Machine Learning Engineer
@ Trilogy

Hybrid
$100,000
Hybrid
Full Time
Posted 1 day ago

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Job Details

Overview

Trilogy is seeking a Machine Learning Engineer to leverage mastery of LLMs and drive productivity. This role focuses on designing and building AI-driven tools to streamline workflows and automate tasks. Your work will have a direct impact on improving efficiency and shaping the future of productivity tools.

What You Will Be Doing

You will design high-quality AI automations, experiment with state-of-the-art AI tools like GPT-4 Vision and Amazon CodeWhisperer, and optimize AI solutions deployed across various infrastructures including AWS.

What You Won’t Be Doing

You will not engage in traditional coding or repetitive tasks. Instead, you will focus on innovation and strategic problem solving using AI as your primary tool.

Key Responsibilities

  • Architect and deploy fully-automated AI systems.
  • Integrate Generative AI solutions for scalable impact.

Basic Requirements

  • AI-first mindset with at least 5 years professional experience.
  • Proficiency in Python and AWS.
  • Experience with GenAI code assistants and LLM APIs.

About Trilogy

Trilogy has been innovating for three decades with a focus on finding top talent, driving technology innovation, and incubating new business models using modern cloud-based stacks.

Working with Us

This full-time position is available immediately on a contractor basis through Crossover. Compensation is $50 USD/hour, equating to $100,000 USD/year with weekly payments.

Key skills/competency

  • LLMs
  • AI Automation
  • Python
  • AWS
  • Generative AI
  • GPT-4 Vision
  • Amazon CodeWhisperer
  • Scalability
  • Innovation
  • Architecture

How to Get Hired at Trilogy

🎯 Tips for Getting Hired

  • Customize Resume: Tailor skills to match Trilogy requirements.
  • Highlight Experience: Emphasize LLMs and AI tool expertise.
  • Research Trilogy: Understand their innovations and culture.
  • Prepare for Interviews: Review technical and scenario questions.

📝 Interview Preparation Advice

Technical Preparation

Review LLM API documentation.
Practice Python and AWS integration.
Test AI automation projects.
Study state-of-art AI tools.

Behavioral Questions

Describe a challenge using AI innovations.
Explain remote team collaboration experiences.
Discuss handling complex, non-repetitive tasks.
Share experiences in automated solution deployments.

Frequently Asked Questions