Machine Learning Engineer (LLM RAG)

PurposeThe Senior Machine Learning Engineer is a creative, open-minded problem solver with effective time management and communication skills. The role involves collaboratively working with stakeholders to manage engagements, leading teams of data and analytics resources in the design and delivery of machine learning solutions, including ML Pipelines, AI Integration, and Data Management.The Senior Machine Learning Engineer will leverage Machine Learning Methods and Artificial Intelligence to enhance innovation, profitability, and growth across three dimensions:

1. Business Innovation: Design and implement innovative, data-driven business models, identify and assess use cases, and utilize machine learning models to drive improvements in Sales, Marketing, Operations, and Business Models.
2. Big Data and Analytics: Extract actionable insights from data sources using sophisticated Machine Learning and AI solutions.
3. Digital Transformation: Define and implement strategies for transitioning businesses to "Data-Driven" organizations using machine learning, AI, and digital technologies.

The role involves building scalable ML pipelines, providing end-to-end solutions, and working closely with stakeholders to align ML outputs with business needs.Key Responsibilities

• ML Pipeline Development: Design and implement scalable ML pipelines for data cleaning and processing, incorporating cleaned data and enabling models to recognize products based on descriptions.
• RAG Framework Implementation: Leverage Retrieval-Augmented Generation (RAG) to improve the integration and retrieval of data insights.
• Recommendation Engines: Develop and optimize recommendation systems to align with business needs.
• Collaborative Problem Solving: Engage with the data science network to bring in diverse perspectives and drive innovative solutions.
• Cloud Proficiency: Ensure optimal use of GCP, BigQuery, and Vertex AI tools for data analytics and model deployment.
• Data Insights: Analyze high-dimensionality data, build predictive models, and deliver actionable insights to stakeholders.
• Technical Leadership: Provide hands-on guidance in the design, development, and deployment of ML models.
• Mentorship: Empower and mentor team members to enhance their machine learning capabilities.
• Communication: Effectively interpret and present machine learning results and model outputs to business stakeholders.

Minimum RequirementsWork Experience:

• 5 to 7 years of hands-on experience in machine learning engineering.
• Proven success in applying machine learning methodologies to business outcomes.
• Extensive knowledge of statistical methods and data mining.

Education Level:

• Bachelor’s degree or PhD in Mathematics, Statistics, Engineering, Machine Learning, Artificial Intelligence, or related fields.

Technical Competencies:

• Experience with LLMs (Large Language Models) and designing scalable ML pipelines.
• Expertise in recommendation engines.
• Proficient in machine learning packages such as scikit-learn and TensorFlow.
• Strong programming skills in Python, R, or Scala.
• most essential is to have Proficiency with cloud-based AI/ML tools, especially GCP, BigQuery, and Vertex AI.
• Familiarity with RAG frameworks and implementing them in data solutions.
• Experience in deploying and managing ML models in production environments.
• Knowledge of feature engineering, supervised learning, and clustering techniques.
• Ability to overlay multiple datasets to derive actionable insights.
• Familiarity with Power BI or Google Looker for dashboard development.

Preferred Qualifications

• Knowledge of NLP and image processing techniques.
• Experience with Agile methodologies and working in Scrum Teams.
• Proficiency in at least one deep learning framework.
• Experience with data visualization tools and creating compelling dashboards.
• Background in developing and scaling insights across datasets.

ZPAP Leadership Competencies

• Strategic Orientation and Innovation.
• Collaboration with colleagues and external partners.
• Building and developing teams.
• Making and implementing decisions.
• Continuous learning and self-development.

ZP Core Values

• Integrity & Trust
• Collaboration
• Innovation
• Passion for Excellence
• Personal Growth

Essential Skills:

• Logical and systematic problem-solving abilities.
• Strong interpersonal communication.
• Team player with the ability to work under tight deadlines.
• Flexibility to travel and work off-hours as required.
• This updated job description reflects the prioritized skills and tools essential for the Senior Machine Learning Engineer role, aligning with current project needs and technological advancements.