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Senior AI Engineer / Data Scientist

  • Job type Posted on: Jun 26, 2026
  • Experience level Koantek
  • Employment type Chandler, Arizona
  • Employment type Onsite
  • Salary Full-time

Job Title :

Senior AI Engineer / Data Scientist

Job Type :

Full-time

Job Location :

Chandler Arizona United States

Remote :

No

Jobcon Logo Job Description :

Chandler, United States | Posted on 06/23/2026 Location: United States (Remote) Employment Type: Full-Time / Contract Experience Level: Senior Overview 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. #J-18808-Ljbffr

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Jobcon Logo Position Details

Posted:

Jun 26, 2026

Reference Number:

14660_69A556576E23F9CDD6E82887FDB4BE49

Employment:

Full-time

Salary:

Not Available

City:

Chandler

Job Origin:

APPCAST_CPC

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Chandler, United States | Posted on 06/23/2026 Location: United States (Remote) Employment Type: Full-Time / Contract Experience Level: Senior Overview 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. #J-18808-Ljbffr

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