projects with Fortune 500 companies.
• Contribute to IP, reusable accelerators, and real business impact.
• Be part of a high‑performance, engineering‑first culture.