ML Engineer

Role Overview Design, develop, and deploy advanced ML and generative AI solutions (e.g., RAG, image generation) using LLMs, prompt engineering, and MLOps best practices. Collaborate across teams to integrate Azure, Snowflake, and other technologies into scalable, secure AI applications. Key Responsibilities Build generative AI systems using Azure OpenAI, Cognitive Search, and Snowflake Cortex. Fine‑tune LLMs/SLMs using techniques like RLHF and prompt tuning. Develop CI/CD pipelines and implement model observability (e.g., hallucination detection). Collaborate with cross‑functional teams to deliver business‑driven AI solutions. Maintain documentation and stay current with AI advancements. Required Qualifications Bachelor’s in Computer Science or 7+ years of software development experience. 4–6 years in ML/MLOps/software development, including 1+ year in generative AI. Proficiency in Python, LangChain, Hugging Face, and PyTorch. Experience with Azure (OpenAI, ML, DevOps) and Snowflake (Snowpark, ML, Cortex). Strong understanding of RAG, vector databases, and prompt engineering. Familiarity with MLOps tools (MLflow, Docker, Kubernetes, GitHub Actions). EEO Employer Apex Systems is an equal opportunity employer. We do not discriminate or allow discrimination on the basis of race, color, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), age, sexual orientation, gender identity, national origin, ancestry, citizenship, genetic information, registered domestic partner status, marital status, disability, status as a crime victim, protected veteran status, political affiliation, union membership, or any other characteristic protected by law. Apex will consider qualified applicants with criminal histories in a manner consistent with the requirements of applicable law. #J-18808-Ljbffr Apex Systems