AI/ML Software Engineer

AI/ML Software Engineer

Location: 100% Remote: Annapolis, MD Job ID: K23-0094-25L-17 Duration: Long Term Contract Position, Possibility of extension Pay Rate: Hourly

About the Job

The client is seeking an AI/ML Software Engineer to build software tools that automate tasks with high accuracy, assist internal users, and improve external user experiences. This includes RPA, chatbot development, AI/ML integration into reporting tools, LLM agents for knowledge retrieval, deep research, translation, transcription, redaction, document analysis, document generation, agentic coding, and data processing.

Responsibilities

System Design & Collaboration:

• Work within established constraints for infrastructure, programming languages, and model selection.
• Contribute to technical decisions regarding data processing, retrieval strategies, and system integration.
• Collaborate with team members to define agent architectures, workflows, and system design.
• Evaluate and select appropriate approaches, determining when to use LLM-based versus non-LLM techniques.
• Design and build software systems integrating AI/ML techniques.

Testing, Evaluation, and Quality Assurance:

• Assist in designing and implementing testing and evaluation pipelines for AI/ML systems.
• Develop unit and integration tests for AI-enabled workflows and data pipelines.
• Generate and utilize synthetic data for evaluation and benchmarking.
• Contribute to improving system performance (accuracy, latency, cost efficiency).

Deployment & Operations:

• Support deployment of AI/ML applications in a hybrid cloud environment.
• Work with containerized applications for reliable deployment and updates.
• Optimize systems for environments with limited computational resources (minimal GPU availability).

General Responsibilities:

• Deliver production-grade systems aligned with requirements, supporting iterative improvement.
• Document system designs, workflows, and technical decisions.
• Stay informed on relevant AI/ML advancements and apply them appropriately.

Deliverables by Purchase Order Year:

Year 1:

• Internal Chatbot Refinement: UI improvements, user history & feedback -- 240 hours.
  • Deliverables: Application code + Docker build; user profile & history DB; test cases & privacy/compliance pipeline.
• External Chatbot Development: Initial conversational bot (non-analytical) -- 480 hours.
  • Deliverables: Application code + Docker build; conversation DB; test cases & compliance pipeline; UX/agency scoring.
• RPA: Local LLM analysis tools with batching -- 240 hours.
  • Deliverables: Application code; integration documentation; usage & process reporting.
• Knowledge Retrieval (RAG & Search): Improve vector/hybrid search & case mgmt integration -- 520 hours.
  • Deliverables: Comparative RAG results; agent code/prompts; test pipeline; recommendations for knowledge store updates.
• Translation: MD-specific terminology & guidelines -- 80 hours.
  • Deliverables: Translation agent code/prompts; test cases & pipeline.
• Transcription: Refine deployment based on feedback -- 160 hours.
  • Deliverables: Comparative pipeline results; updated code/prompts; test cases & pipeline.
• Redaction (PII & Sensitive Data): Build detection agent -- 240 hours.
  • Deliverables: Application code; test cases & pipeline for PII/sensitive data identification.

(Years 2-5 follow the same structure as Year 1)

Qualifications

Minimum Qualifications:

• Bachelor of Science in Engineering, Computer Science, Data Science, Mathematics, or a related field.

Preferred Qualifications:

• At least three (3) years' experience in data science, machine learning, or applied AI development.
• At least three (3) years' experience in software engineering, architecture, or web development.

Preferred Skills, Experience, & Capabilities:

• Experience with:
  • 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.
  • Embedding models, vector similarity, re-ranking, and graph retrieval techniques in RAG systems.
  • Version control systems (e.g., Git), containerization (e.g., Docker), and service-oriented architectures.
  • Collaborating with LLMs (API-based integration and local deployment).
  • Validating AI-generated outputs, mitigating hallucinations, and integrating AI tools into production service pipelines.
• 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 synthetic data use.
  • Develop production-grade backend services, APIs, middleware, and data pipelines in Python.
  • Design and implement AI/ML systems balancing accuracy, latency, and cost in complex datasets and constrained environments.
  • Collaborate on system architecture, agent workflows, and data pipelines in constrained environments (limited GPU, predefined infrastructure).
• Knowledge of:
  • Hybrid cloud environments and distributed system considerations.
  • Threading, asynchronous processing, and queues in backend servers.
  • React and Microsoft Teams Toolkit for chatbot UIs.
  • Non-LLM data analysis techniques for structured, semi-structured, and unstructured data.
  • Classical NLP techniques alongside LLM-based approaches.
  • Data science and LLM-related libraries in Rust or other performance-oriented languages.

About DataSoft Technologies

DataSoft Technologies is a recognized IT consulting services provider founded in 1994, offering staff augmentation for IT and Automotive Services.

Benefits:

• Paid Holidays/Paid Time Off (PTO)
• Medical/Dental Insurance
• Vision Insurance
• Short Term/Long Term Disability
• Life Insurance
• 401 (K)