SENIOR AI/ML ENGINEERS - - GC-USC-4+ Years in Banking Mandatory

Client Requirement Banking Experience (Mandatory)

The client s primary requirement is strong recent banking domain experience.
Candidates must have worked with a Banking or Brokerage client for at least 4+ years within the last 7 years.

Please do not submit profiles that do not clearly meet this criterion.
Resumes without sufficient recent banking experience will not be considered by the client.

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

Client:

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.

REQUIRED SKILLS:

• 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