Machine Learning Engineer

Machine Learning Engineer

REMOTE

GC and USC

The ideal candidate has hands-on experience with Large Language Models (LLMs) and is highly skilled in Google Cloud Platform (GCP), specifically Vertex AI. This is not a generic ML engineering role—it requires deep expertise in designing, deploying, and managing LLM-powered applications in production environments.

REQUIRED

3+ years of experience as a Machine Learning Engineer.

Proficiency in Python for ML development.

Hands-on experience with RDBMS and NoSQL databases (e.g., MongoDB, BigQuery, PostgreSQL).

Strong experience with GCP, including Vertex AI for MLOps (training, deployment, monitoring).

Extensive experience with LLMs, including deep understanding of architectures, capabilities, and limitations.

Proven track record of deploying and managing LLM-based solutions in production using Vertex AI.

Experience leveraging Vertex AI Model Garden for model discovery and management.

Ability to develop advanced LLM-powered applications using agentic frameworks such as LangChain or LangGraph.

Understanding of core ML concepts and workflows.

Familiarity with version control systems (e.g., Git).

Nice to Haves:

Familiarity with Azure OpenAI Services and other cloud-based LLM offerings.

Experience with Retrieval-Augmented Generation (RAG) architectures.

Knowledge of NLP beyond LLMs.

Familiarity with big data technologies (Apache Spark, Ray, Dask).

Experience with streaming data platforms (e.g., Apache Kafka, Google Pub/Sub).

Strong analytical and problem-solving skills.

Ability to work collaboratively in a team environment.

Education & Certifications

Bachelor's degree in Computer Science, Engineering, Information Technology, or related field.

Relevant certifications (e.g., Google Professional Data Engineer, Google Cloud ML Engineer, AWS Certified Data Analytics) are a plus.