Applied Scientist

Machine Learning Engineer / Data Scientist – GenAI & LLM

Location: Seattle, WA

Job Summary

STAFFXPERT LLC is seeking a Machine Learning Engineer / Data Scientist – GenAI & LLM on behalf of our client in [Location] to help build next-generation, AI-powered translation solutions at global scale. The role focuses on Generative AI, Large Language Models (LLMs), NLP, Computer Vision, and OCR to automate the translation of text, image, and video content across 130+ languages and locales.

The ideal candidate will have hands-on experience developing and fine-tuning LLMs, building production-grade machine learning solutions, and applying advanced AI techniques to complex multilingual challenges. This is an opportunity to work in a highly innovative, fast-paced environment and contribute to scalable AI systems processing millions of content assets.

Key Responsibilities

• Design, develop, and deploy scalable Machine Learning and Generative AI solutions for multilingual translation.

• Evaluate, fine-tune, optimize, and deploy LLMs and NLP models for production use cases.

• Develop intelligent solutions to identify translation opportunities across text, images, and video.

• Build and enhance OCR and Computer Vision capabilities for text detection, extraction, and content understanding.

• Evaluate and select foundation models based on accuracy, latency, scalability, and business requirements.

• Develop and maintain AI pipelines supporting translation across 130+ languages and locales.

• Partner with MLOps teams to automate model training, deployment, monitoring, and inference.

• Conduct data analysis, experimentation, and model evaluation to improve AI system performance.

• Develop high-performance, low-latency AI solutions capable of operating at enterprise scale.

• Identify opportunities to automate manual processes throughout the translation lifecycle.

• Collaborate with Machine Learning Engineers, Software Engineers, Data Scientists, Product Managers, and MLOps teams.

• Research emerging advancements in LLMs, NLP, Computer Vision, and Generative AI and apply relevant technologies to the platform.

• Communicate technical findings, solutions, and recommendations effectively to technical and non-technical stakeholders.

Required Qualifications

• Hands-on experience fine-tuning, evaluating, and optimizing Large Language Models (LLMs).

• Strong understanding of foundation models, machine learning, and deep learning concepts beyond prompt engineering.

• Experience designing and deploying production-grade machine learning solutions.

• Strong expertise in NLP, Machine Learning, Deep Learning, or Generative AI.

• Strong programming skills in Python.

• Experience working with large-scale data, AI, or machine learning environments.

• Demonstrated ability to evaluate and select appropriate AI/ML models for business and technical requirements.

• Strong problem-solving, analytical, experimentation, and communication skills.

• Ability to work effectively in a collaborative, cross-functional engineering environment.

Preferred Qualifications

• Experience with OCR and Computer Vision systems.

• Experience with multilingual or machine translation systems.

• Familiarity with MLOps, model hosting, model monitoring, and automated ML pipelines.

• Experience optimizing AI systems for high throughput, scalability, and low latency.

• Experience working with multimodal AI involving text, image, and video.

• Familiarity with modern LLM architectures, fine-tuning techniques, evaluation frameworks, and inference optimization.

• Advanced degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related field.

Why This Opportunity?

Join a high-impact AI initiative focused on building a scalable, highly automated translation ecosystem serving global users across 130+ languages and locales. You will have the opportunity to work on challenging real-world problems spanning LLMs, NLP, Computer Vision, OCR, and MLOps while helping shape the future of AI-powered multilingual experiences.