Product Engineer (MLOps) San Francisco, CA - Remote

HaylieRead Interior Design; San Francisco (CA); Remote; USD 200,000 - 250,000; Full time

Job summary

An innovative startup is seeking a passionate Machine Learning Engineer to join their dynamic Data Science team. This remote position offers the opportunity to work on cutting-edge predictive sports analytics products, where you'll design and implement high-performance systems for generating sports datasets and predictions. You'll collaborate closely with DevOps and Data Engineering teams, ensuring the optimization and scalability of workloads. If you thrive in a fast-paced environment and have a strong background in machine learning and statistical modeling, this role is perfect for you. Join a forward-thinking company where your contributions will directly impact the sports analytics industry!

Qualifications

• 5+ years of experience in developing clean and efficient production code.
• Masters degree in a technical field required.

Responsibilities

• Design and implement systems to generate sports datasets and predictions.
• Collaborate with DevOps and Data Engineering teams for optimization.

Skills

Machine Learning

Statistical Modeling

Data Validation

Feature Engineering

Data Visualization

Collaboration

Communication Skills

Education

Masters in Computer Science

Masters in Applied Mathematics

Masters in Data Science

Tools

Python

SQL

MySQL

Kubernetes

CI/CD

Rust

Job description

Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and enterprise clients.

The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch. They can assist with optimizing the different aspects of the modeling process (Data Validation, Data Visualization, Data Stores & Structures, Feature Engineering, Model Training & Evaluation, Deployments) and improving a variety of Swish products. They will know when to “roll your own” and when to outsource a particular step in the modeling process. They will engineer custom solutions to solve complex data-related sports challenges across multiple leagues.

This position is 100% remote

Responsibilities:

• 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.

Qualifications:

• 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.
• 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 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.

Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law.