Machine Learning Engineer

Focus Financial Partners is a leading financial services firm offering integrated wealth management and business management services. They are seeking a skilled Machine Learning Engineer to design, deploy, and maintain machine learning systems, collaborating with teams to translate research models into impactful applications.

Responsibilities:

• Develop, deploy, and optimize machine learning models for real-world business use cases and client-facing applications
• Partner with data scientists to operationalize predictive models and ensure scalable, maintainable, and performant production deployments
• Design and implement data pipelines and workflows that support training, inference, and model lifecycle management
• Work with large, complex datasets to ensure data quality, reproducibility, and reliable version control across ML workflows
• Implement model monitoring, logging, and alerting strategies to track performance, detect drift, and support retraining cycles
• Leverage cloud platforms (AWS, Azure, GCP) to build scalable ML solutions using managed services and infrastructure-as-code practices
• Write clean, modular, and well-documented code aligned with MLOps and software engineering best practices
• Stay current on emerging ML tooling, frameworks, and industry best practices to continuously enhance our platform and capabilities

Requirements:

• Master's degree in Computer Science, Data Science, Engineering, or a related technical field
• 6+ years of experience in machine learning engineering, applied ML, or related software engineering roles
• Strong proficiency in Python and experience with modern ML frameworks such as TensorFlow, PyTorch, or scikit-learn
• Experience with distributed data processing and compute frameworks (e.g., Pandas, Spark, Dask)
• Hands-on experience with containerization and orchestration technologies such as Docker and Kubernetes
• Familiarity with CI/CD pipelines, testing automation, and version control using Git
• Strong understanding of model evaluation, feature engineering, and performance optimization in production contexts
• Excellent analytical, communication, and collaboration skills, with the ability to work effectively in cross-functional teams
• Experience working with cloud-based ML platforms or services (e.g., SageMaker, Vertex AI, Databricks, or Snowflake ML)