Sr AI Engineer / Data Scientist / MLOps Consultant
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
â 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.
â Exhibit excellent communication, presentation, and
stakeholder management skills to clearly articulate technical findings, proposals, and
project status to both technical and non-technical audiences.
â 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.
â 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.
â Manage underlying solution
infrastructure, demonstrating proficiency in technologies such as Docker,
pipeline orchestrators, and database systems.
â Leverage expertise in
distributed computing frameworks, specifically in scalable machine learning and
high-performance data processing (e.g., using technologies like Apache Spark).
â Contribute to the strategic
growth of the ML Practice Team, including participation in technical
assignments and knowledge transfer activities.
â Ensure all client engagements
and training activities are properly documented and reported via designated
partner platforms.
Required Qualifications
â 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.
â 3+ years of experience in a customer-facing consulting or solutions
architect role, focused on technical implementation and delivery.
â Excellent verbal and written communication skills for effective client and
internal team interaction.
â Expertise in MLOps lifecycle
management, including model versioning, testing, monitoring, and automated
deployment best practices.
â Demonstrable experience with
infrastructure management, encompassing containerization (Docker) and data
pipeline orchestration.
â Deep understanding of
programming for data-intensive and scalable ML applications.
â Proven experience in
deploying and managing Generative AI and NLP solutions for client applications.
Preferred Qualifications
â Hands-on experience with
modern ML platform stacks, such as Databricks MLOps Stacks.
â Knowledge of specific tools
and techniques used in scalable machine learning and large-scale data
processing.
â Demonstrated commitment to
continuous learning in emerging ML fields, such as LLMs and GenAI application
architectures.
â Hands-on experience with
modern ML platform stacks, such as Databricks MLOps Stacks.
â Knowledge of specific tools
and techniques used in scalable machine learning and large-scale data
processing.
â Demonstrated commitment to
continuous learning in emerging ML fields, such as LLMs and GenAI application
architectures.

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