5 months ago
Atlanta, GA, USAStaff+
Base Salary
$159k - $209k/yr
Responsibilities
- Design and implement intelligent search systems using typeahead search, vector search, and ML personalization signals
- Own ML and search systems end-to-end from ideation through production
- Build and scale serving architectures for ML and GenAI/LLM models
- Design and evolve CLI, SDK, infrastructure automation, and platform application capabilities for ML and GenAI/LLM development
- Drive technical strategy and adoption of ML and GenAI/LLM platform solutions across engineering teams
- Apply data security, privacy, governance, and data testing practices to reliable and compliant data products
- Own continuous integration and delivery of scalable, reliable, and cost-efficient data and ML systems
- Operate with end-to-end ownership of components of the data and ML platform architecture
- Set engineering standards and mentor junior engineers in system design, reliability, automation, data quality, and operational excellence
Requirements
- 7+ years of relevant experience developing code in core programming languages such as Python or Java
- 4+ years designing and building scalable software architectures for ML, search, or LLM workloads
- 2+ years implementing vector search, semantic search, or embedding-based retrieval systems in production
- 2+ years building platform components and frameworks that improve ML/AI development and deployment efficiency
- At least 1 year driving technical direction, making architectural trade-offs, and influencing engineering decisions across teams
- At least 1 year collaborating cross-functionally with leadership and partner teams
- At least 1 year conducting design reviews and setting engineering standards
- Experience with data and streaming technologies including Spark, Flink, Kafka, Airflow, and Terraform
- Experience working in cloud environments such as AWS, GCP, or Azure
- Experience designing and building production data pipelines for ML and GenAI/LLM systems
- Strong understanding of data structures, distributed systems, and software engineering principles
- Ability to independently own and deliver complex technical projects in ambiguous environments
- Ability to communicate technical concepts through dashboards, data models, or design artifacts
- Track record of mentoring engineers and improving team-wide engineering practices and technical quality
- Preferred: experience with typeahead or autocomplete systems and ML signals for query understanding or ranking
- Preferred: experience combining vector search, typeahead, and personalization retrieval systems
- Preferred: experience deploying production ML and GenAI/LLM models under scalability, correctness, and maintainability constraints
- Preferred: hands-on experience with Scikit-learn, PyTorch, TensorFlow, and LLM frameworks
- Preferred: hands-on experience with ML and GenAI/LLM platforms such as SageMaker, Bedrock, and Databricks
Benefits
- Health plans including fertility and family planning, mental health support, and fitness benefits
- Paid time off and sick leave
- Annual bonus and long-term incentive opportunities based on performance
- 401(k) with up to a 5% match
- Commuter benefits and pet insurance
- Medical, vision, dental, life, and disability insurance
- 14 paid company holidays
- Hybrid work arrangement indicated by #LI-Hybrid
Tech Stack
Apache AirflowApache FlinkApache KafkaApache SparkAWSAzureDatabricksElasticsearchGoogle Cloud PlatformJavaPythonPyTorchscikit-learnTensorFlowTerraform
Categories
About FanDuel
FanDuel builds consumer sports wagering and gaming products in North America, including FanDuel Sportsbook, daily fantasy sports, FanDuel Casino, and horse-racing wagering, plus the FanDuel TV/TV+ media platforms. It earns revenue from consumer bets, fantasy entry fees, and gaming operations, and is available across the U.S., Canada, and Puerto Rico. Founded in 2009 and headquartered in New York, it is a subsidiary of Flutter Entertainment (NYSE: FLUT).