Senior Multimodal ML Engineer - LLMs & Production

WLEN WorldJobs LLP; San Francisco (CA); Hybrid; USD 180,000 - 230,000; Full time

Job summary

WLEN WorldJobs LLP in San Francisco is seeking an experienced ML Engineer to develop multimodal AI solutions at enterprise scale.

You will collaborate with product teams to deploy LLM-powered applications, integrate AI services, and build robust MLOps pipelines across video, text, image, and audio data.

The ideal candidate has 4–8 years of production experience, strong Python, and fluency with PyTorch/TensorFlow, AWS, and LangChain.

Qualifications

• 4–8 years of production ML experience.
• Strong Python and production-quality code practices.
• Proficiency with PyTorch, TensorFlow, scikit-learn.
• Experience with LLMs and AI service APIs (OpenAI, Anthropic, Hugging Face).
• Cross-domain ML across NLP, CV, and audio.
• Cloud infra familiarity (AWS or GCP).

Responsibilities

• Develop multimodal ML solutions processing video, text, imagery and audio at scale.
• Engineer and implement LLM applications using retrieval-augmented generation.
• Create content analysis and categorization models for media.
• Build discovery and search using vector embeddings and semantic matching.
• Develop audio processing and analysis workflows.
• Establish ML ops infrastructure including data pipelines and deployment services.
• Collaborate with product teams and clients on ML product innovation.
• Utilize cutting-edge AI tooling to accelerate development.
• Partner with clients to translate ambiguous needs into production ML solutions.
• Deliver rapidly in a fast-paced, high-priority environment.

Skills

PyTorch

TensorFlow

AWS

LangChain

Job description

WLEN WorldJobs LLP in San Francisco is seeking an experienced ML Engineer to develop multimodal AI solutions at enterprise scale.

You will collaborate with product teams to deploy LLM-powered applications, integrate AI services, and build robust MLOps pipelines across video, text, image, and audio data.

The ideal candidate has 4–8 years of production experience, strong Python, and fluency with PyTorch/TensorFlow, AWS, and LangChain.