Title: Machine Learning & AI Engineer – Production Systems (Contract-to-Hire)

Location: New York, NY (Hybrid)

Company Overview

We’re partnering with a leading global financial institution recognized for its innovation across investment banking, global markets, and asset and wealth management. The firm leverages advanced technology to enhance its infrastructure, strengthen client solutions, and drive data-driven decision-making across all business lines. With a global footprint and a strong engineering culture, the company continues to invest heavily in artificial intelligence and automation to deliver scalable, efficient, and reliable systems.

Position Overview

The Machine Learning & AI Engineer will join the Production Runtime Experience team, which develops and deploys advanced ML and GenAI solutions to reduce the risk and cost of managing large-scale compute environments. This is a contract-to-hire role that offers the opportunity to work on cutting-edge technology—combining classical ML, LLMs, and agentic AI—to automate production management and improve system reliability across a complex infrastructure.

Key Responsibilities

Design and implement tool-calling agents that combine retrieval, structured reasoning, and secure action execution.
Build evaluation frameworks for open-source and foundational LLMs, including retrieval pipelines, prompt synthesis, response validation, and self-correction loops.
Integrate agents into observability, incident management, and deployment systems to automate diagnostics, remediation, and post-incident reporting.
Collaborate with production and engineering teams to translate operational challenges into AI-driven solutions that improve productivity and reduce risk.
Implement guardrails, policy checks, fallback mechanisms, and continuous evaluation to ensure safety and compliance.
Optimize model performance and cost through prompt engineering, caching, model routing, and other performance tuning techniques.

Qualifications

3+ years of software development experience (Python, C/C++, Go, or Java); strong Python experience preferred.
3+ years of experience building and maintaining production ML systems (deployment, monitoring, evaluation, or data pipelines).
Hands-on experience with Large Language Models (LLMs), including prompt engineering, fine-tuning, retrieval-augmented generation (RAG), and tool-using agents.
Understanding of commercial and open-source LLMs (OpenAI, Gemini, Llama, Qwen, Claude).
Familiarity with applied statistics, core ML concepts, algorithms, and data structures.
Experience with cloud platforms (AWS preferred) and related tools—ECS/EKS, Lambda, S3, DynamoDB, SageMaker, Terraform, or CloudFormation.
Strong analytical thinking, communication, and collaboration skills.

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