Job Information
Apex Systems, Inc Software - Machine Learning Engineer - 3026858 in Dearborn, Michigan
Job#: 3026858
Job Description:
AI / ML Engineer
Role Overview
Apex Systems is seeking an AI / ML Engineer to help build and operationalize machine learning capabilities in a production environment. This role focuses on model development, deployment, and agent-based systems, with a strong emphasis on MLOps. While the client does not yet have a fully mature MLOps platform, this engineer will play a key role in shaping, standing up, and evolving those practices.
This position is ideal for someone who enjoys building systems from the ground up, working in environments where tooling and standards are still emerging, and directly impacting how ML is operationalized at scale.
Position Details
Compensation: $70--80/hour (negotiable)
Location: Dearborn, MI
Benefits: Access to health, dental, vision, and 401(k)
How to Apply: Apply through this posting or send your resume to Sam Wade, Sr. Professional Recruiter at [email protected]{target="_blank" rel="noopener"} with the subject line "AI / ML Engineer."
Role Focus & Responsibilities
50% -- ML Model Development
- Build and develop machine learning models using PyTorch
- Work with real-time data to solve production-level problems
- Apply ML techniques to real-world use cases
- Collaborate closely with data engineers on data inputs and pipelines
50% -- Agents & ML Enablement
- Develop and support agent-based systems within GCP
- Support and enhance the broader data and ML ecosystem
- Work with prompt engineering
Help operationalize and enable ML workflows across the organization
Technology & Platform Environment
- Programming Language: Python
- Model Development: PyTorch
- Deployment & Orchestration: Vertex AI
- Cloud Platform: Google Cloud Platform (GCP)
- Data: Real-time data processing
Candidates do not need to be GCP experts on day one, but must have prior production ML experience.
MLOps Expectations
This role is well-suited for someone who:
- Has deployed machine learning models into production environments
- Understands core MLOps concepts, including:
- Model versioning
- Monitoring
- Retraining
- Data drift
Is comfortable working in environments where:
- Tooling is still evolving
- Standards are being defined
They are helping build the runway, not just using it
Education & Background Flexibility
The client is open to candidates from a variety of backgrounds, including:
Master's candidates from top programs, provided you have:
- Hands-on machine learning experience
Exposure to production-level systems
Ideal Candidate Profile
The ideal candidate:
Has built ML models using PyTorch
Has deployed ML models into production
Possesses