Senior Machine Learning Engineer
LPL FinancialAbout the role
Senior Machine Learning Engineer
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.
Job Overview:
LPL Financial Corp is seeking a highly skilled and experienced Senior Machine Learning Engineer to join our innovative technology team. You will be instrumental in designing, developing, and deploying cutting-edge machine learning solutions that drive business intelligence, optimize operations, and enhance client experiences within the financial services domain.
Responsibilities:
- Lead the full ML lifecycle: Drive end-to-end development of machine learning models, including problem definition, data exploration, training, evaluation, and production deployment.
- Collaborate and translate business needs: Work closely with product managers, data scientists, and engineering teams to deliver robust, scalable ML solutions aligned with business requirements.
- Design scalable ML pipelines: Implement pipelines with strong data quality, feature engineering, model versioning, and CI/CD practices for seamless deployment.
- Ensure performance and reliability: Select appropriate algorithms/frameworks, validate models through A/B testing, and maintain production-grade systems with monitoring and alerting for data drift.
- Promote innovation and compliance: Stay current with ML advancements, mentor team members, and uphold best practices in security, data privacy, and regulatory compliance.
What are we looking for?
We’re looking for strong collaborators who deliver exceptional client experiences and thrive in fast-paced, team-oriented environments. Our ideal candidates pursue greatness, act with integrity, and are driven to help our clients succeed. We value those who embrace creativity, continuous improvement, and contribute to a culture where we win together and create and share joy in our work.
Requirements:
- Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related quantitative field. PhD is a plus.
- 3-5+ years of professional experience in machine learning engineering, with a strong portfolio of successfully deployed ML models in production.
- Proficiency in programming languages such as Python (essential) and experience with relevant ML libraries (e.g., NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch).
- Solid understanding of machine learning algorithms, including supervised, unsupervised, and reinforcement learning techniques.
- Experience with cloud platforms (e.g., AWS, Azure, GCP) and their machine learning services (e.g., SageMaker, Azure ML, Google AI Platform).
Core Competencies:
- Strong experience with MLOps principles and tools for model deployment, monitoring, and management.
- Proficiency in SQL and experience working with large datasets, data warehousing, and ETL processes.
- Experience with distributed computing frameworks (e.g., Spark) is a plus.
- Excellent problem-solving skills, analytical thinking, and attention to detail.
- Strong communication and interpersonal skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.
- Experience within the financial services industry is highly desirable.
Pay Range:
$111,788-$186,313/yearCompany Overview:
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 29,000 financial advisors and the wealth-management practices of 1,100 financial institution, servicing and custodying approximately $1.9 trillion in brokerage and advisory assets on behalf of approximately 7 million Americans. The firm provides a wide range of advisor affiliati
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