Location: United States – Remote
Employment Type: Full-Time and Contract
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.
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.
● Hands-on
experience with modern ML platform stacks, such as Databricks MLOps Stacks.
● 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
Skills Required
- 4+ years of hands-on professional experience developing, deploying, and managing Machine Learning models.
- 3+ years of experience in a customer-facing consulting or solutions architect role.
- Excellent verbal and written communication skills for effective client and internal team interaction.
- Expertise in MLOps lifecycle management, including model versioning, testing, and monitoring.
- Demonstrable experience with infrastructure management, encompassing containerization (Docker).
- Deep understanding of programming for data-intensive and scalable ML applications.
- Proven experience in deploying and managing Generative AI and NLP solutions.
What We Do
Koantek is a Databricks-exclusive system integrator focused on enterprise-scale data and AI transformation, helping clients modernize, migrate, and scale AI solutions.
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