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Senior AI \/ ML Engineers

ePATHUSA
Contract
On-site
New York City, New York, United States
Machine Learning Engineer
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:
<\/div>
  • 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.<\/span>
    <\/li>
  • 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.
    <\/li>
  • 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.
    <\/li>
  • Collaborate with cross\-functional teams to identify requirements and develop solutions to meet business needs within the organization.
    <\/li>
  • Communicate effectively with both technical and non\-technical stakeholders.
    <\/li>
  • Build and maintain data pipelines and data processing workflows for prompt engineering on LLMs utilizing cloud services for scalability and efficiency.
    <\/li> <\/ul>

    <\/div>

    <\/div><\/span>

    Requirements<\/h3>
    <\/colgroup>
    Skills
    <\/td>     		Required\/Preferred
    <\/td>     		Years
    <\/td>     		Candidate Experience
    <\/td> <\/tr>
    Must have 10+ years of experience working in IT in the US  <\/span>for companies in the US.
    <\/td>     		Required
    <\/td>     		10+
    <\/td>
    <\/td> <\/tr>
    Must have 4 + years of ‘Recent’ experience working for a bank or brokerage house (Since 2019). <\/span>
    <\/td>     		Required
    <\/td>     		4+
    <\/td>
    <\/td> <\/tr>
    Must have 7+ years’ experience with prompt design and implementation of chatbot applications.
    <\/td>     		Required
    <\/td>     		7+
    <\/td>
    <\/td> <\/tr>
    Must have 7+ years’ experience programming utilizing Python, C\/C++, Go, Java, and Spark . <\/span>
    <\/td>     		Required
    <\/td>     		7+
    <\/td>
    <\/td> <\/tr>
    Must have strong past hands\-on experience building and maintaining large\-scale Python applications.
    <\/td>     		Required
    <\/td>
    <\/td>
    <\/td> <\/tr>
    Must have 7 plus years’ experience with PyTorch and \/ or TensorFlow.
    <\/td>     		Required
    <\/td>     		7+
    <\/td>
    <\/td> <\/tr>
    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)."
    <\/td>     		Required
    <\/td>     		5+
    <\/td>
    <\/td> <\/tr>
    Must have 7 years plus experience building data pipelines for both structured and unstructured data processing.
    <\/td>     		Required
    <\/td>     		7+
    <\/td>
    <\/td> <\/tr>
    Must have 7 years plus experience developing APIs and integrating NLP or LLM models into software applications.
    <\/td>     		Required
    <\/td>     		7+
    <\/td>
    <\/td> <\/tr>
    Excellent and Recent hands\-on experience with agentic AI concepts and Large Language Models (LLMs).
    <\/td>     		Required
    <\/td>
    <\/td>
    <\/td> <\/tr>
    Excellent and Recent hands on experience with agent frameworks such as LangChain, CrewAI, or AutoGen.
    <\/td>     		Required
    <\/td>
    <\/td>
    <\/td> <\/tr>
    Excellent and Recent hands\-on experience with GIT and version control systems.
    <\/td>     		Required
    <\/td>
    <\/td>
    <\/td> <\/tr>
    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).
    <\/td>     		Required
    <\/td>
    <\/td>
    <\/td> <\/tr>
    Experience with different LLMs, both commercial and open source, and their capabilities (e.g., OpenAI, Gemini, Llama, Qwen, Claude).
    <\/td>     		Required
    <\/td>
    <\/td>
    <\/td> <\/tr>
    Recent hands\-on experience with MLOps tools and practices, ensuring seamless integration of machine learning models into production environments.
    <\/td>     		Required
    <\/td>
    <\/td>
    <\/td> <\/tr>
    Recent hands on experience with model fine\-tuning techniques such as DPO and RLHF.
    <\/td>     		Required
    <\/td>
    <\/td>
    <\/td> <\/tr>
    Excellent ability to communicate ideas and results to stakeholders and leadership in a clear and concise manner
    <\/td>     		Required
    <\/td>
    <\/td>
    <\/td> <\/tr>
    Knowledge of financial products and services including trading, investment and risk management
    <\/td>     		Required
    <\/td>
    <\/td>
    <\/td> <\/tr> <\/tbody> <\/table> <\/div>

    <\/div><\/span>

    Benefits<\/h3>

    Benefit Package includes:<\/span> <\/span><\/span><\/span>
    <\/span><\/span><\/p> <\/div>

    • Paid Sick Time<\/span><\/span><\/span> <\/span><\/span>
      <\/span><\/span><\/p><\/li> <\/ul> <\/div>

      • Insurance for Medical, Dental, Vision and Life Available<\/span><\/span><\/span> <\/span><\/span>
        <\/span><\/span><\/p><\/li> <\/ul> <\/div>

        • 401(k) including Employer Match <\/span><\/span><\/span> <\/span><\/span>
          <\/span><\/span><\/p><\/li> <\/ul> <\/div>

          • HSA or FSA, Short\-term & Long\-term Disability Available <\/span><\/span><\/span> <\/span><\/span>
            <\/span><\/span><\/p><\/li> <\/ul> <\/div>

            • We are an EEO\/Veterans\/Disabled employer<\/span><\/span><\/span>
              <\/span><\/span><\/p><\/li> <\/ul> <\/div>


              <\/div><\/span>
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