AI/ML Engineer NY

Hi,

Hope you are doing well!!

I have an urgent requirement with one of my clients. Please find the job details below and forward me your updated resume along with your contact details at Jitendra.s@noviainfotech.com

Role : AI/ML Engineer – GenAI & MLOps

 

Location :

• Boston, MA (HQ) – 40 Water Street
• New York, NY – 375 Hudson Street
• Chicago, IL – 35 W. Wacker Drive
• Dallas, TX – 2828 Routh Street
• Houston, TX – 1111 Bagby Street
• Austin, TX – 300 W. 6th Street
• Atlanta, GA – 384 Northyards Blvd NW
• Arlington, VA – 1515 N. Courthouse Road
• Miami, FL – 2911 Grand Avenue
• San Francisco, CA – 350 Bush Street
• San Jose, CA – 1 Almaden Boulevard
• Seattle, WA – 1448 NW Market Street
• El Segundo, CA – 13031 W. Jefferson Bouleva

 

Your Impact

•                     Design, build, and deploy ML and Generative AI pipelines from development through production.

•                     Implement RAG (Retrieval-Augmented Generation) solutions to enhance AI-driven applications with contextual data.

•                     Develop and integrate APIs and orchestration workflows to support scalable AI systems.

•                     Drive end-to-end productionization of AI/ML models, ensuring reliability, scalability, and performance.

•                     Partner with cross-functional teams (engineering, data, product) to operationalize AI use cases in real-world environments.

•                     Optimize model performance, monitoring, and lifecycle management within cloud-native environments.

 

Skills & Experience

•                     Strong hands-on experience in AI/ML engineering, including building and deploying models in production.

•                     Proven experience with Generative AI frameworks and RAG architectures.

•                     Expertise in MLOps practices (model deployment, monitoring, CI/CD for ML workflows).

•                     Experience building and consuming REST APIs and designing workflow orchestration pipelines.

•                     Strong experience with AWS (SageMaker, Lambda, S3, ECS/EKS, or similar services).

•                     Proficiency in Python and common ML/AI libraries (e.g., PyTorch, TensorFlow, LangChain, etc.).

•                     Experience with data pipelines and distributed systems.

•                     Familiarity with tools like Docker, Kubernetes, and workflow orchestrators (Airflow, Step Functions, etc.).

•                     Strong focus on implementation and production delivery, not just modeling/research.

 

 

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