5 months ago
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.
- Drive the design and evolution of ML platform capabilities, including CLI, SDK, infrastructure automation, and platform applications.
- Influence adoption of ML and GenAI/LLM platform solutions across partner 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, cost-efficient production data and ML systems.
- Operate with end-to-end ownership of key data and ML platform architecture components.
- Set engineering standards and mentor junior engineers in system design, reliability, automation, data quality, and operational excellence.
- Collaborate with downstream engineering teams, upstream data teams, Data Scientists, Analysts, leadership, and partner teams.
Requirements
- At least 7 years of relevant experience developing code in core programming languages such as Python or Java.
- At least 4 years of experience designing scalable software architectures for ML, search, or LLM workloads.
- At least 2 years of production experience with vector search, semantic search, or embedding-based retrieval and vector stores such as AWS OpenSearch or Elasticsearch.
- At least 2 years of experience building platform components and frameworks that improve ML/AI development and deployment efficiency.
- At least 1 year of experience driving technical direction, making architectural trade-offs, and influencing engineering decisions across teams.
- At least 1 year of cross-functional experience working with leadership and influencing partner teams to adopt platform capabilities and best practices.
- At least 1 year of experience conducting design reviews and setting engineering standards.
- Experience with data and streaming technologies including Spark, Flink, Kafka, Airflow, or Terraform.
- Experience working in AWS, GCP, or Azure cloud environments.
- 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 complex technical projects end-to-end 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 outputs to improve relevance.
- Preferred experience deploying ML and GenAI/LLM models in production under scalability, correctness, and maintainability constraints.
- Hands-on experience with Scikit-learn, PyTorch, TensorFlow, and LLM frameworks is preferred.
- Hands-on experience with ML and GenAI/LLM platforms such as SageMaker, Bedrock, or Databricks is preferred.
Benefits
- Health, vision, and dental insurance, including fertility and family-planning programs
- Mental health support and fitness benefits
- Paid time off, sick leave, and 14 paid company holidays
- 401(k) with up to a 5% company match
- Commuter benefits and pet insurance
- Annual bonus and long-term incentive opportunities based on performance
- Potential eligibility for cash bonuses and stock program participation
- Hybrid work arrangement indicated by the #LI-Hybrid designation
Tech Stack
Apache AirflowApache FlinkApache KafkaApache SparkAWSAzureDatabricksElasticsearchGoogle Cloud PlatformJavaPythonPyTorchscikit-learnTensorFlow
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).