Senior Machine Learning Platform Engineer

Senior Machine Learning Platform Engineer

About Crown Point Technologies, LLC

Crown Point Technologies, LLC is an Economically Disadvantaged Women-Owned Small Business (EDWOSB) dedicated to providing critical full-stack software development and data engineering solutions and services to both Government and commercial clients.Proudly based in Maryland, our small business is dedicated to serving customers in a variety of domains including DoD, Federal Health, Life Sciences, Financial Services, and Manufacturing.

Description

Position Overview

We are seeking an experienced data and modeling engineer to support the development and deployment of enterprise-scale predictive modeling solutions. The ideal candidate will have strong experience developing Python-based predictive models and building orchestration pipelines that integrate multiple models into governed, production-ready workflows. This role will also support the enablement of data scientists by implementing and maintaining modeling, orchestration, and visualization platforms that facilitate scalable analytics and decision-making.

The ideal candidate also has strong experience with modern data architectures, including data modeling, ETL/ELT pipelines, relational and NoSQL databases, streaming data platforms, and semantic technologies such as ontologies, RDF, and graph databases. The role requires close collaboration with stakeholders, architects, and engineers to define requirements, prioritize work, and deliver scalable, mission-aligned data solutions.

Key Responsibilities

• Develop and implement data-driven predictive models, with a primary focus on Python-based model development.
• Design and build complex orchestration pipelines that chain together predictive models and analytics workflows across enterprise environments.
• Implement solutions that support model governance, versioning, traceability, and change management.
• Work with off-the-shelf modeling, orchestration, and visualization platforms (e.g., RapidMiner, KNIME, Dataiku, Databricks, or similar) to support scalable analytics workflows.
• Act in an enablement role, supporting and empowering data scientists and analysts to effectively use enterprise modeling platforms in their daily work.
• Design and support modern data architectures, including data modeling, ETL/ELT pipelines, and integrations across relational, NoSQL, and streaming data platforms.
• Work with semantic technologies and knowledge of graph frameworks, including ontologies, RDF, and graph databases, to support advanced data integration and reasoning capabilities.
• Collaborate with cross-functional teams including data scientists, engineers, architects, and stakeholders to define requirements, prioritize development efforts, and deliver scalable solutions.
• Support best practices for model lifecycle management, reproducibility, and deployment.

Required Qualifications

• Strong experience developing predictive models using Python.
• Experience building enterprise-level orchestration pipelines that integrate multiple predictive models or analytics workflows.
• Experience implementing governance, version control, and change management for data science or modeling pipelines.
• Experience working with commercial or open-source modeling and orchestration platforms (e.g., RapidMiner, KNIME, Dataiku, Alteryx, Databricks, or similar).
• Experience designing or working with modern data architectures, including ETL/ELT pipelines and distributed data platforms.
• Experience working with relational, NoSQL and/or RDF Graph databases.
• Familiarity with semantic technologies such as ontologies, RDF, and graph databases.
• Experience supporting data science teams in an enablement or platform engineering role.
• Strong collaboration and communication skills in cross-disciplinary environments.

Preferred Qualifications

• Experience with mechanistic or physics-based modeling approaches.
• Domain experience in pharmaceuticals, biotechnology, or life sciences.

Salary

$150,000 - $185,000 per year