Lead Machine Learning Engineer (Generative AI Focus)

Iris Software Inc.; Newark (NJ); Hybrid; USD 180,000 - 230,000; Full time

Benefits offered by this job

Hybrid work (3 days/week)

Job summary

Iris Software Inc. is urgently seeking a Lead Machine Learning Engg (GEN AI Focus) in Newark, NJ. The role emphasizes deploying GenAI models, building robust data pipelines, and managing cloud-based infrastructure for scalable AI solutions.

You will drive DevOps, CI/CD, and secure, cost-efficient GenAI deployments while leveraging frameworks like LangChain and Hugging Face to deliver production-ready systems with advanced retrieval and monitoring capabilities.

Qualifications

• Bachelor's degree in computer science/engineering or related field; master's preferred.
• 5+ years of practical ML engineering experience deploying models in production.
• Strong Python and software engineering fundamentals.
• Solid ML lifecycle understanding and production readiness.
• Experience with cloud platforms, containerization, and infra management.
• DevOps practices, automation tools, and CI/CD awareness a must.
• GenAI frameworks, prompt engineering, and model serving expertise.
• Ability to manage GPU/TPU resources and optimize serving frameworks.
• Experience building agentic and multi-agent systems; cost optimization proven.

Responsibilities

• Lead deployment, monitoring, and maintenance of GenAI models in production.
• Build and maintain efficient data pipelines and storage for model ops.
• Use cloud platforms (AWS/Azure/GCP) and container orchestration (Docker, Kubernetes).
• Develop CI/CD pipelines; manage Git-based version control and automation.
• Implement secure coding practices, auth, monitoring, and alerting.
• Apply GenAI techniques like RAG and hallucination monitoring; human-in-the-loop.
• Design agent and multi-agent systems using LangChain and external APIs.

Skills

Python

GenAI

LLMs

Model deployment

Data pipelines

Cloud platforms

Docker

Kubernetes

Terraform

Git

Prompt engineering

Cost optimization

Education

Bachelor's degree in CS/Engineering

Master's degree preferred

Tools

LangChain

Hugging Face

Docker

Kubernetes

Terraform

CloudFormation

Job description

Our client which is a large Insurance Firm is urgently looking to hire a Lead Machine Learning Engg ( GEN AI Focus )

Location - Newark, NJ

3 Days Hybrid every week.

RAG, LLM, Langchain, hallucination monitoring, and human-in-the-loop systems.

We are seeking a highly skilled and experienced Senior Machine Learning Engineer to join our dynamic team. In the rapidly evolving world of Generative AI (GenAI), this role demands not only traditional machine learning expertise but also a deep understanding of GenAI-specific challenges. The ideal candidate will be a pivotal bridge between the theoretical capabilities of GenAI models and their practical application in production environments. We are looking for someone who can ensure our GenAI solutions are innovative, reliable, scalable, secure, and cost-effective.

Key Responsibilities:

Model Deployment & Maintenance: Focus on deploying, monitoring, and maintaining GenAI models in production, ensuring they function reliably in real-world settings.

Data Engineering: Build and maintain efficient data pipelines and storage solutions that support model operations.

Infrastructure Management: Utilize cloud platforms (AWS, Azure, GCP) for model deployment, containerization (Docker), orchestration (Kubernetes), and infrastructure as code (Terraform/CloudFormation).

DevOps & Automation: Develop CI/CD pipelines, manage version control (Git), and automate deployment processes for seamless operational efficiency.

Security & Monitoring: Implement secure coding practices, authentication, authorization, and set up robust monitoring and alerting systems for both infrastructure and model performance.

Generative AI Expertise: Deep understanding of LLMs, GenAI architectures, frameworks like Hugging Face, prompt engineering, and specialized infrastructure for GenAI workloads.

Advanced Techniques: Apply advanced GenAI techniques like Retrieval-Augmented Generation (RAG), hallucination monitoring, and human-in-the-loop systems.

Agent Development: Design and develop agent and multi-agent systems using frameworks like LangChain, enabling them to interact with external APIs and tools efficiently.

Cost Optimization: Implement strategies to manage and reduce the operational costs associated with GenAI deployments.

Qualifications:

• Bachelor's degree in computer science/Engineering, data science, or a related field. Master's degree preferred
• At least five plus years' experience as a machine learning engineer, deploying models in production
• Strong proficiency in Python and software engineering principles.
• Solid understanding of machine learning fundamentals and model lifecycle management.
• Experience with cloud platforms, containerization, and infrastructure management.
• Familiarity with DevOps practices and automation tools.
• Expertise in GenAI frameworks, prompt engineering, and model serving.
• Ability to manage GPU/TPU resources and optimize model serving frameworks.
• Experience in developing agentic systems and multi-agent architectures.
• Proven track record in cost optimization in AI deployments.
• Experience working in fast paced environment and independent worker