Machine Learning Engineer

Quantiphi; United States; On-site; USD 90,000 - 130,000; Full time

Benefits offered by this job

Exposure to Fortune 500 companies

Work with cutting-edge AI technologies

Dynamic team environment

Job summary

A global AI and Big Data solutions firm is seeking a skilled Machine Learning Engineer. The role involves designing, training, and deploying ML models using Google Cloud tools, particularly Document AI and Vertex AI. Candidates should hold a relevant degree and possess solid experience in ML development, Python, and API integration. A collaborative environment awaits where you can innovate and excel in your career, supporting top-tier clients worldwide.

Qualifications

• Bachelor’s or Master’s degree in relevant field or equivalent practical experience.
• Proven experience with custom Document AI and pre-trained processors.
• Hands-on experience with Google Cloud Vertex AI.
• Strong understanding of Large Language Models and fine-tuning.
• Experience in model design, training, testing, and evaluation.

Responsibilities

• Design, develop, and fine-tune machine learning models.
• Integrate ML models into production systems via APIs.
• Evaluate model performance and optimize for efficiency.
• Collaborate with cross-functional teams for seamless delivery.

Skills

Expertise in Google Cloud AI tools

Machine Learning model development

End-to-end deployment

Proficiency in Python

Understanding of API integration

Troubleshooting and debugging

Education

Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning

Tools

Google Cloud Document AI

Google Cloud Vertex AI

TensorFlow

PyTorch

scikit-learn

Job description

While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.

If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!

About Quantiphi

Quantiphi is an award‑winning Applied AI and Big Data software and services company, driven by a deep desire to solve transformational problems at the heart of businesses. Our signature approach combines groundbreaking machine‑learning research with disciplined cloud and data‑engineering practices to create breakthrough impact at unprecedented speed.

Company Highlights

• 17x Google Cloud Partner of the Year awards in the last 8 years
• 3x AWS AI/ML award wins
• 3x NVIDIA Partner of the Year titles
• 2x Snowflake Partner of the Year awards
• We have also garnered Top analyst recognitions from Gartner, ISG, and Everest Group.
• We offer first‑in‑class industry solutions across Healthcare, Financial Services, Consumer Goods, Manufacturing, and more, powered by cutting‑edge Generative AI and Agentic AI accelerators.
• We have been certified as a Great Place to Work for the third year in a row‑ 2021, 2022, 2023.

Be part of a trailblazing team that’s shaping the future of AI, ML, and cloud innovation. Your next big opportunity starts here!

Job Overview

We are looking for a Machine Learning Engineer with strong expertise in Google Cloud AI tools, ML model development, and end‑to‑end deployment. The ideal candidate will have hands‑on experience with Google Cloud Document AI, Vertex AI, and Large Language Models (LLMs). You will be responsible for designing, training, evaluating, and fine‑tuning ML models, integrating them with cloud‑based applications, and ensuring scalable and reliable performance in production environments.

Key Responsibilities

• Design, develop, train, and fine‑tune machine learning models, including custom and pre‑trained models on Google Cloud Vertex AI and Document AI.
• Build and manage custom Document AI processors such as Custom Document Splitter, Custom Document Classifier, and Custom Document Extractor.
• Work with pre‑trained Document AI processors and customize them for business‑specific document understanding tasks.
• Develop and deploy ML solutions using GCP services like Cloud Functions, Cloud Run, Firestore, Cloud SQL, Cloud Storage, and BigQuery.
• Design and implement data preprocessing pipelines for large‑scale, unstructured, and semi‑structured data.
• Integrate ML models into production systems via secure and scalable APIs.
• Evaluate model performance using standard ML metrics, perform model validation, and optimise for accuracy, latency, and efficiency.
• Collaborate with cross‑functional teams (Data Engineers, Software Developers, and Product Teams) to ensure seamless model integration and delivery.
• Troubleshoot and debug ML pipelines, training jobs, and model deployment issues.
• Maintain proper version control of code, models, and configurations using Git/GitHub.
• Follow best practices for ML lifecycle management, testing, and documentation.

Basic Qualifications (Essential)

• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field, or equivalent practical experience.
• Proven experience with Google Cloud Document AI (Custom Workbench: Splitter, Classifier, Extractor, and pre‑trained processors).
• Hands‑on experience with Google Cloud Vertex AI for model training, tuning, and deployment.
• Strong understanding and practical experience with Large Language Models (LLMs) and their fine‑tuning.
• Proficiency in Python and ML libraries/frameworks (e.g., TensorFlow, PyTorch, scikit‑learn).
• Experience with ML model design, training, testing, evaluation, and fine‑tuning.
• Solid experience in data preprocessing and feature engineering.
• Familiarity with GCP services such as Cloud Functions, Cloud Run, Firestore, Cloud Storage, Cloud SQL, and BigQuery.
• Strong understanding of API integration for ML model deployment.
• Proficiency in troubleshooting and debugging ML‑related issues.
• Experience with Git/GitHub for version control and collaboration.

Other Qualifications (Good To Have)

• Knowledge of MLOps practices for automating ML workflows, model versioning, and continuous deployment.
• Experience building and exposing ML models via FastAPI or similar frameworks.
• Familiarity with data pipeline orchestration tools (e.g., Airflow, Kubeflow).
• Understanding of security and compliance best practices in ML systems.
• Strong analytical, problem‑solving, and communication skills.

What Is In It For You

• Be part of the fastest‑growing AI‑first digital transformation and engineering company in the world
• Be a leader of an energetic team of highly dynamic and talented individuals
• Exposure to working with fortune 500 companies and innovative market disruptors
• Exposure to the latest technologies related to artificial intelligence and machine learning, data and cloud

If you like wild growth and working with happy, enthusiastic over‑achievers, you’ll enjoy your career with us!