Senior AI Engineer

ZS
Princeton, NJ, United States
11 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
4 years minimum
Working hours
Regular working hours
Languages
English
Job source

Tech stack

A/B Testing Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Computer Vision Audit Trail Microsoft Azure Big Data Encodings Computer Programming Databases Continuous Integration
+45 more
Information Engineering Extract Transform Load (ETL) Data Transformation Data Security Dependency Injection Software Design Patterns DevOps Django Web Framework Github Python (Programming Language) Key Management Machine Learning Object-Oriented Software Development Tensorflow Azure DevOps Pipelines Search Technologies SQL Databases Strategies of Testing Management of Software Versions Feature Engineering Pytorch Flask (Web Framework) Large Language Models Prompt Engineering Deep Learning Generative AI Backend Keras Rate Limiting Fastapi Containerization Pyspark Solid Principles Kubernetes Information Technology HuggingFace Machine Learning Operations Celery Asynchronous Programming GPT Software Version Control Data Pipelines Docker Key Vault Microservices

Job description

  • Build, refine, and use ML Engineering platforms and components; develop and implement scalable backend systems, APIs, and microservices using FastAPI.
  • Implement MLOps including model KPI measurement, tracking, model drift detection, and model feedback loops.
  • Deploy and operationalize ML and Deep Learning models, with a strong focus on LLMs and Generative AI.
  • Integrate Azure OpenAI (GPT-4, GPT-4 Vision) and other LLM providers with proper retry logic and error handling.
  • Maintain up-to-date knowledge of state-of-the-art technologies such as LLMs, GenAI, and transformer architectures.
  • Scale machine learning algorithms to work on massive data sets under strict SLAs.
  • Build and orchestrate model pipelines including feature engineering, inferencing, and continuous model training.
  • Write backend application code in Python and SQL using strong object-oriented principles and asynchronous programming (asyncio, async/await).
  • Implement dependency injection patterns and layered architecture (Service, Foundation, Orchestration, DAL).
  • Build LLM observability (e.g., Langfuse) to track prompts, tokens, costs, and latency.
  • Develop prompt management systems with versioning and fallback mechanisms.
  • Implement Celery (or similar) workflows for asynchronous task processing and complex pipelines.

Requirements

  • Master’s or bachelor’s degree in Computer Science or a related field from a top university.
  • 4+ years of hands-on experience in Machine Learning, including production LLM systems.
  • Strong fundamentals in machine learning, deep learning, and fine-tuning models (LLMs), including:
  • Understanding of transformer architectures
  • Prompt engineering expertise
  • Embeddings and vector search
  • Experience in backend API design using FastAPI or similar asynchronous frameworks (e.g., Flask, Django), including async patterns and rate limiting.
  • Experience with vector databases, including:
  • Pinecone, Weaviate, or Chroma
  • Embedding storage and similarity search
  • Hybrid search implementations
  • Strong programming expertise in Python is a must, including:
  • Async programming (asyncio, async/await)
  • Type hints and Pydantic
  • SOLID principles and design patterns
  • PySpark/Scala is optional.
  • Knowledge of AI/ML concepts and experience integrating AI models into backend services is mandatory.
  • Experience with MLOps to measure and track model performance, including:
  • MLFlow for model tracking
  • Langfuse or similar tools for LLM observability (strongly preferred)
  • Model versioning and A/B testing
  • Experience working with NLP and computer vision, including:
  • Text extraction and preprocessing
  • Document understanding (layout, tables)
  • OCR processing
  • GPT-4 Vision or similar multimodal integration
  • Experience implementing:
  • Feature engineering pipelines
  • Real-time inferencing systems
  • Batch prediction pipelines
  • Model serving with FastAPI
  • Experience with ML frameworks, including:
  • HuggingFace (transformers, datasets) - mandatory
  • Keras/TensorFlow/PyTorch
  • LangChain - strongly preferred
  • LlamaIndex for RAG
  • Familiarity with database technologies such as SQL.
  • Good problem-solving skills and the ability to work in a fast-paced, team-oriented environment.

Additional Skills:

  • Understanding of DevOps and CI/CD, including:
  • Docker containerization
  • Azure DevOps pipelines or GitHub Actions
  • Kubernetes (nice to have)
  • Data security practices, including:
  • Multi-tenant data isolation
  • Secure key management (e.g., Azure Key Vault)
  • Audit trail implementation
  • Experience designing on cloud platforms:
  • Azure (strongly preferred): Azure OpenAI, Blob Storage, Key Vault, Container Registry
  • AWS or GCP
  • Experience with data engineering in Big Data systems, including large-scale data processing and ETL/ELT pipelines.
  • Rate limiting and quota management for high-throughput API usage.
  • Cost management and optimization for LLM usage at scale.
  • Document processing expertise (PDF extraction, OCR tooling).
  • Production incident management and on-call experience.
  • Testing strategies for non-deterministic LLM outputs (e.g., golden datasets, fuzzy matching).

  • Domain knowledge in regulated industries (e.g., healthcare/pharma workflows, regulatory compliance) is a plus.
  • Fluency in English
  • Client-first mentality
  • Intense work ethic
  • Collaborative spirit and problem-solving approach

Benefits & conditions

Pulled from the full job description

  • Internal mobility program
  • Work from home
  • Opportunities for advancement, * Cross-functional skills development & custom learning pathways
  • Milestone training programs aligned to career progression opportunities
  • Internal mobility paths that empower growth via s-curves, individual contribution and role expansions

Perks & Benefits:

At ZS, your growth matters. We offer a comprehensive total rewards package that supports your health and well-being, financial future, time away, and professional development. With robust skills-building programs, multiple career progression paths, internal mobility, and a deeply collaborative culture, you’ll have the opportunity to do meaningful work, expand your capabilities, and thrive as part of a global community. For details on total rewards in United States, visit ZS US office locations Where we work ZS.

Hybrid working model:

We are committed to giving our employees a flexible and connected way of working. A flexible and connected ZS allows us to combine work from home and on-site presence at clients/ZS offices for the majority of our week. The magic of ZS culture and innovation thrives in both planned and spontaneous face-to-face connections.

Travel:

Travel is a requirement at ZS for client facing ZSers; business needs of your project and client are the priority. While some projects may be local, all client-facing ZSers should be prepared to travel as needed. Travel provides opportunities to strengthen client relationships, gain diverse experiences, and enhance professional growth by working in different environments and cultures.

Considering applying?

At ZS, we honor the visible and invisible elements of our identities, personal experiences, and belief systems-the ones that comprise us as individuals, shape who we are, and make us unique. We believe your personal interests, identities, and desire to learn are integral to your success here. We are committed to building a team that reflects a broad variety of backgrounds, perspectives, and experiences. Learn more about our inclusion and belonging efforts and the networks ZS supports to assist our ZSers in cultivating community spaces and obtaining the resources they need to thrive.

If you’re eager to grow, contribute, and bring your unique self to our work, we encourage you to apply.

ZS is an equal opportunity employer and is committed to providing equal employment and advancement opportunities without regard to any class protected by applicable law.

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