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: Masters 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/GCP/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.
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 technic...
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: Masters 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/GCP/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.
View more
View less