About the Role
FIS's AI Platform organization builds the models, infrastructure, and practices that help teams across FIS bring AI into production safely and at scale.
We are looking for a Software Machine Learning Engineer to build domain-specific foundation and embedding models for financial data. These models learn useful representations from large volumes of financial activity, and many products and teams can reuse them across a range of use cases.
You will work across the full model lifecycle: data preparation, pretraining, fine-tuning, evaluation, and packaging models so other teams can use them. You will work with platform, data, and product engineering teams to turn research into reliable, well-governed models in production.
What You Will Do
•Build and improve deep learning models on large-scale financial data, including sequence modeling, pretraining, and fine-tuning of transformer-based models.
•Produce reusable, versioned embeddings and model artifacts that downstream teams can easily use.
•Design models that generalize across tasks and datasets, and measure how well they perform on downstream problems.
•Work with data and infrastructure engineers on training pipelines, data lineage, and reproducible experiments.
•Work with serving engineers to optimize models for efficient, low-latency inference.
•Build sound evaluation into the workflow, including time-based testing and imbalanced or delayed labels.
•Support product and engineering teams as they integrate models, with clear documentation and interfaces.
•Balance model quality against compute cost, and report results in terms of business impact.
•Work with risk and governance partners so models are explainable, well documented, and meet regulatory expectations.
Required Qualifications
•Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience.
•4+ years of experience building and deploying machine learning models in production.
•Strong programming skills in Python and experience with modern deep learning tools such as PyTorch.
•Hands-on experience pretraining, training, or fine-tuning transformer or other deep learning models on GPUs.
•Experience working with large datasets and ML pipelines on cloud platforms (AWS, Azure, or GCP), with tools such as Spark, Snowflake, or Databricks.
•Solid ML fundamentals, including representation learning, offline evaluation, handling imbalanced data, and choosing the right metrics.
•Good engineering habits: version control, testing, reproducible experiments, and code that others can build on.
•Ability to explain technical results clearly to non-technical audiences.
•Strong collaboration skills and comfort working across engineering, product, and risk teams.
Preferred Qualifications
•Experience with sequence modeling, self-supervised learning, or embedding models for tabular or event data.
•Experience with financial services or payments data.
•Experience with distributed training and GPU-accelerated ML frameworks.
•Experience with inference optimization (quantization, distillation, batching) or real-time ML systems.
•Experience with MLflow, model registries, feature stores, or other MLOps tools.
•Experience working in a regulated environment, including model risk management and model documentation.
What Success Looks Like
•High-quality, reusable models that perform well across more than one downstream task.
•Reproducible, well-documented models and artifacts that pass internal review.
•Models adopted by product teams in production, with measurable improvement over existing approaches.
•Strong working relationships across platform, data, product, and risk teams.
Why Join Us?
You will help build core AI capabilities at one of the world's largest fintech companies, with work that reaches financial institutions and the people they serve. You will work with experienced ML engineers, platform engineers, and data scientists.
What We Offer You
•Opportunities to make an impact in fintech
•Personal and professional learning
•Inclusive, diverse work environment
•Resources to give back to your community
•Competitive salary and benefits
The pay range for this full-time position is $173,680.00 - $295,250.00 and reflects the minimum and maximum target for new hire salaries for this position based on the posted role, level, and location. Within the range, actual individual starting pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Any changes in work location will also impact actual individual starting pay. Please consult with your recruiter about the specific salary range for your preferred location during the hiring process.
