Machine Learning Engineer (with Vertex AI Experience)

Tiger Analytics; United States; Sur place; USD 120 000 - 150 000; Plein temps

Avantages offerts par ce poste

Career development opportunities

Entrepreneurial environment

Résumé du poste

A leading data analytics company in the United States is seeking a skilled Machine Learning Engineer to design, build, and deploy scalable ML solutions. The role involves developing and optimizing models using Google Cloud Platform and Vertex AI, collaborating with data teams, and monitoring performance. Candidates should have strong Python skills and experience in ML libraries. This position offers significant career development opportunities in a fast-growing and entrepreneurial environment.

Qualifications

• Hands-on experience with Google Cloud Platform (GCP) and Vertex AI.
• Strong proficiency in Python and ML/DL libraries.
• Experience in building and deploying scalable ML solutions.

Responsabilités

• Develop and optimize ML models using Vertex AI.
• Design and implement scalable ML pipelines.
• Collaborate with teams to enable reproducible ML workflows.
• Monitor model performance and implement governance.

Connaissances

Machine Learning Engineering

Google Cloud Platform (GCP)

Vertex AI

Python

TensorFlow

PyTorch

RESTful API development

Outils

Vertex AI Pipelines

Cloud Build

BigQuery

Dataflow

FastAPI

Cloud Functions

GitOps

Description du poste

Tiger Analytics is looking for a skilled and innovative Machine Learning Engineer with hands‑on experience in Google Cloud Platform (GCP) and Vertex AI to design, build, and deploy scalable ML solutions. You will play a key role in operationalizing machine learning models and driving the end-to-end ML lifecycle, from data ingestion to model serving and monitoring.

Key Responsibilities

• Develop, train, and optimize ML models using Vertex AI, including Vertex Pipelines, AutoML, and custom model training.
• Design and build scalable ML pipelines for feature engineering, training, evaluation, and deployment.
• Deploy models to production using Vertex AI endpoints and integrate with downstream applications or APIs.
• Collaborate with data scientists, data engineers, and MLOps teams to enable reproducible and reliable ML workflows.
• Monitor model performance and set up alerting, retraining triggers, and drift detection mechanisms.
• Utilize GCP services such as BigQuery, Dataflow, Cloud Functions, Pub/Sub, and GCS in ML workflows.
• Apply CI/CD principles to ML models using Vertex AI Pipelines, Cloud Build, and GitOps practices.
• Implement model governance, versioning, explainability, and security best practices within Vertex AI.
• Document architecture decisions, workflows, and model lifecycle clearly for internal stakeholders.

Advanced Generative AI

1. Advanced RAG including Graph based hybrid retrieval
2. Multimodal agent

Python Expertise

1. Expert in Python with strong OOP and functional programming skills
2. Proficient in ML/DL libraries: TensorFlow, PyTorch, scikit-learn, pandas, NumPy, PySpark
3. Experience with production‑grade code, testing, and performance optimization

GCP Cloud Architecture & Services

• Vertex AI
• BigQuery
• Cloud Storage
• Cloud Run
• Cloud Functions
• Pub/Sub
• Dataproc
• Dataflow
• Understanding of IAM, VPC

API Development & Integration

• Designs and builds RESTful APIs using FastAPI or Flask
• Integrates ML models into APIs for real‑time inference
• Implements authentication, logging, and performance optimization

System Design & Scalability

• Designs end‑to‑end AI systems with scalability and fault tolerance in mind
• Hands‑on experience in developing distributed systems, microservices, and asynchronous processing

Benefits

Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast‑growing, challenging, and entrepreneurial environment, with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.