Senior Finance ML Engineer

Genesys empowers organizations of all sizes to improve loyalty and business outcomes by creating the best experiences for their customers and employees. Through Genesys Cloud, the AI-powered Experience Orchestration platform, organizations can accelerate growth by delivering empathetic, personalized experiences at scale to drive customer loyalty, workforce engagement, efficiency and operational improvements.

We employ more than 6,000 people across the globe who embrace empathy and cultivate collaboration to succeed. And, while we offer great benefits and perks like larger tech companies, our employees have the independence to make a larger impact on the company and take ownership of their work. Join the team and create the future of customer experience together.

We are seeking an experienced Machine Learning Engineer to be a part of impactful data-driven initiatives across the organization. This role will leverage machine learning, LLM, and data engineering skillsets to improve operational efficiency and drive strategic decision-making. The ideal candidate will have expertise in model development, deployment, and interpretation, combined with foundation data engineering skills. You will collaborate with cross-functional teams to ensure models deliver measurable business value while being a champion for data best practices.

Key Responsibilities:

LLM and ML Model Development

• Design, develop, and test scalable machine learning models with a focus on reducing manual forecasting.

• Build and optimize time series models for forecasting customer usage, renewal rates, and various segments of revenue.

• Create diverse agents using Amazon Bedrock to expand and improve existing agentic systems enabling tasks related to revenue, bookings, and expenses.

Model Deployment and Monitoring

• Leverage MLOps best practices to develop systems for model deployment, monitoring, retraining, and lineage tracking to maintain accuracy over time.

• Build AI agents with SOX compliance and security in mind by instituting guardrails, deny-lists, and systems for model auditing.

Data Engineering and Feature Creation

• Assist in the migration and expansion of existing data pipelines into a new architecture meant to support the team's centralized data initiatives.

• Design and implement innovative features to enhance predictive accuracy, particularly for time series and customer behavior models.

• Work extensively with finance data to identify business risks, project opportunities, and strategic customers.

Cross-Functional Collaboration and Communication

• Partner with finance, product, and operational teams to align data science solutions with business objectives.

• Translate complex machine learning outcomes into actionable insights and compelling narratives for both technical and non-technical audiences.

Key Qualifications:

• 4+ years of experience in data science roles, with proven expertise in model deployment and integration into production environments with at least 1yr building and testing GenAI or LLMbased applications (Bedrock, OpenAI, Anthropic, etc.)

• Strong proficiency in Python, SQL, and statistical modeling techniques.

• Experience building production data pipelines in AWS.

• Experience with time series analysis and advanced feature engineering.

• Deep knowledge of MLOps best practices and tools for scalable deployment.

• Proven experience working with finance datasets and SOX compliance requirements

What Sets You Apart:

• A track record of reducing technical debt through robust model architecture and deployment strategies.

• History of building observability pipelines model drift in production.

• Experience implementing LLM guardrails for sensitive information

• A passion for the future of data science, continuously striving to learn and implement new techniques and technologies.

• Familiarity with testing and tuning large language models (LLMs).

• Experience with agile methodologies and Git flow.

#LI-Remote

Compensation:

This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate's experience, qualifications, skills, and location. This role might also be eligible for a commission or performance-based bonus opportunities.

Benefits:

• Medical, Dental, and Vision Insurance.

• Telehealth coverage

• Flexible work schedules and work from home opportunities

• Development and career growth opportunities

• Open Time Off in addition to 10 paid holidays

• 401(k) matching program

• Adoption Assistance

• Fertility treatments

More details about our company benefits can be found at the following link:https://mygenesysbenefits.com

If a Genesys employee referred you, please use the link they sent you to apply.

About Genesys:

Genesys empowers more than 8,000 organizations in over 100 countries to improve loyalty and business outcomes by creating the best experiences for their customers and employees. Through Genesys Cloud, the AI-powered Experience Orchestration platform, Genesys delivers the future of CX to organizations of all sizes so they can provide empathetic, personalized experience at scale. As the trusted platform that is born in the cloud, Genesys Cloud helps organizations accelerate growth by enabling them to differentiate with the right customer experience at the right time, while driving stronger workforce engagement, efficiency and operational improvements. Visitwww.genesys.com.

Reasonable Accommodations:

If you require a reasonable accommodation to complete any part of the application process, or are limited in your ability to access or use this online application and need an alternative method for applying, you or someone you know may contact us at reasonable.accommodations@genesys.com.

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Genesys is an equal opportunity employer committed to fairness in the workplace. We evaluate qualified applicants without regard to race, color, age, religion, sex, sexual orientation, gender identity or expression,marital status, domestic partner status,national origin, genetics, disability,military andveteran status, and other protected characteristics.

Please note that recruiters will never ask for sensitive personal or financial information during the application phase.