As an AI/ML Engineer, you will design and implement advanced machine learning models, work with Large Language Models (LLMs) and computer vi... Read More
As an AI/ML Engineer, you will design and implement advanced machine learning models, work with Large Language Models (LLMs) and computer vision to drive business outcomes. Your role will involve optimizing models, maintaining backend infrastructure, and collaborating with cross-functional teams to deliver scalable AI solutions. You’ll stay up-to-date with the latest AI research while making impactful contributions in a fast-paced environment.
Key Responsibilities:
Design and implement machine learning models ensuring high performance and accuracy.
Work with Large Language Models (LLMs) to develop solutions.
Conduct detailed EDA, build data pipelines, and ensure data quality.
Collaborate on the use of computer vision to address business-specific needs.
Optimize machine learning models for high performance and scalability.
Implement and maintain backend infrastructure to support AI systems.
Work closely with cross-functional teams to deliver solutions that align with business objectives.
Stay up-to-date with the latest AI research and advancements.
Contribute to the codebase, uphold best practices, and ensure comprehensive documentation.
Required Knowledge, Skills, and Abilities:
Strong understanding of backend systems, including API design, integration, and database management.
Proven experience with AI and deep learning frameworks such as TensorFlow or PyTorch.
Experience with model tuning and optimization to ensure high performance, accuracy, and scalability.
Familiarity with NLP techniques and hands-on experience working with LLMs for developing AI solutions to enhance business outcomes and customer satisfaction.
Proficiency in data manipulation and analysis using tools like pandas and numpy.
Proficiency in computer vision techniques and models to address business-specific challenges.
Excellent communication skills and the ability to work effectively in a collaborative team environment.
Education + Experience:
2+ years of experience in a related field.
Apply Instruction:
Interested candidates fulfilling the mentioned criteria are encouraged to Apply using the Easy Apply Button below. Registered candidates may also apply using the Apply Now Button.
The Data Scientist will play a critical role in solving complex challenges related to unstructured data and developing knowledge driven insights ... Read More
The Data Scientist will play a critical role in solving complex challenges related to unstructured data and developing knowledge driven insights using knowledge graphs, machine learning, and large language models (LLMs). This role requires expertise in data science, graph-based data modeling, and experience working with APIs for large language models like OpenAI, Hugging Face, or similar. Success will be measured by the ability to transform unstructured data into actionable insights, create scalable knowledge representations, and enhance decision-making processes across Yirifi’s operations.
Responsibilities and Deliverables
Unstructured Data Analysis
Develop methods to extract, process, and analyze unstructured data (e.g., text, images, and logs) using advanced machine learning and natural language processing (NLP) techniques.
Leverage LLM APIs to extract meaningful insights, perform summarization, and generate structured outputs from raw data.
Knowledge Graph Development
Design and construct knowledge graphs using tools like Neo4j and semantic web technologies (RDF, OWL).
Develop and implement ontologies, taxonomies, and schema definitions to represent relationships within the data.
LLM Integration
Work with LLM APIs (e.g., OpenAI, Hugging Face) to build pipelines that enhance data processing and generate contextual insights.
Fine-tune or adapt LLMs for specific use cases like document classification, regulatory compliance, and entity extraction.
Machine Learning and Advanced Analytics
Build predictive and descriptive models using machine learning techniques to uncover patterns and insights in complex datasets.
Apply graph-based machine learning for link prediction, anomaly detection, and graph embeddings.
Collaborate with Engineering Teams
Work closely with data engineers to develop scalable data pipelines that support knowledge graph development, LLM integration, and machine learning workflows.
Partner with product teams to translate analytical findings into actionable solutions.
Data Visualization and Storytelling
Create intuitive visualizations to represent insights from knowledge graphs, machine learning models, and LLM outputs.
Develop dashboards and tools that allow stakeholders to explore and interact with analytical results.
Data Quality and Governance
Implement data validation frameworks to ensure the accuracy and reliability of unstructured data and graph models.
Ensure compliance with data governance and security standards.
Emerging Technologies and Research
Stay updated on the latest advancements in data science, knowledge graphs, LLMs, and machine learning.
Pilot and implement cutting-edge techniques to enhance Yirifi’s data science capabilities.
Key Performance Indicators (KPIs)
Model Performance: Maintain high accuracy (e.g., >90%) in predictive and descriptive models.
Knowledge Graph Utilization: Achieve 95% representation of critical entities and relationships in the knowledge graph.
LLM Integration Success: Successfully implement at least 3 LLM-based use cases for unstructured data processing and insights.
Data Insights Delivery: Deliver actionable insights from unstructured data within defined project timelines.
Collaboration Success: Positive feedback from cross-functional teams on the utility and accessibility of analytical outputs.
Required Knowledge, Skills, and Abilities:
Data Science and Analytics:
Expertise in machine learning, NLP, and graph-based data analysis.
Strong knowledge of graph-based algorithms, including PageRank, shortest path, and community detection.
LLM Expertise:
Experience working with LLM APIs like OpenAI, Hugging Face, or equivalent for tasks such as summarization, classification, and entity extraction.
Knowledge of fine-tuning or prompt engineering techniques for LLMs is a plus.
Knowledge Graphs and Ontologies:
Proficiency in knowledge graph tools like Neo4j and semantic web technologies (RDF, OWL, SPARQL).
Experience designing and implementing ontologies and taxonomies.
Programming:
Proficiency in Python, with experience in libraries like Scikit-learn, TensorFlow, PyTorch, Transformers, and NetworkX.
Familiarity with data manipulation libraries like Pandas and NumPy.
Unstructured Data Processing:
Experience working with unstructured data sources (e.g., text, images, logs).
Hands-on experience with NLP libraries (e.g., SpaCy, NLTK, or Hugging Face).
Big Data Tools and Infrastructure:
Familiarity with distributed data processing tools like Apache Spark and cloud platforms like AWS or GCP.
Visualization and Reporting:
Proficiency in data visualization tools like Tableau, Power BI, or Matplotlib/Seaborn.
Soft Skills
Problem-Solving: Strong analytical and problem-solving skills, particularly in unstructured data environments.
Collaboration: Excellent communication skills to work effectively with cross-functional teams.
Adaptability: Ability to work in a fast-paced startup environment and manage multiple priorities.
Attention to Detail: A meticulous approach to data quality and model validation.
Education + Experience:
3+ years of experience working with LLM APIs like OpenAI, Hugging Face, or equivalent for tasks such as summarization, classification, and entity extraction.
Job Benefits:
Be part of a dynamic team that is redefining the crypto risk and compliance industry. As a Data Scientist at Yirifi, you’ll tackle complex challenges, work on cutting-edge technologies, and directly contribute to building innovative solutions with LLMs, knowledge graphs, and advanced analytics. Join us to make an impact and grow your career in a fast-paced, high-growth environment!
Apply Instruction:
Interested candidates fulfilling the mentioned criteria are encouraged to Apply using the Easy Apply Button below. Registered candidates may also apply using Apply Now Button.
