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Senior AI Engineer

  • Chesterfield, MO, United States

Full-time · Contract

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Job details

Job type
Full-time · Contract
Posting language
English
Posted

Original job description

Sr AI Engineer / Data Scientist / MLOps Consultant

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. The successful candidate will be instrumental in designing, deploying, and maintaining production-grade ML solutions, including advanced Generative AI and Natural Language Processing (NLP) models, for our diverse client base.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 like 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 with 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.

Preferred Qualifications

  • Hands-on experience with modern ML platform stacks, such as Databricks MLOps Stacks.
  • 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.

Requirements

  • Hands-on experience with modern ML platform stacks, such as Databricks MLOps Stacks.
  • 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.
More about this job

Skills

  • Machine learning
  • ML
  • Natural language processing
  • Communication skills
  • Stakeholder management
  • CI/CD
  • Docker
  • Database management systems
  • Apache Spark
  • Databricks

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