Silver.devAceUp - Machine Learning Engineer (Generative AI & LLM Focus)
About the companyAceUp is evolving from a traditional SaaS platform into an AI-first leadership development engine.
We are looking for a Machine Learning Engineer who is passionate about Generative AI. You will work closely with our Lead ML Engineer and Product team to turn high-level architectural designs into functioning, production-ready AI features. This is a hands-on coding role where you will live in Python and Vertex AI.
The Tech Stack:
We are a GCP-native shop. You will be building directly within the Google Cloud ecosystem:
GenAI & Compute: Vertex AI, Gemini Pro/Ultra, PaLM API, Cloud Functions.
Data & Vector: Firestore, BigQuery, Vertex AI Vector Search.
Orchestration: Cloud Run, Pub/Sub.
Frameworks: Python, LangChain/LangGraph.
What You Will Do:
Build & Optimize LLM Workflows: Implement the specific prompt chains and logical flows that power our conversational agents. You will iterate on system instructions to improve model tone, accuracy, and compliance.
Develop RAG Retrievers: Write the code that chunks, embeds, and indexes our proprietary content. You will fine-tune retrieval queries to ensure the AI always has the right context.
Python Backend Development: Build the robust Python services and APIs (using frameworks like FastAPI or GCP Cloud Functions) that wrap our AI models and expose them to the Full Stack team.
Model Evaluation: Create and run evaluation datasets (“Golden Sets”) to measure the performance of our models. You will be responsible for catching hallucinations or regressions before they reach the user.
Data Processing Pipelines: Write efficient scripts to clean and structure unstructured data (text logs, transcripts) for downstream analysis.
Collaborate on Architecture: Work with the Lead ML Engineer to prototype new ideas. You will be the “first implementer” validating if a new approach (like a specific agentic framework) actually works in practice.
Who You Are:
A Strong Python Developer: You write clean, modular, and testable Python code. You are comfortable with async programming and type hinting.
GenAI Curious: You have likely built your own projects using OpenAI APIs or LangChain. You understand concepts like “Context Window,” “Temperature,” and “Embeddings” intuitively.
Problem Solver: You don’t just blame the model when it fails; you investigate the data, the prompt, and the retrieval logic to find the root cause.
Team Player: You are ready to collaborate with Full Stack engineers to define the JSON contracts and APIs they need to integrate your models.
Requirements:
Experience: 3+ years of professional software engineering experience.
ML Experience: 1+ years of experience working with Machine Learning or Data Engineering pipelines.
LLM Exposure: Demonstrated experience (professional or significant side projects) working with LLM APIs (OpenAI, Anthropic, or Vertex AI).
Cloud Experience: Familiarity with a cloud provider (GCP preferred, AWS/Azure acceptable).
Language: Conversational English is required.
Education: B.S. in Computer Science, Mathematics, or related field.
Nice to Haves:
Experience with LangChain or LlamaIndex.
Experience using Firebase/Firestore.
Understanding of basic DevOps (Docker, CI/CD).
AceUp is proud to be an equal opportunity employer, seeking to create a welcoming and diverse environment.
Interview process:
Silver Screening interview
Take Home Challenge
First meeting with client: Intro Intro Call + Problem Solving
Technical Interview
Interview w/Product