Senior Machine Learning Engineer

Machine Learning Development & Modeling

• Design, develop, and validate machine learning models for prediction, classification, segmentation, and optimization use cases.
• Perform feature engineering, model selection, hyperparameter tuning, and performance evaluation.
• Apply statistical and machine learning techniques to extract insights from structured and semi-structured data.
• Ensure models are interpretable, reproducible, and aligned with business objectives.

MLOps & Model Lifecycle Management

• Build and maintain scalable ML pipelines for training, testing, deployment, and monitoring of models.
• Deploy models into production environments using batch and real-time inference patterns.
• Implement model versioning, monitoring, drift detection, and retraining strategies.
• Establish CI/CD practices for machine learning workflows in collaboration with engineering teams.

Data Integration & Collaboration

• Partner with the Senior Data Engineer to leverage and enhance data pipelines for ML readiness.
• Collaborate with the Senior Data Architect to align model development with enterprise data architecture and governance standards.
• Work with analysts and stakeholders to translate business problems into data science and machine learning solutions.
• Ensure data used for modeling meets quality, governance, and compliance standards.

AI/ML Enablement & Innovation

• Identify opportunities to apply machine learning and AI to improve operational efficiency and organizational outcomes.
• Develop reusable ML components, templates, and frameworks to accelerate adoption across teams.
• Stay current with emerging AI/ML technologies and recommend practical applications within Catalight’s ecosystem.
• Support experimentation and prototyping of new AI/ML use cases.

Governance, Compliance & Responsible AI

• Ensure machine learning solutions comply with HIPAA and applicable healthcare data privacy regulations.
• Implement best practices for responsible AI, including fairness, transparency, and bias mitigation.
• Document models, assumptions, and methodologies for auditability and organizational transparency.
• Partner with Data Governance to align ML practices with enterprise policies.

Qualifications

• Bachelor’s degree in Computer Science, Data Science, Machine Learning, or a related field preferred; or 6+ years of relevant experience in lieu of a degree.
• Strong proficiency in Python and common machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience developing and deploying machine learning models in production environments.
• Ability to mentor more junior engineers collaboratively.
• Strong proficiency with data platforms such as Snowflake and experience working with large-scale datasets.
• Experience with AWS and/or Azure services supporting ML workloads (e.g., SageMaker, Azure ML, or equivalent).
• Understanding of MLOps practices, including model deployment, monitoring, and lifecycle management.
• Strong SQL skills and experience working with data pipelines and ETL/ELT processes.
• Experience working in regulated environments, preferably healthcare, with knowledge of HIPAA and data privacy.
• Ability to communicate complex technical concepts clearly to both technical and non-technical stakeholders.

Requests:

• Must be able to communicate effectively within the work environment, read and write using the primary language within the workplace.
• Visual and auditory ability to work with clients, staff and others in the workplace continuously.
• Frequent speaking and listening (25-75%) to clients, staff, and others in the workplace.

Knowledge, Skills & Abilities (organized by our company values):

Community Centered:

• Seeks to understand the underlying needs, desires, and values of colleagues.
• Appreciates and demonstrates collaboration across teams.
• Serves as a role model, bringing our core values to life in your work.
• Work in an exciting, fast paced high energy environment while effectively multitasking and managing day-to-day responsibilities without supervision.
• Personable; able to work comfortably with individuals at all levels within the organization.
• Excellent verbal and writing communication skills; frequent proofreading and checking documents for accuracy.

Equity informed:

• Knowledge of multiple historically excluded groups with knowledge in I/DD (intellectual and developmental disability) communities.
• Interest in working with and elevating employee needs.
• Approaches work with a growth mindset, welcome feedback, and understand that humans all have biases and are imperfect as a baseline.
• Sensitivity to working with an ethnically, linguistically, culturally, and economically diverse population.

Bold:

• Navigates ambiguity with an excitement for problem solving.
• Effectively manages programs from visioning to implementation + impact measure.
• Commitment to meet agreed upon deadlines on time or ahead of schedule.
• Transparent on action, pursuits, and outcomes.
• A commitment to the values of the organization while demonstrating good judgment, flexibility, patience and discretion when dealing with confidential and sensitive matters.

Wellbeing driven:

• Willingness and commitment to self-reflection and re-thinking.
• Ability to understand your physical, mental, social, and financial wellbeing needs with a willingness to co-create boundaries that allow you to sustainably show up and honor your humanity.
• Capacity to contribute to and help cultivate effective + sustainable wellbeing driven spaces.
• Commitment to managing a remote schedule that aligns with PST business hours, ensuring your availability supports a healthy team rhythm and effective cross-functional partnership.

Conditions of Employment

• Ability to obtain and maintain criminal record clearance through the Department of Justice (DOJ). The People & Performance Department must analyze DOJ/FBI live scan reports in accordance with applicable Federal, State, and Local laws, as well as fitness for the position.
• Ability to obtain and maintain clearance through the Office of Inspector General.
• Must attend any required training.

Time Type:

Compensation:

The statements contained in this job description reflect general details as necessary to describe the principal functions of this job. It should not be considered an all-inclusive listing of work requirements. Individuals may perform other duties as assigned, including work in other functional areas as deemed fit for the organization.