Machine Learning Engineer II

Machine Learning Engineer II

LPL Financial

What if you could build a career where ambition meets innovation?

At LPL Financial, we empower professionals to shape their success while helping clients pursue their financial goals with confidence. What if you could have access to cutting‑edge resources, a collaborative environment, and the freedom to make an impact? If you're ready to take the next step, discover what’s possible with LPL Financial.

We are seeking a Machine Learning Engineer II to design, develop, and deploy machine learning solutions that support business intelligence, operational efficiencies, and enhanced client experiences. This role includes ownership of end‑to‑end machine learning initiatives and collaboration with cross‑functional teams to deliver scalable, production‑ready models.

• Manage the full lifecycle of machine learning development, including data exploration, feature engineering, model development, and production deployment.
• Collaborate with product managers, data scientists, and engineering teams to ensure alignment between technical solutions and business requirements.
• Design and implement scalable machine learning pipelines supported by CI/CD practices.
• Monitor and maintain model performance, reliability, and compliance with security and regulatory standards.

We are seeking individuals who work effectively in collaborative, fast‑paced environments and who contribute to consistent and reliable delivery. Candidates should demonstrate accountability, clear communication, adaptability, and a commitment to continuous improvement.

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field;
  PhD preferred but not required.
• 3+ years of experience developing and deploying machine learning models in production environments.
• Proficiency in Python and machine learning libraries such as Tensor Flow, PyTorch, and Scikit‑learn.
• 3+ years of experience with cloud platforms (AWS, Azure, or GCP) supporting ML workflows.
• Knowledge of machine learning algorithms, model evaluation techniques, and production‑level model integration.

• Experience with MLOps principles, including deployment automation, monitoring, and model lifecycle management.
• Proficiency in SQL and experience working with large datasets; experience with Spark is preferred.
• Demonstrated analytical and problem‑solving abilities.
• Ability to present and explain technical concepts to technical and non‑technical audiences.

$48.73-$81.21/hour
Actual base salary varies based on factors, including but not limited to, relevant skill, prior experience, education, base salary of internal peers, demonstrated performance, and geographic location. Additionally, LPL Total Rewards package is highly competitive, designed to support your success at work, at home, and at play – such as 401K matching, health benefits, employee stock options, paid time off, volunteer time off, and more.

Your recruiter will be happy to discuss all that LPL has to offer!

LPL Financial Holdings Inc. (Nasdaq: LPLA) is among the fastest growing wealth management firms in the U.S. As a leader in the financial advisor-mediated marketplace, LPL supports over 32,000 financial advisors and the wealth management practices of approximately 1,100 financial institutions, servicing and custodying approximately $2.3 trillion in brokerage and advisory assets on behalf of approximately 8 million Americans. The firm provides a wide range of advisor affiliation models, investment solutions, fintech tools and practice management services, ensuring that advisors and institutions have the flexibility to choose the business model, services, and technology resources they need to run thriving businesses.

For further information about LPL, please visit

At LPL, independence means that advisors and institution leaders have the freedom they deserve to choose the business model, services, and technology resources that allow them to run a thriving business. They have the flexibility to do business their way. And they have the freedom to manage their client…