AI/ML Software Engineer

AI/ML Software Engineer
Location: Remote
Employment Type: W2 Contract
Rate: $110/hour
Duration: Multi-year contract

Overview

We are seeking an experienced AI/ML Software Engineer to design and build software solutions that leverage artificial intelligence and machine learning to automate targeted tasks, enhance internal workflows, and improve user-facing services. This role supports initiatives for the Maryland Judiciary, with a focus on high-accuracy, production-grade systems built within defined technical constraints.

Key Responsibilities

·       System Design & Collaboration:

o   Work within established constraints regarding infrastructure, programming languages, and model selection

o   Contribute to technical decision-making related to data processing, retrieval strategies, and system integration

o   Collaborate with team members to define agent architectures, workflows, and system design decisions

o   Evaluate and select appropriate approaches for given tasks, including determining when to use LLM-based versus non-LLM techniques

o   Designing and building software systems that integrate AI/ML techniques to automate tasks, assist internal users, and improve user-facing services.

·       Testing, Evaluation, and Quality Assurance:

o   Assist in the design and implementation of testing and evaluation pipelines for AI/ML systems

o   Develop unit and integration tests for AI-enabled workflows and data pipelines

o   Generate and utilize synthetic data to support evaluation and benchmarking efforts

o   Contribute to improving system performance, including accuracy, latency, and cost efficiency

·       Deployment & Operations:

o   Support deployment of AI/ML applications within a hybrid cloud environment

o   Work with containerized applications to ensure reliable deployment and updates.

o   Optimize systems for environments with limited computational resources, including minimal GPU availability

·       General Responsibilities:

o   Deliver production-grade systems aligned with defined requirements, while supporting iterative improvement of evolving tools

o   Document system designs, workflows, and technical decisions as required

o   Stay informed on relevant advancements in AI/ML and apply them where appropriate within project constraints

Required Qualifications:

• Bachelor’s degree in Engineering, Computer Science, Data Science, Mathematics, or a related field
• Minimum of 3 years of experience in data science, machine learning, or applied AI development
• Minimum of 3 years of experience in software engineering, architecture, or web development

Preferred Skills and Experience:

·       SQL and relational database systems (e.g., PostgreSQL)

·       Fine-tuning small language models or embedding models

·       Contributing to or maintaining open-source software projects

·       Graph databases or graph extensions (e.g., Neo4j, Apache AGE)

·       Designing and implementing multi-agent or task-oriented AI systems

o   Embedding models, vector similarity, re-ranking, and graph retrieval techniques in RAG systems

o   Version control systems (e.g., Git), containerization technologies (e.g., Docker), and service-oriented architectures

o   Collaborating with large language models (LLMs), including both API-based integration and local deployment

o   Validating AI-generated outputs, mitigating hallucinations, and integrating AI tools into production service pipelines

o   Ability to:

§  Understand data structures, algorithms, and clean coding principles

§  Select and apply appropriate techniques (LLM and non-LLM) based on task requirements

§  Develop and improve testing and evaluation pipelines for AI systems, including use of synthetic data

§  Demonstrate proficiency in Python, including the ability to develop production-grade backend services, APIs, middleware, and data pipelines.

§  Design and implement AI/ML systems that operate effectively on complex, inconsistent, or evolving datasets while balancing accuracy, latency, and cost (token consumption)

§  Collaborate with team members to define system architecture, agent workflows, and data pipelines while working in constrained environments, including limited GPU availability and predefined infrastructure

·       Knowledge of:

o   Hybrid cloud environments and distributed system considerations

o   Threading, asynchronous processing, and queues in backend servers

o   React and Microsoft Teams Toolkit for developing chatbot user interfaces

o   Non-llm data analysis techniques for structured, semi-structured, and unstructured data

o   Classical natural language processing (NLP) techniques in addition to LLM-based approaches

o   Data science and LLM-related libraries in Rust or other performance-oriented programming languages