AI/ML Engineer

ConglomerateIT LLC; Dallas (TX); Remote; USD 120,000 - 160,000; Full time

Job summary

ConglomerateIT LLC is seeking an AI/ML Engineer to design and deploy end-to-end ML pipelines remotely. The role requires deep Python expertise and hands-on experience with AWS data tools for processing large datasets.

You will work on ML model development using SAS analytics, implement MLOps practices, and contribute to scalable AI platforms while collaborating with global teams in a remote setup.

Qualifications

• Hands-on experience building end-to-end ML pipelines, including data prep and feature engineering.
• Strong Python coding with Pandas, NumPy, Scikit-learn, TensorFlow, and PyTorch.
• Practical work with AWS data tools: S3, Glue, Athena, Spark for large datasets processing.
• Deep knowledge of AWS ML services, especially SageMaker, SageMaker Pipelines, Feature Store, and model deployment.
• Track record of building ML models using supervised and unsupervised methods, predictive analytics, and statistical techniques.
• Background with SAS for analytics and ML in large enterprise settings.
• MLOps know-how covering CI/CD, monitoring, retraining, and production support.
• Ability to own technical design from build to deployment with minimal supervision.

Tools

Python

Pandas

NumPy

Scikit-learn

TensorFlow

PyTorch

AWS SageMaker

SageMaker Pipelines

Feature Store

Spark

SAS

Kafka

Step Functions

Job description

AI/ML Engineer (Remote)

What you'll need:

• Hands-on experience building end-to-end ML pipelines, with solid skills in data prep, feature engineering, and core data engineering
• Strong Python coding, using libraries like Pandas, NumPy, Scikit-learn, TensorFlow, and PyTorch
• Practical work with AWS data tools such as S3, Glue, Athena, and Spark for processing large datasets
• Deep knowledge of AWS ML services, mainly SageMaker, SageMaker Pipelines, Feature Store, and model deployment
• A track record of building ML models using supervised and unsupervised methods, predictive analytics, and statistical techniques
• Background in SAS for analytics and ML, including building, validating, and deploying models in large enterprise settings
• MLOps know-how covering the full model lifecycle: CI/CD, monitoring, retraining, and supporting models in production
• Ability to own technical design through build, deployment, and delivery with little supervision

Good to have:

• Experience creating reusable ML platforms, feature stores, and company-wide AI/ML solutions
• Familiarity with model explainability, Responsible AI, observability, and ML governance
• Knowledge of real-time streaming and event-driven setups using Kafka, Kinesis, Lambda, and Step Functions
• Experience with cloud-native APIs, microservices, and connecting enterprise apps on AWS

Founded in 2014, ConglomerateIT is a global leader in delivering innovative IT solutions and services. Headquartered in the USA with a presence in the UK, Canada, and India, we specialize in offering industry-leading expertise and cutting-edge products that help our clients maximize their technological investments. Our focus on best-in-class solutions, a highly knowledgeable team, and proactive talent mapping ensure we remain at the forefront of the IT industry.

ConglomerateIT is driven by our Center for Excellence and Innovation, an initiative dedicated to keeping us ahead in a rapidly evolving technology landscape. We understand that building strong relationships is key to our success, and this commitment has enabled us to partner with Fortune 500 companies and leading system integrators worldwide. Our ability to provide local talent on a global scale ensures that we can meet the contingent project requirements of our clients efficiently and effectively.