AI Lead

San Francisco / Seattle, PST time. (On-site) Rate:
Contract to Hire in 3 months.

• AI / ML Solution Development:
  Design, develop, and deploy ML and AI models to solve business problems.
• Build solutions across Machine Learning, Deep Learning, NLP, Computer Vision, and Generative AI.
• Implement feature engineering, model training, tuning, validation, and deployment.
• Develop scalable model pipelines and reusable AI components.
• GenAI & LLM (If applicable):
  Build solutions on Azure OpenAI, OpenAI, AWS Bedrock, Google Vertex or similar platforms; prompt engineering, RAG pipelines, embeddings, vector DB integration; implement model governance, data privacy, bias & compliance controls.
• MLOps & Productionization:
  Operationalize models using MLOps frameworks (Azure ML, Sage Maker, MLflow, Databricks, Vertex AI); CI/CD for ML, model monitoring, retraining strategies; optimize performance, scalability, and reliability of AI solutions.
• Data
  
  Collaboration:
  
  Work closely with Data Engineers & Architects to ensure reliable data pipelines; handle structured and unstructured datasets; ensure data quality, lineage, and governance alignment.
• Stakeholder
  
  Collaboration:
  
  Work with business, product, and engineering stakeholders to understand use cases; translate business requirements into AI solutions; provide technical leadership and guidance to project teams.

• 5+ years in AI/ML engineering roles.
• Strong expertise in Python and ML libraries (Tensor Flow, PyTorch, Scikit-learn).
• NLP, Computer Vision, or GenAI (at least one specialization).
• SQL, data wrangling, feature engineering.
• Experience with Azure ML, AWS Sage Maker, GCP Vertex, Databricks.
• MLOps, CI/CD, APIs, containers (Docker, Kubernetes).
• Experience building and deploying production AI systems.
• Strong understanding of algorithms, statistics, and ML concepts.

• Experience with Generative AI/LLM implementations.
• Experience with vector databases (Pinecone, FAISS, Azure Vector Search).
• Knowledge of RAG, prompt engineering, model tuning.
• Cloud certifications (Azure, AWS, GCP).
• Experience in specific domains (Banking, Retail, Manufacturing, Healthcare, etc.).

• Strong problem-solving and analytical ability.
• Excellent communication and stakeholder collaboration.
• Innovation mindset and ability to think productively.
• Ability to work independently and mentor junior engineers.