Senior Machine Learning Engineer

The Crown Is Yours

As a Senior Machine Learning Engineer on the Lottery Intelligence Team, you'll build and scale machine learning solutions that turn complex operational data into accurate, reliable customer experiences. You'll lead the development of computer vision and multimodal models, taking innovative solutions from experimentation to real-world deployment. Working alongside Engineering and cross-functional teams, you'll improve model performance, strengthen customer trust, and help expand lottery fulfillment capabilities into new markets nationwide.

What you'll do as a Senior Machine Learning Engineer

• Design, train, and optimize computer vision and multimodal machine learning models that transform complex inputs into accurate, structured data.
• Fine-tune and evaluate multimodal models using techniques such as LoRA and hyperparameter optimization to improve accuracy, speed, and cost efficiency.
• Build and maintain scalable data pipelines that prepare, validate, and organize production data for model training, testing, and evaluation.
• Develop robust evaluation frameworks and performance metrics to compare models, measure accuracy, and guide deployment decisions.
• Deploy and manage machine learning models on scalable cloud infrastructure, using automated scaling, monitoring, and controlled rollouts to maintain reliable performance.
• Integrate machine learning models into real-time processing systems and enhance computer vision capabilities, including image preprocessing, barcode decoding, and optical character recognition.
• Partner with Engineering, Fulfillment Operations, and other cross-functional teams to identify opportunities, improve operational workflows, and strengthen the systems supporting lottery fulfillment.
• Elevate engineering standards through code reviews, technical documentation, automated testing, and mentorship while contributing to the team's broader data infrastructure.

What you'll bring

• A Bachelor's Degree in Computer Science, Engineering, Mathematics, Data Science, or a related field, or equivalent practical experience, with at least 3 years of machine learning engineering experience.
• Proven experience developing, deploying, and maintaining machine learning models in production environments.
• Strong proficiency in Python and software engineering best practices, including automated testing, data validation, and asynchronous programming.
• Hands-on experience with computer vision, multimodal or vision-language models, and machine learning frameworks such as PyTorch, Hugging Face Transformers, PEFT, or vLLM.
• Experience with model fine-tuning, prompt design, performance evaluation, and image processing tools such as OpenCV.
• Experience with cloud-based machine learning platforms, preferably Google Cloud, and familiarity with containerization, orchestration, and monitoring tools such as Docker, Kubernetes, GitHub Actions, or Datadog.
• Strong technical ownership, problem-solving, and communication skills, with the ability to lead complex initiatives, explain technical decisions, and collaborate across teams.
• Familiarity with Kotlin, Java, message-driven architectures, or Protocol Buffers is a plus, as is experience in lottery, gaming, financial technology, or other regulated industries.

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