MLOps Engineer
Trunk Tools140,000 - 200,000 USD/year
- Full Time
- Junior (1 to 2 years)
Not SpecifiedCompensation
Junior (1 to 2 years)Experience Level
Full TimeJob Type
UnknownVisa
Sports Analytics, Data & Analytics, Betting, Fantasy SportsIndustries
Requirements
Candidates should possess a Master’s degree in Computer Science, Applied Mathematics, Data Science, Computational Physics/Chemistry, or a related technical subject area, along with 5+ years of experience developing and delivering clean and efficient production code to meet business needs. They should have demonstrated experience developing data science modeling systems and infrastructure at scale, and experience with Python and exposure to modern machine learning frameworks.
Responsibilities
The Product Engineer (MLOps) will design, prototype, implement, evaluate, and optimize systems to generate sports datasets and predictions with high accuracy and low latency. They will evaluate internal modeling frameworks and tools to optimize data scientist's modeling workflow, build, test, deploy, and maintain production systems, and work closely with DevOps and Data Engineering teams to assist with implementation, optimization, and scaling workloads on Kubernetes using CI/CD, automation tools, and scripting languages. They will support maintenance and optimization of cloud-native EDW and ETL solutions, maintain and promote best practices for software development, including deployment process, documentation, and coding standards, and participate in the development of database structures that fit into the overall architecture of Swish systems.
Skills
Python
Machine Learning Frameworks
Data Validation
Data Visualization
Data Stores & Structures
Feature Engineering
Model Training & Evaluation
Deployments
Data Science Modeling Systems
Infrastructure Development
Swish Analytics
Sports analytics and optimization tools provider
About Swish Analytics
Swish Analytics specializes in sports analytics and optimization tools for daily fantasy sports and sports betting, focusing on major U.S. leagues like the NFL, MLB, NBA, and NHL. The company uses an advanced machine learning system to analyze large datasets, providing accurate sports predictions and optimized lineups. This helps users, including individual bettors and professional operators, make informed decisions about their bets and fantasy picks. Swish Analytics differentiates itself by being an Authorized MLB Data Distributor, establishing trust in the sports betting community. Operating on a subscription-based model, users can access various levels of tools and analytics, starting with a free trial. The goal of Swish Analytics is to maximize return on investment for clients by identifying the best bets and balancing risk and reward for long-term success.
Key Metrics
San Francisco, CaliforniaHeadquarters
2014Year Founded
$6.5MTotal Funding
EARLY_VCCompany Stage
Fintech, AI & Machine Learning, Financial ServicesIndustries
51-200Employees