GenAI & ML Engineer — Onsite NYC, 6-Month Contract

Saransh Inc; New York (NY); On-site; USD 96,000 - 165,000; Full time

Job summary

Saransh Inc. seeks an AI/ML Engineer to lead design, development, and deployment of advanced AI and ML solutions across the enterprise.

You will collaborate with AI Architects, Cloud Engineers, and CRM Development Teams to deliver scalable, ethical AI systems, spanning Generative AI models like Gemini and GPT-4 and traditional NLP/Deep Learning architectures. This hands-on technical leadership role requires deep ML expertise, strong system design, and mentorship to guide retraining and

Responsibilities

• Be a critical member of the design, development, and deployment of machine learning and GenAI models in collaboration with AI Architects, Cloud Engineers, and CRM Development Teams.
• Evaluate and fine-tune state-of-the-art models and integrate them into enterprise systems such as Salesforce.
• Guide retraining efforts to maintain model performance, fairness, and ethical standards.
• Mentor junior engineers and provide technical leadership on best practices in ML model development, optimization, and MLOps.
• Collaborate cross-functionally with product owners, data scientists, and business stakeholders to translate business needs into AI solutions.
• Ensure AI governance and ethics by monitoring for bias, ensuring data privacy compliance, and adhering to responsible AI principles.
• Stay ahead of industry trends, tools, and research to continuously innovate and improve AI capabilities within the organization.
• Document architectures, workflows, and model lifecycles for transparency, reproducibility, and audit readiness.

Job description

Saransh Inc. seeks an AI/ML Engineer to lead design, development, and deployment of advanced AI and ML solutions across the enterprise.

You will collaborate with AI Architects, Cloud Engineers, and CRM Development Teams to deliver scalable, ethical AI systems, spanning Generative AI models like Gemini and GPT-4 and traditional NLP/Deep Learning architectures. This hands-on technical leadership role requires deep ML expertise, strong system design, and mentorship to guide retraining and