Machine Learning Engineer

CovenantHR is a modern recruiting and talent solutions firm specializing in Cybersecurity, Cloud, AI, Data, Software Engineering, IT Infrastructure, Healthcare, and other specialized industries.

Recognized as a Top 10 Executive Recruitment Service Provider by HR Tech Outlook and one of the 50 Most Innovative Companies to Watch by CIO Bulletin, we combine experienced recruiters with our proprietary Scout™ AI-powered recruiting platform to deliver contract, direct-hire, and global talent solutions with speed, quality, and transparency.

The full job description covers all associated skills, previous experience, and any qualifications that applicants are expected to have.

Job Title: AI/ML Engineer

Location: Fully remote within the United States

Role Type: Contract engagement

Must-Have Skills:

• Production AI/ML engineering experience with advanced Python skills and strong machine learning fundamentals
• Hands-on experience with Generative AI, LLMs, RAG, embeddings, and vector databases
• Experience deploying AI/ML solutions on AWS, Azure, or GCP
• MLOps/LLMOps experience, including APIs, model evaluation, monitoring, and production deployment
• Experience with PyTorch, TensorFlow, or Scikit-learn
• Experience with LangChain, LlamaIndex, or similar AI application frameworks
• Experience with prompt engineering, fine-tuning, and AI application development
• REST APIs, microservices, Docker, CI/CD, and Git
• Strong problem-solving skills with the ability to independently own and deliver technical solutions
• Must be authorized to work in the United States

Responsibilities and Job Details:

• Design, develop, test, and deploy production-ready AI/ML models and applications
• Build Generative AI and LLM-powered solutions, including RAG pipelines, embeddings, vector search, and prompt-based applications
• Develop scalable APIs, microservices, backend integrations, and data pipelines supporting model training, evaluation, and inference
• Improve model and application accuracy, performance, reliability, and scalability
• Implement MLOps/LLMOps practices for deployment, monitoring, versioning, evaluation, and model lifecycle management
• Collaborate across engineering, data, xhyhwjd product, and business teams to translate requirements into production AI solutions
• Research and evaluate emerging AI technologies, frameworks, models, and development approaches
• Preferred experience with enterprise-scale production AI deployments and platforms such as Azure OpenAI, AWS Bedrock, Vertex AI, OpenAI APIs, or Anthropic Claude
• Preferred experience with AI agents, agentic workflows, tool calling, and vector databases such as Pinecone, Weaviate, Milvus, or FAISS
• Familiarity with AI security, responsible AI, model governance, and data privacy is preferred
• Our client is an equal opportunity employer committed to providing employment opportunities without unlawful discrimination.