What are the responsibilities and job description for the AI Lead position at Veracity Software Inc?
San Francisco / Seattle , PST time. (On-site)
Primary focus for someone with good audio/video/chat interface experience (OpenAI real time API experience would be good) and good communication skills.
Rate : Contract to Hire in 3 months
We are looking for an AI Lead with 13 years of Exp to design, develop, and deploy AI/ML and Generative AI solutions that deliver measurable business value. The role involves building scalable models, working with large datasets, integrating AI systems with enterprise applications, and collaborating with cross-functional teams including Data Engineering, Cloud, and Product to operationalize AI at scale.
Key Responsibilities
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, SageMaker, 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
Required Skills & Experience
5 years in AI/ML engineering roles
Strong expertise in:
Python, ML libraries (TensorFlow, PyTorch, Scikit-learn)
NLP, Computer Vision, or GenAI (at least one specialization)
SQL, data wrangling, feature engineering
Experience with:
Azure ML / AWS SageMaker / 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
Nice to Have
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.)
Soft Skills
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
Primary focus for someone with good audio/video/chat interface experience (OpenAI real time API experience would be good) and good communication skills.
Rate : Contract to Hire in 3 months
We are looking for an AI Lead with 13 years of Exp to design, develop, and deploy AI/ML and Generative AI solutions that deliver measurable business value. The role involves building scalable models, working with large datasets, integrating AI systems with enterprise applications, and collaborating with cross-functional teams including Data Engineering, Cloud, and Product to operationalize AI at scale.
Key Responsibilities
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, SageMaker, 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
Required Skills & Experience
5 years in AI/ML engineering roles
Strong expertise in:
Python, ML libraries (TensorFlow, PyTorch, Scikit-learn)
NLP, Computer Vision, or GenAI (at least one specialization)
SQL, data wrangling, feature engineering
Experience with:
Azure ML / AWS SageMaker / 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
Nice to Have
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.)
Soft Skills
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