JSR Tech Consulting
Lead Machine Learning Engineer (Generative AI Focus)
Contract to hire position with a financial firm. Hybrid in Newark, NJ preferred.
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.
Impact & Purpose We are committed to attracting the best and brightest talent who are driven by impact and purpose. The Senior Machine Learning Engineer will play a crucial role in advancing our GenAI capabilities, pushing the boundaries of innovation while ensuring practical application and scalability. If you are passionate about transforming theoretical AI models into impactful real-world solutions, we invite you to join our team.
Payrate: 70 - 90 per hour, depending on experience.
Referrals increase your chances of interviewing at JSR Tech Consulting by 2x.
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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.
Impact & Purpose We are committed to attracting the best and brightest talent who are driven by impact and purpose. The Senior Machine Learning Engineer will play a crucial role in advancing our GenAI capabilities, pushing the boundaries of innovation while ensuring practical application and scalability. If you are passionate about transforming theoretical AI models into impactful real-world solutions, we invite you to join our team.
Payrate: 70 - 90 per hour, depending on experience.
Referrals increase your chances of interviewing at JSR Tech Consulting by 2x.
#J-18808-Ljbffr