Senior Machine Learning Engineer (Fully Remote)

Harnham; United States; Remote; USD 200,000 - 220,000; Full time

Benefits offered by this job

Competitive salary and bonus structure

Comprehensive health coverage

Generous PTO and company holidays

Flexible remote working options

Job summary

A leading technology firm is seeking a Senior Machine Learning Engineer to build scalable ML infrastructure and deploy production-grade models. This fully remote role requires expertise in PyTorch, Python, and PySpark, along with a strong understanding of CI/CD workflows. The ideal candidate holds an MSc or PhD in a relevant field and has hands-on experience with Databricks. This position offers a competitive salary and comprehensive benefits including health coverage and generous PTO.

Qualifications

• Strong ML engineering with proficiency in PyTorch.
• Hands-on experience with Databricks.
• Expert-level Python and PySpark skills for large-scale data processing.

Responsibilities

• Architect and train neural-network models for optimization and audience modeling.
• Build multi-GPU training pipelines and implement hyperparameter tuning strategies.
• Develop feature-engineering workflows using PySpark.

Skills

ML engineering

Proficiency in PyTorch

Python

PySpark

MLOps

Education

MSc or PhD in Computer Science, Machine Learning, or related field

Tools

Databricks

AWS

Snowflake

Job description

Senior Machine Learning Engineer (Fully Remote)

Base pay range: $200,000.00/yr - $220,000.00/yr

Location: Remote (optional hybrid New York)

Salary up to $220,000

Our client

Our client is a fast-growing, profitable technology business operating at the cutting edge of AI-driven decisioning. They partner with global brands to deliver advanced machine learning solutions that optimize real-time strategies across digital platforms.

Role overview

As a Senior Machine Learning Engineer, you will build scalable ML infrastructure, deploy production‑grade models, and impact business outcomes. The role involves distributed systems, cutting‑edge neural‑network architectures, and MLOps best practices in a high‑performance environment.

Responsibilities

• Architect and train neural‑network models for optimization and audience modeling using PyTorch and distributed training frameworks.
• Build multi‑GPU training pipelines and implement hyperparameter tuning strategies.
• Develop feature‑engineering workflows using PySpark and embedding techniques.
• Own the ML lifecycle from training to batch inference, ensuring automation and reproducibility.
• Implement monitoring and observability solutions to track model performance and system health.
• Collaborate with cross‑functional teams to align ML initiatives with product strategy and KPIs.

Requirements

• MSc or PhD in Computer Science, Machine Learning, or related field.
• Strong ML engineering with proficiency in PyTorch.
• Hands‑on experience with Databricks.
• Expert‑level Python and PySpark skills for large‑scale data processing.
• Familiarity with AWS cloud platform and Snowflake data warehousing.
• Strong understanding of CI/CD workflows and best practices.

Benefits

• Competitive salary and bonus structure.
• Comprehensive health coverage.
• Generous PTO and company holidays.
• Flexible remote working options.

Desired skills and experience

MLOps, Databricks.

How to apply

Apply today to learn more.