Sr. Machine Learning Engineer - Search

Pento Careers; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Pento Careers in the United States is seeking a hands-on ML Engineer to build and operate machine learning systems and AI features from experimentation to production deployment and monitoring. The role combines classic ML methods with deep learning and language model applications for reliable, scalable solutions.

You will work closely with backend and data engineering teams to deliver end-to-end pipelines, integrate models, and ensure production observability and fairness.

Qualifications

• At least three years of professional ML/AI engineering experience, shipping models to production.
• Strong knowledge of supervised/unsupervised learning, feature engineering, model evaluation.
• Proficiency in Python and a deep learning framework; PyTorch preferred.
• Experience building APIs with FastAPI, Flask, or Django and cloud tooling.

Responsibilities

• Develop, evaluate, deploy, and maintain ML models and AI-powered features.
• Build end-to-end data pipelines for ingestion, feature engineering, training, and serving.
• Apply language models via prompt design, retrieval-augmented generation, and observability.
• Collaborate with backend and data engineering to integrate models into systems.
• Monitor production performance, reliability, fairness, and contribute to CI/CD practices.

Skills

Python

English

Experiment tracking

CI/CD

Communication

Education

Bachelor's degree in CS or related field

Tools

PyTorch

Docker

FastAPI

Flask

Django

Job description

Role overview

Build and operate machine learning systems and AI features, taking work from experimentation through production deployment and monitoring. The role combines established machine learning methods, deep learning, and language model applications, with a focus on reliable systems that perform at scale.

Responsibilities

• Develop, evaluate, deploy, and maintain models and AI-powered product features.
• Build end-to-end pipelines for data ingestion, feature engineering, training, evaluation, and serving.
• Apply language models through prompt design, retrieval-augmented generation, observability, and orchestration frameworks.
• Work with backend and data engineering colleagues to integrate models into existing systems.
• Monitor production performance, reliability, and fairness, and contribute to experiment tracking, versioning, CI/CD, and observability practices.

Requirements

• At least three years of professional machine learning or AI engineering experience, including shipping systems to production.
• Strong knowledge of supervised and unsupervised learning, feature engineering, and model evaluation.
• Proficiency in Python and a deep learning framework; PyTorch is preferred.
• Experience building and using APIs with a framework such as FastAPI, Flask, or Django.
• Practical experience with language models, such as fine-tuning, retrieval-augmented generation, or AI applications.
• Cloud and machine learning tooling experience, familiarity with Docker and software engineering practices, and advanced written and spoken English.

Nice to have

• Experience with vector databases and semantic search, or a background in NLP, information retrieval, or recommendation systems.
• Familiarity with model evaluation frameworks and responsible AI.