AI/ML Engineer-GenAI & ML Ops

: Senior Associate AI/ML REMOTE

Type of Job : New Contracting Role

Req # to submit to : View phone number on click.appcast.io


offices in: San Francisco, CA or Arlington, VA or Westminster, CO or Chicago, IL or Boston, MA or Birmingham, MI or Houston, TX or Atlanta, GA or Miami, FL or New York, NY or Minneapolis, MN or Los Angeles, CA or Seattle, WA or Dallas/Irving, TX or Irvine, CA.



Openings : 3

Project Overview :

Top Skills Required :

• Top Skills Required :
• Build and deploy ML/GenAI pipelines
• Work on RAG, APIs, orchestration workflows
• Skills: AI/ML, AWS, MLOps
• Focus: implementation + productionization
• Expected Start Date : ASAP
  
  End Date : 6-months from start date
  
  Location : This position does not require candidates to work on-site. Please aim to find candidates who live close to a PS office in case they are converted over permanently. Must work EST or CST hours

AI/ML Engineer - GenAI & MLOps

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.