Sr AI Engineer / Data Scientist

Location: United States – Remote
Employment Type: Full-Time and Contract

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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.

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

Requirements

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.

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

Benefits

• 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