Accountabilities

Design, train, and optimize computer vision and multimodal machine learning models that convert complex inputs into accurate, structured data.

Fine-tune and evaluate multimodal models using techniques such as Low-Rank Adaptation (LoRA) and hyperparameter optimization to improve accuracy, speed, and cost efficiency.

Build and maintain scalable data pipelines to 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 (OCR).

Collaborate with Engineering, Fulfillment Operations, and other cross-functional teams to identify opportunities, improve workflows, and strengthen systems supporting lottery fulfillment.

Promote engineering excellence through code reviews, technical documentation, automated testing, and mentorship.

Contribute to the development and improvement of the team's broader data infrastructure.

Requirements

Bachelor's degree in Computer Science, Engineering, Mathematics, Data Science, or a related discipline, or equivalent practical experience.

At least 3 years of experience in machine learning engineering.

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 models, or vision-language models.

Familiarity with machine learning frameworks and libraries 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.

Familiarity with containerization, orchestration, and monitoring tools such as Docker, Kubernetes, GitHub Actions, or Datadog.

Strong technical ownership, analytical thinking, and problem-solving skills, with the ability to lead complex initiatives and make sound technical decisions.

Excellent communication and collaboration skills, including the ability to explain technical concepts and work effectively across teams.

Familiarity with Kotlin, Java, message-driven architectures, or Protocol Buffers is an advantage.

Experience in lottery, gaming, financial technology, or other regulated industries is considered a plus.

Benefits

Salary: US annual base salary range of $134,400–$168,000, depending on work location, relevant skills, experience, education, and training.

Bonus opportunities and equity compensation, as applicable.

Benefits package for eligible employees.

Opportunity to work remotely within the United States.

Full-time employment.

Opportunity to develop and deploy advanced machine learning and computer vision solutions with real-world operational impact.

Potential requirement to obtain a gaming license from the relevant state agency as a condition of employment.

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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