Senior AI Engineer

Zs Associates; Princeton (NJ); Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

ZS Associates is seeking a skilled ML Engineer to build scalable ML backend systems, APIs, and orchestration pipelines. You will implement MLOps, model performance tracking, and multimodal AI integrations, with a focus on LLMs and Generative AI.

Collaborative cross‑functional teams will drive client‑facing solutions. Ideal candidates have strong Python/SQL, FastAPI experience, and a solid background in transformers, vector databases, and MLOps tooling like MLFlow and Langfuse.

Qualifications

• Master's or bachelor's degree in Computer Science or related field from a top university.

Responsibilities

• 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.

Skills

ML Engineering

Python

Async programming

FastAPI

ML Ops

Azure OpenAI

GPT-4 / LLMs

Data platforms

Vector search

Pinecone / Weaviate / Chroma

HuggingFace

Transformers

LangChain

LlamaIndex

Keras / TensorFlow / PyTorch

SQL

Education

Master's or Bachelor's degree in Computer Science or related field

Tools

FastAPI

Python

SQL

Azure OpenAI

Langfuse

MLFlow

Pinecone / Weaviate / Chroma

HuggingFace

Transformers

Job description

ZS is a place where passion changes lives. As a management consulting and technology firm focused on improving life and how we live it, we transform ideas into impact by bringing together data, science, technology and human ingenuity to deliver better outcomes for all. Here you’ll work side‑by‑side with a powerful collective of thinkers and experts shaping life‑changing solutions for patients, caregivers and consumers, worldwide. ZSers drive impact by bringing a client‑first mentality to each and every engagement. We partner collaboratively with our clients to develop custom solutions and technology products that create value and deliver company results across critical areas of their business. Bring your curiosity for learning, bold ideas, courage and passion to drive life‑changing impact to ZS.

Responsibilities

• 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.

Qualifications

• 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).
• 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), and 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, and 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.
• 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.

How you’ll grow

• 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.

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.

Work Authorization

This position is not eligible for visa sponsorship. Candidates must have authorization to work in the United States that does not now or in the future require employer sponsorship.