

ePATHUSA, Inc.
Senior AI / ML Engineers
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior AI / ML Engineer with a contract length of "unknown," offering a pay rate of "unknown." Candidates must have 10+ years in IT, 4+ years in financial services, and extensive experience with Python, LLMs, and cloud platforms.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
640
-
ποΈ - Date
November 21, 2025
π - Duration
Unknown
-
ποΈ - Location
Unknown
-
π - Contract
Unknown
-
π - Security
Unknown
-
π - Location detailed
New York, NY
-
π§ - Skills detailed
#Python #Deployment #Redshift #Java #AWS (Amazon Web Services) #SageMaker #Leadership #Data Processing #TensorFlow #Cloud #Terraform #S3 (Amazon Simple Storage Service) #GIT #API (Application Programming Interface) #Lambda (AWS Lambda) #Programming #Langchain #Spark (Apache Spark) #AI (Artificial Intelligence) #Version Control #Libraries #ML (Machine Learning) #C++ #Scala #PyTorch #DynamoDB #NLP (Natural Language Processing) #Data Pipeline
Role 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.
Requirements
Skills
Required/Preferred
Years
Candidate Experience
Must have 10+ years of experience working in IT in the US for companies in the US.
Required
10+
Must have 4 + years of βRecentβ experience working for a bank or brokerage house (Since 2019).
Required
4+
Must have 7+ yearsβ experience with prompt design and implementation of chatbot applications.
Required
7+
Must have 7+ yearsβ experience programming utilizing Python, C/C++, Go, Java, and Spark .
Required
7+
Must have strong past hands-on experience building and maintaining large-scale Python applications.
Required
Must have 7 plus yearsβ experience with PyTorch and / or TensorFlow.
Required
7+
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)."
Required
5+
Must have 7 years plus experience building data pipelines for both structured and unstructured data processing.
Required
7+
Must have 7 years plus experience developing APIs and integrating NLP or LLM models into software applications.
Required
7+
Excellent and Recent hands-on experience with agentic AI concepts and Large Language Models (LLMs).
Required
Excellent and Recent hands on experience with agent frameworks such as LangChain, CrewAI, or AutoGen.
Required
Excellent and Recent hands-on experience with GIT and version control systems.
Required
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).
Required
Experience with different LLMs, both commercial and open source, and their capabilities (e.g., OpenAI, Gemini, Llama, Qwen, Claude).
Required
Recent hands-on experience with MLOps tools and practices, ensuring seamless integration of machine learning models into production environments.
Required
Recent hands on experience with model fine-tuning techniques such as DPO and RLHF.
Required
Excellent ability to communicate ideas and results to stakeholders and leadership in a clear and concise manner
Required
Knowledge of financial products and services including trading, investment and risk management
Required
Benefits
Benefit Package includes:
Paid Sick Time
Insurance for Medical, Dental, Vision and Life Available
401(k) including Employer Match
HSA or FSA, Short-term & Long-term Disability Available
We are an EEO/Veterans/Disabled employer
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.
Requirements
Skills
Required/Preferred
Years
Candidate Experience
Must have 10+ years of experience working in IT in the US for companies in the US.
Required
10+
Must have 4 + years of βRecentβ experience working for a bank or brokerage house (Since 2019).
Required
4+
Must have 7+ yearsβ experience with prompt design and implementation of chatbot applications.
Required
7+
Must have 7+ yearsβ experience programming utilizing Python, C/C++, Go, Java, and Spark .
Required
7+
Must have strong past hands-on experience building and maintaining large-scale Python applications.
Required
Must have 7 plus yearsβ experience with PyTorch and / or TensorFlow.
Required
7+
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)."
Required
5+
Must have 7 years plus experience building data pipelines for both structured and unstructured data processing.
Required
7+
Must have 7 years plus experience developing APIs and integrating NLP or LLM models into software applications.
Required
7+
Excellent and Recent hands-on experience with agentic AI concepts and Large Language Models (LLMs).
Required
Excellent and Recent hands on experience with agent frameworks such as LangChain, CrewAI, or AutoGen.
Required
Excellent and Recent hands-on experience with GIT and version control systems.
Required
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).
Required
Experience with different LLMs, both commercial and open source, and their capabilities (e.g., OpenAI, Gemini, Llama, Qwen, Claude).
Required
Recent hands-on experience with MLOps tools and practices, ensuring seamless integration of machine learning models into production environments.
Required
Recent hands on experience with model fine-tuning techniques such as DPO and RLHF.
Required
Excellent ability to communicate ideas and results to stakeholders and leadership in a clear and concise manner
Required
Knowledge of financial products and services including trading, investment and risk management
Required
Benefits
Benefit Package includes:
Paid Sick Time
Insurance for Medical, Dental, Vision and Life Available
401(k) including Employer Match
HSA or FSA, Short-term & Long-term Disability Available
We are an EEO/Veterans/Disabled employer






