Applied Machine Learning Engineer Expert

Allstate•McCullom Lake, IL

22d

About The Position

This expert role will be responsible for multiple major technical aspects and forward engineering in the field of machine learning, information retrieval, artificial intelligence, natural language processing, and ontology engineering technologies. Plays a key role in the vision and realization of cutting-edge technical capabilities into business applications and solutions. About the Role We are looking for a Generative AI Software Engineer to join our team and help build next-generation AI-driven solutions. This role blends traditional Software engineering with cutting-edge AI integration, enabling innovative digital products and services. You will work closely with cross-functional teams to design, develop, and deploy secure, scalable applications and integrate advanced AI models into production environments. This position is open at multiple levels including Senior Consultant, Lead and Expert levels.

Requirements

Minimum of 3+ years of backend development experience using Java Spring Boot / Python.
Minimum of 3+ years working with RESTful APIs, microservices architecture, and asynchronous processing.
Minimum of 1 years’ experience working with Generative AI APIs and/or open-source models.
Minimum of 4+ years of backend development experience using Java Spring Boot / Python.
Minimum of 4+ years working with RESTful APIs, microservices architecture, and asynchronous processing.
Minimum of 1 years’ experience in LangChain, LLM orchestration, and prompt engineering.

Nice To Haves

Exposure to multi-modal AI systems and agentic AI frameworks.
Experience with MLOps workflows and cloud deployment (Azure/AI Foundry preferred).
Strong problem-solving and debugging skills.
Knowledge of ethical AI practices and compliance frameworks.
Familiarity with data preprocessing, token management, and embedding generation.

Responsibilities

Software Engineering Build secure, scalable, and high-performance microservices and applications using Java Spring Boot / Python.
Design and maintain RESTful APIs and microservices architecture with asynchronous processing.
Deploy and manage applications on cloud platforms, preferably Microsoft Azure.
AI Integration & Development Integrate and deploy Generative AI models (e.g., OpenAI, Hugging Face, LangChain) into production environments.
Optimize LLMs for specific use cases and implement RAG (Retrieval-Augmented Generation) pipelines.
Work with embedding models, vector databases, and prompt engineering techniques.
Explore multi-modal AI systems and agentic AI frameworks for advanced capabilities.
Modern Development Practices Leverage tools like GitHub Copilot and agentic AI for code reviews, unit testing, and pull requests.
Leverage APM tools like DataDog to enhance Observability posture for your application.
Collaborate with platform consultants, product engineers, and digital product managers to integrate AI solutions.
MLOps & Model Deployment Implement best practices for model deployment, scaling, versioning, and monitoring.
Develop and maintain scalable data pipelines for ingestion, processing, and feature engineering.
Ensure compliance with ethical AI standards and data governance as per Allstate standards.