Senior AI / ML Engineers

  • New York, NY
  • Posted 7 hours ago | Updated 7 hours ago

Overview

On Site
$100 - $120
Full Time
Accepts corp to corp applications

Skills

Gemini
AI
Machine learning
Banking
Python
Chatbot
Production support
Data Processing
C programming language
Java
Spark
Amazon dynamodb
Git
Version control systems
Api

Job Details

REQUIREMENT

Position: Senior AI / ML Engineers

Location: 499 Park Avenue, New York City, New York - 10022

Work type: Onsite

Duration: 1 year - renewable contracts

Mode of Interview: Virtual

Type: Contract

Industry: Financial Services

USC

W2/C2C

REQUIRED SKILLS:

  • AI
  • Machine learning
  • Banking operations
  • Chatbot
  • Python programming
  • Production support
  • Data Processing
  • Experience Programming
  • C programming language
  • Java
  • Spark
  • Amazon dynamodb
  • Agent
  • Git
  • Version control systems
  • Api
  • Gemini

NOTE: While replying please fill the below skills matrix Candidate Experience column. To make it easy for shortlisting resumes.

JOB DESCRIPTION:

  • Seeking Senior AI / ML Engineers to design, deploy, and manage prompt-based models on LLMs for various NLP tasks in the financial services domain. Additionally, consultants will be expected to:
  • Be responsible for launching and implementing GenAI agentic solutions aimed at reducing the risk and cost of managing large-scale production environments with varying complexities.
  • Address various production runtime challenges by developing agentic AI solutions that can diagnose, reason, and take actions in production environments to improve productivity and address issues related to production support.
  • Conduct research on prompt engineering techniques to improve the performance of prompt-based models within the financial field, exploring and utilizing LLM orchestration and agentic AI libraries.
  • Collaborate with cross-functional teams to identify requirements and develop solutions to meet business needs within the organization.
  • Communicate effectively with both technical and non-technical stakeholders.
  • Build and maintain data pipelines and data processing workflows for prompt engineering on LLMs utilizing cloud services for scalability and efficiency.
  • Must have 10+ years of experience working in IT in the US for companies in the US.
  • Must have 4 + years of Recent experience working for a bank or brokerage house (Since 2019).
  • Must have 7+ years experience with prompt design and implementation of chatbot applications.
  • Must have 7+ years experience programming utilizing Python, C/C++, Go, Java, and Spark .
  • Must have strong past hands-on experience building and maintaining large-scale Python applications.
  • Must have 7 plus years experience with PyTorch and / or TensorFlow.
  • Must have 5+ years of recent hands-on experience with cloud platforms AWS AI / ML deployment and data processing for building and operating on cloud infrastructure including containerized services (ECS/EKS), Lambda), data services (S3, DynamoDB, and Redshift), orchestration (Step Functions), model serving (SageMaker), and infra-as-code (Terraform/CloudFormation)."
  • Must have 7 years plus experience building data pipelines for both structured and unstructured data processing.
  • Must have 7 years plus experience developing APIs and integrating NLP or LLM models into software applications.
  • Excellent and Recent hands-on experience with agentic AI concepts and Large Language Models (LLMs).
  • Excellent and Recent hands-on experience with agent frameworks such as LangChain, CrewAI, or AutoGen.
  • Excellent and Recent hands-on experience with GIT and version control systems.
  • Excellent and recent hands-on experience with large Language Models (LLMs): orchestration and agentic AI libraries. API integration, prompt engineering, fine-tuning/adaptation, and building applications using RAG and tool-using agents (vector retrieval, function calling, secure tool execution).
  • Experience with different LLMs, both commercial and open source, and their capabilities (e.g., OpenAI, Gemini, Llama, Qwen, Claude).
  • Recent hands-on experience with MLOps tools and practices, ensuring seamless integration of machine learning models into production environments.
  • Recent hands on experience with model fine-tuning techniques such as DPO and RLHF.
  • Excellent ability to communicate ideas and results to stakeholders and leadership in a clear and concise manner
  • Knowledge of financial products and services including trading, investment and risk management
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.