Sr AI Engineer / Data Scientist

Koantek LLC; Chesterfield (MO); Presencial; USD 90.000 - 130.000; Jornada completa

Descripción de la vacante

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.

Formación

• 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.

Responsabilidades

• 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.

Conocimientos

Machine Learning

MLOps

Client communication

Generative AI

NLP

Docker

Apache Spark

Herramientas

Databricks MLOps Stacks

Descripción del empleo

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.