Machine Learning Engineer

Brooksource

United States

On-site

USD 89,544 - 96,432

Full time

14 days+

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Job summary

A leading tech staffing firm in the United States is seeking an AI/ML Engineer to develop and optimize generative AI solutions. The role involves prompt engineering, collaboration with subject matter experts, and monitoring model performance. Ideal candidates will have extensive experience in relevant technologies and a solid understanding of AI applications. This is a full-time position with a competitive pay range of $65-$70 per hour.

Qualifications

Solid experience in business analytics, data science, software development, and data engineering.
Expertise in Python and frameworks such as PyTorch, TensorFlow, or ONNX.
Hands-on experience working with LLMs and Generative AI, including model development and inference patterns.

Responsibilities

Scope, develop, expand, operate, and maintain scalable, reliable and safe generative AI solutions.
Design and execute prompt engineering experiments to optimize Large Language Models (LLMs).
Collaborate with SMEs to evaluate prompt effectiveness and align AI solutions with business needs.

Skills

Business analytics

Data science

Software development

Data engineering

Python

PyTorch

TensorFlow

ONNX

LLMs

Generative AI

Job description

Overview

IT/ Engineering Recruiter | Connecting IT Professionals with Industry-Leading Opportunities

This range is provided by Brooksource. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$65.00/hr - $70.00/hr

Role description

Our Fortune 50 Healthcare Insurance client is seeking a highly skilled AI/ML Engineering resource to play a pivotal role in the development, expansion, operation, and maintenance of generative AI solutions. The primary responsibilities include running an experimental framework to determine the optimal prompt engineering approaches, tuning prompts, and collaborating with subject matter experts (SMEs) for evaluations and results. This role requires a deep understanding of evaluating models output in production, particularly when ground metrics are absent, monitoring for issues such as model drift and hallucinations, and optimizing for offline and online metrics.

Key Responsibilities

Scope, develop, expand, operate, and maintain scalable, reliable and safe generative AI solutions.
Design and execute prompt engineering experiments to optimize Large Language Models (LLMs) for various use cases.
Collaborate with SMEs to evaluate prompt effectiveness and align AI solutions with business needs.
Understand and apply offline and online evaluation metrics for LLMs, ensuring continuous model improvements.
Evaluate production models using live data in the absence of ground metrics, implementing robust monitoring systems.
Monitor LLM applications for model drift, hallucinations, and performance degradation.
Ensure smooth integration of LLMs into existing workflows, providing real-time insights and predictive analytics.

Qualifications

Solid experience in business analytics, data science, software development, and data engineering.
Expertise in Python and frameworks such as PyTorch, TensorFlow, or ONNX.
Hands-on experience working with LLMs and Generative AI, including model development and inference patterns.
Proven ability to design scalable systems leveraging LLMs, particularly in distributed computing environments.

Preferred Skills

Experience in prompt engineering and prompt optimization.
Expertise in running experiments to evaluate generative AI performance.
Knowledge of production-level monitoring tools for ML models, including drift detection and mitigation strategies.
Excellent problem-solving skills and ability to work cross-functionally with data scientists, engineers, and SMEs.
Experience with safety, security and responsible use of AI.
Experience with red-teaming (adversarial testing) of generative AI.
Experience with developing AI applications with sensitive data such as PHI, PII and highly confidential data.

Seniority level