AWS Lambda, Amazon Simple Storage Service (S3), Amazon Web Services (AWS), Application Programming Interface (API), Artificial Intelligence (AI), Cloud Computing, Continuous Deployment/Delivery, Continuous Integration, Cross-Functional, Data Management, Distributed Computing, Docker, Performance Analysis, Performance Modeling, Performance Tuning/Optimization, Python Programming/Scripting Language, REST (Representational State Transfer), Systems Scalability, Use Cases
Job Title: Senior Associate AI Engineer
Durations: 6 Months to begin (Potentially to convert FT)
Location: Remote -
- Boston, MA (Headquarters)
- New York, NY
- Chicago, IL
- Atlanta, GA
- Houston, TX
- Irving, TX
- Denver, CO
- Miami, FL
- New Jersey
Job Description:
Top Skills Required:
- Build and deploy ML/GenAI pipelines
- Work on RAG, APIs, orchestration workflows
- Skills: AI/ML, AWS, MLOps
- Focus: implementation + productionization
- AI/ML Engineer – GenAI and MLOps
Candidates’ 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 and 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.
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.
Interview Process:- 1 to 2 internal video interviews and 1 client round.
Pay Range: $60.50/Hr -$70.50/Hr
The specific compensation for this position will be determined by a number of factors, including the scope, complexity and location of the role as well as the cost of labor in the market; the skills, education, training, credentials and experience of the candidate; and other conditions of employment. Our full-time consultants have access to benefits including medical, dental, vision and 401K contributions as well as any other PTO, sick leave, and other benefits mandated by appliable state or localities where you reside or work.
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