AI Engineer

Role: AI Engineer

Location: San Francisco, CA (Onsite)

Type: Contract

Job Duties: About the Role

We are seeking an experienced technical leader to architect and scale our AI systems. You will bridge traditional machine learning with state-of-the-art Large Language Models (LLMs), acting as the technical anchor to drive our AI strategy from research to production.

Key Responsibilities

• System Architecture: Design, build, and scale secure, cost-effective ML pipelines and Generative AI applications.
• LLM Integration: Lead development using advanced RAG architectures, prompt engineering, and fine-tuning (PEFT/LoRA) on models like Llama 3, Gemini, and OpenAI.
• Core Machine Learning: Train and optimize predictive models, classifiers, and recommendation systems using deep learning and classical ML.
• MLOps & Leadership: Oversee model deployment (CI/CD for ML), monitor for drift, ensure AI safety, and mentor junior engineers.

Minimum Skills Required: Required Skills & Qualifications:

• Experience: 8–10 years in Machine Learning or Software Engineering, with 4+ years deploying Deep Learning models to production.
• Education: Master’s or Ph.D. in CS, AI, Math, or equivalent practical experience.
• 8+ years’ experience in Programming & Frameworks: Expert in Python; extensive hands-on experience with PyTorch (preferred) or TensorFlow.
• 4+ years’ experience in LLM Ecosystem: Deep knowledge of orchestration (LangChain, LlamaIndex), vector databases (Pinecone, Weaviate), and inference optimization (vLLM, quantization).
• 6+ years’ experience in Traditional ML & Data: Strong grasp of statistical modeling (scikit-learn, XGBoost) and large-scale data processing (Apache Spark, Ray).
• 6+ years’ experience in MLOps & Cloud: Proficiency with Cloud platforms (AWS/Google Cloud Platform/Azure), containerization (Docker, Kubernetes), model tracking (MLflow), and API deployment (FastAPI).

Preferred: Open-source AI contributions, experience with multi-modal models, or a background in AI guardrails."