Senior AI Engineer / Data Scientist [Remote]

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Location: United States (Remote)
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Employment Type: Full -Time / Contract
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Experience Level: Senior
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About the Role:
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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.
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You will design, deploy, and maintain production -grade ML solutions, including advanced Generative AI and NLP models, for our diverse client base.
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Key Responsibilities:
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* Technical Consulting: Lead end -to -end ML implementations directly with clients, translating business problems into robust technical solutions.
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* MLOps and Pipelines: Design, build, and maintain production -grade ML pipelines with a strong focus on CI/CD, automation, and scalability.
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* GenAI and NLP Deployment: Implement and optimize cutting -edge Generative AI applications (such as LLMs and RAG) in live production settings.
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* Infrastructure and Data Scale: Manage underlying infrastructure using Docker, pipeline orchestrators, and distributed computing frameworks like Apache Spark.
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* Stakeholder Management: Clearly communicate technical findings, proposals, and project status to both technical and non -technical audiences.
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Required Qualifications:
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* 4+ years of professional experience developing, deploying, and maintaining ML models in a live production environment (Mandatory).
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* 3+ years of experience in a customer -facing consulting or Solutions Architect role.
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* Strong expertise in the MLOps lifecycle (model versioning, testing, monitoring, and automated deployment).
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* Solid hands -on experience with containerization (Docker) and data pipeline orchestration.
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* Proven track record of deploying Generative AI and NLP solutions for client applications.
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* Excellent verbal and written communication skills.
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Preferred Qualifications:
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* Hands -on experience with modern ML platform stacks, specifically Databricks MLOps Stacks.
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* Deep knowledge of large -scale data processing and distributed machine learning techniques.
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* A strong commitment to continuous learning in emerging ML fields and GenAI application architectures.
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