Description

Company Description

Hybopay seeks a talented and passionate Machine Learning Engineer to join our growing team. In this role, you will design, develop, and deploy cutting-edge machine learning solutions, focusing on leveraging large language models (LLMs) to solve real-world problems. You will be a key contributor to developing innovative applications that push the boundaries of what’s possible with AI.

Hybopay is dedicated to revolutionizing customer support by providing accurate, secure, and real-time machine translation services. Hybopay is an application developer with expertise in GenAI. We sell products and services in the Gen AI markets for financial GenAI copilot or virtual assistant applications and consulting services. We sell GenAI virtual assistant financial applications to Fintech partners, banks, and merchants across different business divisions. We are searching for a Machine Learning Azure Synapse ML expert who will develop our financial products in our already existing Azure Document Embedding services into the next phase of Azure AI services and financial LLM models, using prompt flow and Azure Open AI and Synapse ML. With our financial tools newly developed products and implementation consulting services, we want to revolutionize the financial application LLM co-pilot market. Join us in our mission to revolutionize the GenAI markets in data-driven markets and economies.

Role Description

This is a part-time remote role for a Machine Learning Engineer at Hybopay. As a Machine Learning Engineer, you will be responsible for developing and implementing machine learning models and algorithms, collaborating with cross-functional teams to drive business solutions. You will work on exciting projects in a remote setting.

This is a part-time, stock options position, non-salaried position, working 100% remotely from any US location.

Qualifications

• Proficiency in Python and other programming languages
• Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn
• Strong understanding of algorithms, data structures, and statistics
• Knowledge of deep learning, natural language processing, and computer vision
• Ability to work independently and in a team, with strong communication skills
• Bachelor’s degree in Computer Science, Engineering, or related field
• Experience with cloud services like AWS or Azure
• Previous experience in machine learning projects or internships is a plus

Machine Learning Engineer Azure Synapse ML

Hybopay seeks a talented and passionate Machine Learning Engineer to join our growing team. In this role, you will design, develop, and deploy cutting-edge machine learning solutions, focusing on leveraging large language models (LLMs) to solve real-world problems. You will be a key contributor to developing innovative applications that push the boundaries of what’s possible with AI.

Hybopay is dedicated to revolutionizing customer support by providing accurate, secure, and real-time machine translation services. Hybopay is an application developer with expertise in GenAI. We sell products and services in the Gen AI markets for financial GenAI copilot or virtual assistant applications and consulting services. We sell GenAI virtual assistant financial applications to Fintech partners, banks, and merchants across different business divisions. We are searching for a Machine Learning Azure Synapse ML expert, who will develop our financial products in our already existing Azure Document Embedding services into the next phase of Azure AI services and financial LLM models, using prompt flow and Azure Open AI and Synapse ML. With our financial tools newly developed products and implementation consulting services, we want to revolutionize the financial application LLM co-pilot market. Join us in our mission to revolutionize the GenAI markets in data-driven markets and economies.

Requirements

• Lead Innovation: Design and deploy a state-of-the-art retrieval-augmented-generation (RAG) conversational agent, leveraging a vast and intricate proprietary dataset.
• Collaborate for Success: Partner with product managers, content managers, and senior stakeholders to develop, optimize, and launch advanced AI/ML/LLM/GenAI solutions that align with business goals and user needs.
• Ensure Excellence: Optimise LLMs, datasets, and agent workflows to uphold the highest quality standards, minimizing hallucinations and output errors.
• Technical Mastery: Deploy and maintain RAG architecture and LLM pipelines within cloud environments, ensuring top-tier performance.
• Enhance Performance: Fine-tune data chunks and text embeddings for superior semantic search across a specialized text corpus.
• Stay Ahead: Keep abreast of the competitive landscape and technological advancements within the GenAI field.

• At least 3-5 years of proven experience in machine learning and software engineering.
• Strong coding skills in Python, Knowledge of Azure Synapse ML, Synapse Studio, Spark, Azure Factory, Azure Blob Storage, Prompt flow, Azure Open AI, Azure AI Services,
• RAG model Knowledge is an Architecture you must be familiar with
• You must bring Azure Cognitive Search and Azure Document Intelligence to the next level with Azure AI services and Azure Prompt flow
• Proven experience building applications with Large Language Models. Experience with Google’s Gemini is a plus.
• Proficiency in SQL, with PostgreSQL experience being a plus.
• Excellent communication skills, both written and verbal.
• Stay Ahead: Keep abreast of the competitive landscape and technological advancements within the GenAI field.
• Optimize Operations: Monitor and enhance agent and model latency and performance, analyzing user feedback for continuous improvement.
• Share Insights: Communicate utilization and user feedback reports to stakeholders.
• Mentor and Educate: Guide and inspire engineering staff and the broader business community.

Responsibilities

• Build applications that leverage the power of Large Language Models to solve complex business problems.
• Develop and maintain data pipelines for efficient data ingestion, processing, and feature engineering.
• Stay up-to-date with the latest advancements and research in machine learning, particularly in the field of Large Language Models.

Nice to haves

• Experience working in a Scrum environment.
• Familiarity with AWS cloud services.
• Proficiency in reading and writing in languages other than English.
• General NLP experience, including text embeddings and cosine similarity.
• Experience with REST APIs, JSON, Python, Pytorch.