AI Developer - Facets experience needed

CareSource; United States; On-site; USD 100,000 - 120,000; Full time

Job summary

A healthcare organization is seeking a Talent Acquisition Partner II to lead AI model development and deployment. The ideal candidate will have a Bachelor's degree, 5+ years of experience in AI/ML, and proficiency in Python. Responsibilities include designing algorithms, managing MLOps pipelines, and collaborating with teams to integrate AI into core processes. This role offers opportunities for innovation in a dynamic environment.

Qualifications

• Minimum of five years of experience in developing and deploying AI/ML models.
• Experience with cloud platforms and MLOps tools required.
• Experience with Agile methodologies required.

Responsibilities

• Design and implement AI models and algorithms.
• Lead the architecture of Generative AI platforms.
• Prototype proof-of-concept solutions.
• Train, validate, and fine-tune machine learning models.
• Deploy models using cloud infrastructure.
• Monitor model performance and retrain as needed.

Skills

Model interpretability and ethical AI practices

Proficiency in Python

Strong analytical and problem-solving abilities

Understanding of data structures and algorithms

Excellent communication and collaboration skills

Education

Bachelor’s degree in Computer Science or related field

Master’s degree preferred

Tools

TensorFlow

PyTorch

Scikit-learn

AWS

Azure

GCP

Docker

Kubernetes

Job description

Talent Acquisition Partner II @ CareSource

Overview

The AI Developer plays a key role in designing, developing, and deploying intelligent solutions. This role focuses on solving complex business challenges through innovative AI technologies and collaborates with cross-functional teams to deliver solutions aligned with defined objectives.

Responsibilities

• Design and implement AI models and algorithms tailored to diverse business challenges
• Define and lead the architecture of Generative AI platforms, including large language models (LLMs), vector databases, and inference pipelines
• Maintain deep expertise in modern generative AI technologies and related tools (e.g., Python, LangChain, embeddings, semantic search, RAG, IaC, Streamlit)
• Prototype proof-of-concept solutions to assess emerging technologies and ideas
• Foster innovation and collaboration in a fast-paced environment with a self-driven mindset
• Leverage AI-assisted development tools to enhance productivity
• Apply creative problem-solving to identify and implement process improvements
• Assess technical risks and develop mitigation strategies for successful delivery
• Collaborate with data scientists, software engineers, and product teams to integrate AI into production-ready systems
• Partner with leadership to evaluate services and optimize delivery and support
• Perform data preprocessing and analysis on large datasets to uncover actionable insights
• Train, validate, and fine-tune machine learning and deep learning models
• Deploy models using cloud infrastructure and containerization (e.g., Docker, Kubernetes)
• Implement and manage MLOps pipelines for model training, deployment, monitoring, and lifecycle management
• Apply AIOps practices to enhance operational efficiency and automate incident detection
• Monitor model performance and retrain as needed to maintain accuracy
• Stay current with industry trends and assess applicability to organizational goals
• Document workflows, models, and codebases to support maintainability
• Provide timely progress updates to stakeholders with milestones and proposed solutions

Education and Experience

• Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, or related field, or equivalent experience (required)
• Master’s degree preferred
• Minimum of five (5) years of experience in developing and deploying AI/ML models (required)
• Experience with cloud platforms (AWS, Azure, GCP) and MLOps tools (required)
• Experience with Agile methodologies (required)

Competencies, Knowledge, and Skills

• Knowledge of model interpretability and ethical AI practices
• Proficiency in Python and libraries such as TensorFlow, PyTorch, Scikit-learn
• Strong analytical and problem-solving abilities
• Understanding of data structures, algorithms, and software engineering principles
• Excellent communication and collaboration skills
• Knowledge of healthcare and managed care

Preferred Licensure and Certification

• AI / Data Science certifications or credentials preferred

Working Conditions

• General office environment; may require extended sitting or standing
• Occasional travel may be required to meet with stakeholders and development teams