Applied AI/ML Engineer

OP Recruiting; New York (NY); On-site; USD 170,000 - 250,000; Full time

Job summary

OP Recruiting is seeking an Applied AI / Machine Learning Engineer in New York, NY, to design and implement AI infrastructure for a fast-paced financial services environment.

You will build autonomous multi‑agent systems, work on production‑grade LLM orchestration, and optimize retrieval-augmented workflows with low latency. Expect collaboration with cross‑functional teams and a strong emphasis on MLOps and scalable architectures.

Qualifications

• 6+ years of software engineering and machine learning experience (or 4+ years with an advanced quantitative degree).
• Exceptional Python programming skills with deep experience in PyTorch or JAX.
• Proven experience building production applications with advanced LLM orchestration tools and protocol‑driven tool integration.

Responsibilities

• System Architecture & Deployment: Design and maintain high‑efficiency AI infrastructure, including dynamic model routing, automated evaluation frameworks, and low‑latency inference setups on dedicated hardware.
• Agentic Framework Development: Construct autonomous multi‑agent systems to automate software development, complex document analysis, and large‑scale data workflows across distributed systems.
• Enterprise Search & Retrieval: Scale search architectures leveraging advanced Retrieval‑Augmented Generation (RAG) models, vector storage solutions, and tailored embedding pipelines.
• Stakeholder Collaboration: Work alongside cross‑functional domain experts and analysts to convert complex operational and research challenges into production‑ready, AI‑driven applications.
• MLOps Implementation: Establish robust MLOps practices, including continuous deployment pipelines, model monitoring, version control, drift management, and systematic quality evaluation metrics.

Skills

Python

PyTorch/JAX

LLM orchestration

MLOps

RAG models

Distributed systems

Education

Advanced quantitative degree

Tools

Container technologies

Vector storage solutions

Distributed cloud deployments

Job description

Applied AI / Machine Learning Engineer

Location: New York, NY Metro Area (On-Site)

About The Opportunity

Join a high-velocity, centralized technology group building the foundational artificial intelligence platform for a leading financial services organization. This hands-on, code-first role focuses on designing state-of-the‑art agentic workflows, custom LLM infrastructure, and high-throughput retrieval systems directly driving business outcomes. You will bridge the gap between bleeding-edge generative models and production-grade execution in a fast‑paced, highly quantitative environment.

Responsibilities

• System Architecture & Deployment: Design and maintain high‑efficiency AI infrastructure, including dynamic model routing, automated evaluation frameworks, and low‑latency inference setups on dedicated hardware.
• Agentic Framework Development: Construct autonomous multi‑agent systems to automate software development, complex document analysis, and large‑scale data workflows across distributed systems.
• Enterprise Search & Retrieval: Scale search architectures leveraging advanced Retrieval‑Augmented Generation (RAG) models, vector storage solutions, and tailored embedding pipelines.
• Stakeholder Collaboration: Work alongside cross‑functional domain experts and analysts to convert complex operational and research challenges into production‑ready, AI‑driven applications.
• MLOps Implementation: Establish robust MLOps practices, including continuous deployment pipelines, model monitoring, version control, drift management, and systematic quality evaluation metrics.

Requirements (Must-Have)

• 6+ years of software engineering and machine learning experience (or 4+ years paired with an advanced quantitative degree).
• Exceptional Python programming skills paired with deep experience in deep learning frameworks such as PyTorch or JAX.
• Proven experience building production applications with advanced LLM orchestration tools, structured output architectures, and protocol‑driven tool integration.
• Direct experience utilizing vector storage solutions, container technologies, and deploying applications on distributed cloud environments (AWS, Azure, or GCP).
• Strong technical focus on system optimization, compute efficiency, latency reduction, and a commitment to shipping reliable production code.

Preferred Qualifications (Nice-to-Have)

• Prior background delivering advanced AI tools or alternative data pipelines within quantitative finance, investment management, or premier technology firms.
• Proficiency in a compiled programming language (such as C++, Go, or Java).
• Solid grounding in traditional statistical machine learning methodologies (time‑series analysis, clustering, regression) alongside generative models.

Compensation & Benefits

• Competitive base compensation package paired with performance‑based incentive opportunities.
• Access to high‑performance computational hardware and specialized proprietary data assets.
• Comprehensive medical, dental, and vision insurance coverage.
• Equal Opportunity Employer: All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, or protected veteran status.

Accepting Candidates