Senior MLOps/AI Engineer

Claritev•New York, NY

14h

About The Position

Claritev pioneers innovative solutions for healthcare payments, drawing on unique insights and data analysis to create customized and scalable action plans to help our customers thrive. The Senior Machine Learning Operations Engineer will join our growing data science team to take a lead role in architecting and implementing processes and technologies to make machine learning development and deployment pipelines faster, more reliable, reproducible, and efficient.

Requirements

Must have 6+ years professional experience in data science or machine learning with emphasis on engineering. Experience must include deploying machine learning models into production and implementing systems to support MLOps processes.
High level of comfort with Python.
Knowledge of foundational statistical concepts (probability, distributions, inference, etc.).
Comfortable with containerization and orchestration technologies (Docker, Kubernetes, etc.). Experience with DevOps tools and concepts.
Experience building data pipelines and working with common data storage systems (relational databases, object storage, file systems, etc.).
You are and intellectually curious and a self-directed problem solver, keen to work on a variety of projects and independently search for creative solutions.
You communicate clearly and effectively and value diverse perspectives.
Bachelor's degree in computer science, mathematics, statistics or a related quantitative field (Master's or Doctorate preferred)

Nice To Haves

Experience working with recent LLMOps, AgenticAI Ops is strongly preferred.

Responsibilities

Contribute to the design and implementation of MLOps, LLM Ops, and AgenticAI Ops, processes to support development and deployment of data science solutions.
Contribute to the design and implementation of a model monitoring system to track model performance, model behavior, and data characteristics and to support rapid, human-in-the-loop, model retraining and validation when needed.
Deploy and test machine learning models as containerized services with API endpoints.
Support integration of machine learning pipelines into other systems and products as needed based on business requirements
Find opportunities to simplify workflows, automate tasks, and build components that are reusable across multiple projects
Communicate and collaborate within the data science team and across other departments
Ensure compliance with HIPAA regulations and requirements
Demonstrate the company's core competencies and values held within.
Please note due to the exposure of PHI sensitive data -- this role is considered to be a High Risk Role.

Benefits

Medical (PPO & HDHP), dental and vision coverage
Pre-tax Savings Account (FSA & HSA)
Life & Disability Insurance
Paid Parental Leave
401(k) company match
Employee Stock Purchase Plan
Generous Paid Time Off -- accrued based on years of service
o WA Candidates: the accrual rate is 4.61 hours every other week for the first two years of tenure before increasing with additional years of service
10 paid company holidays
Tuition reimbursement
Employee Assistance Program
Sick time benefits -- for eligible employees, one hour of sick time for every 30 hours worked, up to a maximum accrual of 40 hours per calendar year, unless the laws of the state in which the employee is located provide for more generous sick time benefits