Sr. AI Solutions Engineer - MarTech

Insight Global

Smyrna, United States of America

5 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Languages

English

Experience level

Senior

Job location

Smyrna, United States of America

Tech stack

Artificial Intelligence

Airflow

Amazon Web Services (AWS)

Data analysis

Systems Engineering

Azure

Databases

Continuous Integration

ETL

Python

Machine Learning

Natural Language Processing

TensorFlow

Enterprise Software Applications

PyTorch

Delivery Pipeline

Large Language Models

Deep Learning

Containerization

AI Platforms

Kubernetes

Infrastructure Automation Frameworks

Information Technology

Data Analytics

GraphQL

Machine Learning Operations

Api Design

Automation Anywhere

Docker

Job description

The AI Systems & Machine Learning Solutions Engineer is responsible for the end-to-end lifecycle of artificial intelligence solutions, from designing custom machine learning models to architecting the automation systems that integrate these models into production environments. This individual will analyze complex business requirements to propose and build automated workflows, ensuring that AI-driven insights are seamlessly delivered through scalable technical platforms. The role requires a unique blend of statistical modeling and systems engineering to optimize operational efficiency and drive innovation.

Major Tasks, Responsibilities & Key Accountabilities

25% - Model Development & Training: Designs and builds custom, re-usable machine learning models (NLP, LLMs, Predictive Analytics) based on statistical modeling and data analysis to solve specific business challenges.
25% - Systems Automation & Integration: Architect and develop automated pipelines and ETL jobs to manage the flow of data between AI models and enterprise applications, ensuring intuitive and efficient integration.
25% - MLOps & Infrastructure Maintenance: Maintain comprehensive documentation for AI workflows and manage the deployment infrastructure (CI/CD, containerization) to ensure the stability and scalability of automated AI systems.
25% - Technical Leadership & Strategy: Act as the technical lead for AI initiatives, working with senior leadership and stakeholders to translate business obstacles into technical requirements and actionable AI roadmaps.

Requirements

The knowledge, skills, and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in Computer Science, Data Science, Artificial Intelligence, or a related field.

Years of Relevant Work Experience

4+ years in a role focused on Machine Learning development or Systems Automation.

Preferred Qualifications

Proven experience as an AI/ML Engineer and/or Systems Automation Engineer.
Expertise in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) and automation tools (e.g., LangChain, Airflow).
Background in MLOps, including containerization (Docker/Kubernetes) and cloud-native AI services (AWS SageMaker, Azure AI, or GCP Vertex AI).
Knowledge of SQL queries, API design (REST/GraphQL), and database management systems.
Analytical mind with a problem-solving aptitude and the ability to take initiative in an innovative environment.

Knowledge, Skills, Abilities and Competencies