Description:

Federato is seeking a Machine Learning Engineer to join their remote team, focusing on enhancing their AI/ML-driven platform for the insurance industry.
The role involves quickly deploying and testing the current LLM-powered pipeline for specific customer use cases, ensuring alignment with customer requirements, and documenting findings clearly.
The engineer will take ownership of deploying product improvements based on customer-specific requests, pushing code and configuration changes to GitHub, and collaborating closely with product and engineering teams for smooth integration.
Responsibilities include building and maintaining a repository of prompts for various scenarios for prospective customer proof of concept, iterating on these to optimize performance and ensure they are production-ready.
The engineer will lead technical PoC projects with prospective customers, showcasing the capabilities of the ML models, addressing specific needs, and gathering feedback for future improvements.
Continuous monitoring of deployed models is essential, focusing on improving accuracy and performance within a structured ML framework while learning best practices for pipeline maintenance.

Requirements:

Candidates must have proven experience as a Machine Learning Engineer or in a similar role, with at least 6 months of relevant internship experience focused on building and benchmarking models.
Practical experience in applying machine learning techniques through coursework, internships, or personal projects is required, ideally with exposure to NLP models, prompt engineering, and working with LLMs using frameworks like Hugging Face or OpenAI.
Familiarity with version control (Git), CI/CD pipelines, and deploying ML models or services locally or in cloud environments is essential, along with knowledge of GitHub for collaboration and maintaining codebases.
Proficiency in Python for building and testing ML models is necessary, with experience using popular ML and data libraries such as TensorFlow, PyTorch, Scikit-learn, Pandas, and NumPy.
Candidates should demonstrate enthusiasm for customer-facing work, with the ability to understand specific use cases and adjust ML models accordingly, while being proactive in learning deployment best practices and taking responsibility for PoCs and prompt engineering tasks.

The position offers a competitive salary range of $120,000 - $150,000 a year, with final offer amounts determined by multiple factors including candidate location, experience, and expertise.
The total compensation package includes stock options, benefits, and additional perks.
Federato emphasizes a culture fit, valuing fast-paced work, user feedback, problem-solving from first principles, and a fun work environment.
The company is an equal-opportunity employer, valuing diversity and providing reasonable accommodations for individuals with disabilities during the job application or interview process.