Senior AI Engineer / Data Scientist
Chandler, Arizona, United States
- Pay
- Pay not listedSimilar roles state $165K–$240K
- Work setting
- Not stated
- Employment
Full-time · Contract — employment source
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.
Employment type in the employer’s posting: Contract
From the employer’s posting
What you’ll work on
Full postingLead end-to-end ML implementations directly with clients
Design, build and maintain production ML pipelines with CI/CD
Implement and optimize GenAI applications such as LLMs and RAG in production
Manage infrastructure with Docker, orchestrators and Apache Spark
Communicate technical findings and project status to varied audiences
From the employer’s posting
Lead end-to-end ML implementations directly with clients
Design, build, and maintain production-grade ML pipelines with a strong focus on CI/CD, automation, and scalability.
Implement and optimize cutting-edge Generative AI applications (such as LLMs and RAG) in live production settings.
Manage underlying infrastructure using Docker, pipeline orchestrators, and distributed computing frameworks like Apache Spark.
Clearly communicate technical findings, proposals, and project status to both technical and non-technical audiences.
Tools in this posting
- Databricks
- Docker
- Spark
Source — Tool mentions in context
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.
Posting record
Report an errorOpen 4 monthsWe first saw this posting 124 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jun 27, 2026 · 124 days ago
- Recorded sightings
- 88
- Last seen by us
- Oct 28, 2026
- Employer says posted
- Jun 23, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
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.
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Chandler, Arizona, United States
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