AI/ML Engineer

Title: AI/ML Engineer - W2/C2C Visa - H1B/USC/TN -12+Years Duration: 5 years 100% remote work but should be available onsite for the first 2 days of the work at Anapolis Maryland Need resume, visa, DL and degree certificates and Need 3 references within the last 5 years for the submission Qualifications:1. The resource(s) that meet the following minimum qualifications:a. Bachelor of Science in Engineering, Computer Science, Data Science, or Mathematics, or arelated field (as determined by the AOC).2. The resource(s) to have the following qualifications:a. At least three (3) years’ experience in data science, machine learning, or applied AI development.b. At least three (3) years’ experience in software engineering, architecture, or web development. Skills and Experience:1. The resource(s) possessing the following preferred skills, experience, and capabilities: a. Experience with:(1) SQL and relational database systems (e.g., PostgreSQL)(2) Fine-tuning small language models or embedding models(3) Contributing to or maintaining open-source software projects(4) Graph databases or graph extensions (e.g., Neo4j, Apache AGE)(5) Designing and implementing multi-agent or task-oriented AI systems(6) Embedding models, vector similarity, re-ranking, and graph retrieval techniques inRAG systems(7) Version control systems (e.g., Git), containerization technologies (e.g., Docker), andservice-oriented architectures(8) Collaborating with large language models (LLMs), including both API-based integration and local deployment(9) Validating AI-generated outputs, mitigating hallucinations, and integrating AI toolsinto production service pipelines b. Ability to:(1) Understand data structures, algorithms, and clean coding principles(2) Select and apply appropriate techniques (LLM and non-LLM) based on task requirements(3) Develop and improve testing and evaluation pipelines for AI systems, including use of synthetic data(4) Demonstrate proficiency in Python, including the ability to develop production gradebackend services, APIs, middleware, and data pipelines.(5) Design and implement AI/ML systems that operate effectively on complex,inconsistent, or evolving datasets while balancing accuracy, latency, and cost (token consumption)(6) Collaborate with team members to define system architecture, agent workflows, anddata pipelines while working in constrained environments, including limited GPU availability and predefined infrastructure c. Knowledge of:(1) Hybrid cloud environments and distributed system considerations(2) Threading, asynchronous processing, and queues in backend servers(3) React and Microsoft Teams Toolkit for developing chatbot user interfaces(4) Non-LLM data analysis techniques for structured, semi-structured, and unstructured data(5) Classical natural language processing (NLP) techniques in addition to LLM-based approaches(6) Data science and LLM-related libraries in Rust or other performance-oriented programming languages