Remote Biomedical Machine Learning Jobs in Missouri

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.

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.

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

●       Demonstrated commitment to continuous learning in emerging ML fields, such as LLMs and GenAI application architectures.

• 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