Senior Machine Learning Engineer

Jobgether; United States; Remote; USD 134,000 - 168,000; Full time

Benefits offered by this job

Remote work within the United States

Bonus opportunities and equity

Benefits package

Full-time employment

Opportunity to work on cutting-edge ML

Possible gaming license considerations

Job summary

Jobgether is seeking a Senior Machine Learning Engineer based in the United States to design, train, and scale computer vision and multimodal models that drive accurate customer experiences. You will lead model development from experimentation to production, building robust data pipelines and evaluation frameworks for reliable performance.

You will deploy models on scalable cloud infrastructure, enabling real-time processing and cross-functional collaboration with Engineering and Fulfillment

Qualifications

• Bachelor's degree in Computer Science, Engineering, Mathematics, Data Science, or equivalent practical experience.
• At least 3 years of experience in machine learning engineering.
• Proven experience deploying ML models in production environments.
• Strong proficiency in Python and software engineering best practices.
• Hands-on experience with computer vision, multimodal models, or vision-language models.
• Familiarity with PyTorch, Hugging Face Transformers, PEFT, or vLLM.
• Experience with model fine-tuning, prompt design, evaluation, and image processing tools such as OpenCV.
• Experience with Google Cloud or cloud ML platforms.
• Familiarity with Docker, Kubernetes, GitHub Actions, Datadog.
• Strong ownership, analytical thinking, and ability to lead complex initiatives.
• Excellent communication and collaboration skills across teams.
• Familiarity with Kotlin/Java or protobuf is a plus.
• Experience in lottery, gaming, fintech or regulated industries is a plus.

Responsibilities

• Design, train, and optimize computer vision and multimodal ML models.
• Fine-tune and evaluate multimodal models using techniques like LoRA.
• Build scalable data pipelines for model training and evaluation.
• Develop robust evaluation frameworks and performance metrics.
• Deploy and manage models on scalable cloud infrastructure with monitoring.
• Integrate models into real-time processing systems (OCR, barcode decoding).
• Collaborate with cross-functional teams to improve workflows and systems.
• Promote engineering excellence via code reviews and automated testing.
• Contribute to team data infrastructure improvements.

Skills

Python programming

Analytical thinking

Problem solving

Strong communication

Education

Bachelor's degree in CS/Engineering/Math/Data Science

Tools

PyTorch

Hugging Face Transformers

PEFT

vLLM

OpenCV

Docker

Kubernetes

GitHub Actions

Job description

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

• 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.

We appreciate your interest and wish you the best! 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. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.