Machine Learning Engineer

🕒 March 20

🏄 California – Remote

🏄 California – Remote

💵 $160k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

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Swish Analytics

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2014

🎲 Gambling

🤖 Artificial Intelligence

🤝 B2B

💰 $6.9M Series B - Swish Analytics on 2019-05

Gambling • Artificial Intelligence • B2B

Swish Analytics is a machine-learning driven sports-odds and predictive-data company that builds a real-time odds origination engine for sportsbooks and fantasy platforms. It provides hyper-accurate player prop pricing, match and team markets, in-play and pre-game projections, and automated bet-lifecycle management to power bookmaking, bet builders, parlays, and micro-markets. Swish positions itself as a B2B provider focused on automation, accuracy, and scalable odds infrastructure for the sports betting industry.

📋 Description

• Design, prototype, implement, evaluate, optimize systems to generate sports datasets and predictions with high accuracy and low latency. • Evaluate internal modeling frameworks and tools to optimize data scientist's modeling workflow. • Build, test, deploy and maintain production systems. • Work closely with DevOps and Data Engineering teams to assist with implementation, optimization and scale workloads on Kubernetes using CI/CD, automation tools and scripting languages. • 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. • Experience applying large scale data processing techniques to develop scalable and innovative sports betting products. • Use extensive experience to build, test, debug, and deploy production-grade components. • Participate in development of database structures that fit into the overall architecture of Swish systems.

🎯 Requirements

• Masters degree in Computer Science, Applied Mathematics, Data Science, Computational Physics/Chemistry or related technical subject area • 5+ years of demonstrated experience developing and delivering clean and efficient production code to serve business needs • A proven background in quantitative analytics, trading, or engineering is required for this position • Demonstrated experience developing data science modeling systems and infrastructure at scale • Experience with Python and exposure to modern machine learning frameworks • Proficient in SQL; experience with MySQL • Background and/or interest in Rust preferred • Affinity for teamwork and collaboration with others to solve problems, share knowledge, and provide feedback • Strong communication skills when discussing technical concepts with technical and non-technical colleagues.

🏖️ Benefits

• None specified