Machine Learning Engineer

Focus Financial Partners

Quick summary

Work type: On-site
Location: St. Louis, MO · Boston, MA · New York, NY
Salary: $140,000–$180,000 / yr
Posted: today

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $218k

This role $160k

$125k most similar roles pay here $277k

This role pays less than 87% of similar roles. Most pay $177,625–$258,500 — the shaded band above. At the midpoint, this role pays about $160k versus about $218k for comparable roles.

Based on 239 similar postings.

Employer

About Focus Financial Partners

Focus Financial Partners is a leading partnership of independent, fiduciary wealth management firms, providing financial advisory, investment management, and related services to individuals, families, and institutions.

Focus Financial Partners currently has 7 open roles on FindRole.

Listed pay typically runs $135,000–$160,000 across 7 roles with salary data.

Most-posted roles

View all roles at Focus Financial Partners

At a glance

TL;DR · Machine Learning Engineer

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Join our dynamic team as a Machine Learning Engineer, where you will collaborate with data scientists and software engineers to develop and deploy production-grade machine learning systems. Your day-to-day responsibilities include designing scalable data pipelines, implementing model monitoring strategies, and leveraging cloud platforms like AWS or Azure for infrastructure-as-code practices. You will need strong proficiency in Python and experience with TensorFlow, PyTorch, or scikit-learn, along with familiarity with containerization tools such as Docker and Kubernetes. This role involves working on large datasets and ensuring data quality while adhering to MLOps best practices. Ideal candidates have a Master’s degree and at least three years of hands-on experience in machine learning engineering.

Skills

Python TensorFlow PyTorch scikit-learn AWS Azure GCP Docker Kubernetes CI/CD Git Pandas Spark Dask

What you'll do

Develop and deploy machine learning models for real-world business applications.
Design data pipelines and workflows to support ML model lifecycle management.
Implement strategies for monitoring, logging, and alerting on model performance.
Build scalable ML solutions using cloud platforms like AWS or Azure services.
Write clean, modular code following MLOps best practices and software engineering standards.

What we're looking for

3+ years of experience in machine learning engineering or related roles.
Strong proficiency in Python and modern ML frameworks like TensorFlow, PyTorch.
Experience with distributed data processing and compute frameworks (Pandas, Spark).
Hands-on expertise with containerization technologies (Docker) and orchestration tools (Kubernetes).
Familiarity with cloud-based ML platforms and CI/CD pipelines for MLOps practices.
Excellent analytical, communication, and collaboration skills in cross-functional teams.

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