Machine Learning Engineer

Pyramid Consulting, Inc; Town of Texas (WI); Hybrid; USD 89,544 - 96,432; Part time

Benefits offered by this job

Health insurance

401(k) plan

Paid sick leave

Job summary

A leading consulting agency is seeking a Machine Learning Engineer in Texas for a 12-month hybrid contract. The role requires experience with agent orchestration, AWS services, and developing machine learning models for production. Responsibilities include managing ML pipelines and collaborating with data scientists. Competitive pay of $65 to $70 per hour with benefits such as health insurance and a 401(k) plan. Immediate application encouraged.

Qualifications

• Strong experience with agent orchestration frameworks.
• Hands-on experience developing and deploying ML models.
• Proficiency with AWS services like S3 and SageMaker.

Responsibilities

• Productionize machine learning and GenAI models.
• Design and implement end-to-end ML pipelines.
• Collaborate with data scientists for model operationalization.

Skills

Agent orchestration frameworks

AWS services

CI/CD practices

Software engineering

Model monitoring

SQL proficiency

Job description

Immediate need for a talented Machine Learning Engineer. This is a 12 Months Contract opportunity with long-term potential and is located in Westlake, TX(Hybrid). Please review the job description below and contact me ASAP if you are interested.

Job Diva ID: 26-04258

Pay Range: $65 - $70/hour. Employee benefits include, but are not limited to, health insurance (medical, dental, vision), 401(k) plan, and paid sick leave (depending on work location).

Key Responsibilities

• Productionize machine learning and GenAI models into scalable, high-availability services
• Design and implement end-to-end ML pipelines including training, deployment, monitoring, and lifecycle management
• Build and manage agent-based workflows using modern orchestration frameworks
• Collaborate with data scientists to operationalize models and support ongoing evaluation and improvement
• Ensure robust monitoring, logging, and performance tracking for deployed models
• Apply DevOps and MLOps best practices to support scalable ML deployments

Key Requirements and Technology Experience

• Strong experience with agent orchestration frameworks such as LangChain, CrewAI, LangGraph, AutoGen, or similar
• Hands-on experience developing, deploying, and supporting statistical and machine learning models in production
• Proficiency with AWS services including S3, Lambda, ECS, SageMaker, and related cloud infrastructure
• Experience with CI/CD, DevOps, and MLOps practices
• Strong software engineering background with a focus on scalable system design
• Experience managing multiple models in production environments
• Strong understanding of model monitoring, drift detection, and performance optimization
• Ability to work cross-functionally with engineering, data science, and platform teams
• Candidates should be prepared to discuss:
• End-to-end ML development, deployment, and production monitoring
• Designing scalable architectures for deploying dozens of ML models
• Strategies for persisting predictions and ML lifecycle data for evaluation and governance
• Diagnosing and responding to model drift
• SQL proficiency and best practices when operationalizing data science logic

Our client is a leading Financial Industry, and we are currently interviewing to fill this and other similar contract positions. If you are interested in this position, please apply online for immediate consideration.

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