Machine Learning Engineer

Status: 12-Month Contract

Job Title: Machine Learning Engineer

Location: 100% Remote

Salary: $75/hr - $85/hr

About the company:

We've been a pioneer in tax automation for more than 40 years. We proudly serve over 4,000 customers worldwide with distinction and provide comprehensive tax solutions that enable global businesses to transact, comply, and grow with confidence.

Our software, content, and services address the increasing complexities of global commerce and compliance by reducing friction, enhancing transparency, and enabling greater confidence in meeting indirect tax obligations. As a result, our software is ubiquitous within our customers’ business systems, touching nearly every line item of every transaction that an enterprise can conduct. Our software is fueled by over 300 million data-driven effective tax rules and supports indirect tax compliance in more than 19,000 jurisdictions worldwide.

We partner with the world’s most respected companies and harness their strengths to deliver the best tax technology solutions to businesses across the globe. We integrate with key technology partners that span ERP, CRM, procurement, billing, POS, and e-commerce platforms. We also work closely with over 50 tax, accounting, and consulting firms to provide integrated tax technology solutions.

Our culture is the foundation of everything we do, guided by a common purpose to build trusted relationships at work, in business, and in our communities. We strive to be a values-driven employer of choice who attracts, retains, and inspires talented professionals to achieve their full potential. We employ over 1,100 full-time professionals today in the US, Europe, and Brazil.

Machine Learning Engineer:

We are looking for a Machine Learning Engineer to join Vertex Emerging Technology Group to be part of our AI and data insight journey. Additionally, this person will help drive our AI implementations related technologies/solutions to address current and future business opportunities.

This person must have strong experience with prompt engineering, designing, developing/deploying ML systems, implementing appropriate ML algorithms, conducting experiments, and staying updated with the latest developments in the field.

Experience working with data to create models, perform statistical analysis, and train and retrain systems to optimize performance. They must have a proven ability to drive business results with their data-based insights and be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for ML and working with stakeholders to improve business outcomes.

Machine Learning Engineer Responsibilities:

• Solve complex problems with multilayered data sets and optimize existing machine learning libraries and frameworks.
• Collaborate with data scientists, data engineers, and data architects on production systems and applications.
• Identify differences in data distribution that could potentially affect model performance in real-world applications.
• Ensure algorithms generate accurate responses.
• Assess the effectiveness and accuracy of new data sources and execute data-wrangling techniques.
• Develop processes and tools to monitor and analyze model performance and data accuracy.

Machine Learning Engineer Qualifications:

• Experience building and operationalizing retrieval augmented generation (RAG) frameworks.
• Experience utilizing LLMs to provide software automation capability integrations.
• Experience configuring vectors databases for semantic search.
• Experience with LangChain and sentence transformer frameworks.
• Experience with ChatGPT4 (or comparable models).
• Experience with MLOps.
• Strong understanding of AI/ML cloud services and infrastructure, including how to leverage them and experience with SaaS infrastructure technologies (AWS/Azure preferred).
• Experience using Python and SQL to manipulate data and draw insights from large data sets.
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• A drive to learn and master new technologies and techniques.
• Ability to quickly assimilate, organize, analyze, abstract, and synthesize large amounts of information and to make decisions based on this analysis.
• Excellent written and verbal communication skills.
• Ability to present and explain technical concepts to non-technical audiences.
• Comfortable working in a dynamic and changing environment.
• Comfortable working with loosely defined requirements where you exercise your creativity and analytical skills to deliver best-in-class solutions.
• Self-motivated / Creative / Innovative.