Senior Machine Learning Engineer

Catalight

1d•Remote

About The Position

The Senior Machine Learning Engineer is a key contributor to Catalight’s Data & Analytics team, responsible for designing, developing, deploying, and maintaining scalable machine learning solutions that support advanced analytics and decision-making across the organization. Reporting to the Director of Data & Analytics, this individual contributor role works at the intersection of data engineering and data architecture, translating high-quality data assets into production-ready AI/ML models and intelligent applications. This role partners closely with the Senior Data Engineer to leverage robust data pipelines and with the Senior Data Architect to align with enterprise data strategy, ensuring machine learning solutions are reliable, secure, compliant, and aligned with Catalight’s mission.

Requirements

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.
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 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.
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.
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.
Ability to obtain and maintain criminal record clearance through the Department of Justice (DOJ).
Ability to obtain and maintain clearance through the Office of Inspector General.
Must attend any required training.

Nice To Haves

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.
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.
Navigates ambiguity with an excitement for problem solving.

Responsibilities

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.
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.
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.
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.
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.
Communicate effectively within the work environment, read and write using the primary language within the workplace.
Work in an exciting, fast paced high energy environment while effectively multitasking and managing day-to-day responsibilities without supervision.
Manage a remote schedule that aligns with PST business hours, ensuring your availability supports a healthy team rhythm and effective cross-functional partnership.