This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Machine Learning Engineer based in the United States.
The Senior Machine Learning Engineer will develop and scale advanced machine learning solutions that transform complex operational data into accurate, reliable customer experiences. In this role, you will lead the development of computer vision and multimodal models, taking innovative approaches from experimentation through production deployment. You will fine-tune models, build robust data pipelines, and establish evaluation frameworks to continuously improve accuracy, performance, and efficiency. Working across Engineering and Fulfillment Operations, you will help strengthen real-time processing systems and expand service capabilities into new markets. You will also contribute to scalable cloud infrastructure, reliable model monitoring, and high engineering standards. This is an opportunity to combine technical leadership and hands-on machine learning expertise in a fast-moving, innovation-driven environment.
Accountabilities
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Design, train, and optimize computer vision and multimodal machine learning models that convert complex inputs into accurate, structured data.
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Fine-tune and evaluate multimodal models using techniques such as Low-Rank Adaptation (LoRA) and hyperparameter optimization to improve accuracy, speed, and cost efficiency.
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Build and maintain scalable data pipelines to prepare, validate, and organize production data for model training, testing, and evaluation.
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Develop robust evaluation frameworks and performance metrics to compare models, measure accuracy, and guide deployment decisions.
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Deploy and manage machine learning models on scalable cloud infrastructure, using automated scaling, monitoring, and controlled rollouts to maintain reliable performance.
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Integrate machine learning models into real-time processing systems and enhance computer vision capabilities, including image preprocessing, barcode decoding, and optical character recognition (OCR).
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Collaborate with Engineering, Fulfillment Operations, and other cross-functional teams to identify opportunities, improve workflows, and strengthen systems supporting lottery fulfillment.
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Promote engineering excellence through code reviews, technical documentation, automated testing, and mentorship.
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Contribute to the development and improvement of the team's broader data infrastructure.
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Bachelor's degree in Computer Science, Engineering, Mathematics, Data Science, or a related discipline, or equivalent practical experience.
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At least 3 years of experience in machine learning engineering.
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Proven experience developing, deploying, and maintaining machine learning models in production environments.
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Strong proficiency in Python and software engineering best practices, including automated testing, data validation, and asynchronous programming.
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Hands-on experience with computer vision, multimodal models, or vision-language models.
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Familiarity with machine learning frameworks and libraries such as PyTorch, Hugging Face Transformers, PEFT, or vLLM.
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Experience with model fine-tuning, prompt design, performance evaluation, and image processing tools such as OpenCV.
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Experience with cloud-based machine learning platforms, preferably Google Cloud.
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Familiarity with containerization, orchestration, and monitoring tools such as Docker, Kubernetes, GitHub Actions, or Datadog.
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Strong technical ownership, analytical thinking, and problem-solving skills, with the ability to lead complex initiatives and make sound technical decisions.
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Excellent communication and collaboration skills, including the ability to explain technical concepts and work effectively across teams.
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Familiarity with Kotlin, Java, message-driven architectures, or Protocol Buffers is an advantage.
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Experience in lottery, gaming, financial technology, or other regulated industries is considered a plus.
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Salary: US annual base salary range of $134,400–$168,000, depending on work location, relevant skills, experience, education, and training.
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Bonus opportunities and equity compensation, as applicable.
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Benefits package for eligible employees.
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Opportunity to work remotely within the United States.
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Full-time employment.
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Opportunity to develop and deploy advanced machine learning and computer vision solutions with real-world operational impact.
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Potential requirement to obtain a gaming license from the relevant state agency as a condition of employment.