Machine Learning Platform Engineer
New
P
PrizePicksDaily Fantasy Sports
While we prefer candidates based in Atlanta, we are open to qualified applicants from anywhere in the U.S. and are willing to consider remote candidates.Full-TimeMiddle
Salary$155,000 to $185,000
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Job Details
- Experience
- 3+ years of experience in Platform Engineering, 1+ years of experience owning ML systems end-to-end in production
- Required Skills
- DockerPythonElasticSearchKafkaKubernetesGoRedisMLOps
Requirements
- 3+ years of experience in Platform Engineering with a focus on scalable ML platform deployment.
- 1+ years of experience owning ML systems end-to-end in production, including on-call responsibilities.
- Proficiency in streaming architectures such as Kafka, Flink, or PubSub.
- Experience building low-latency inference services with <100ms latency.
- Expertise in the full ML lifecycle using tools like SageMaker, VertexAI, Vector DBs, and Graph Databases.
- Experience managing and scaling cache technologies like Redis or Elasticsearch.
- Proficiency in containerization, Docker, and Kubernetes cluster management.
- Expertise in Python and proficiency in Go.
- Strong technical background in Daily Fantasy Sports, oddsmaking, or high-frequency trading (preferred).
- Experience implementing self-service ML and AI agent development (preferred).
Responsibilities
- Design and build end-to-end machine learning infrastructure to transition experimental models into high-availability production services.
- Develop automation for low-latency inference services capable of sub-100ms response times.
- Lead the creation and optimization of a centralized feature store for training complex models.
- Build and operate core ML platform components including training and experimentation pipelines.
- Champion best practices for model deployment, monitoring, and CI/CD for machine learning.
- Implement automated retraining pipelines and observability tools to detect model degradation and data drift.
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