ML Engineer - Video Understanding & Segmentation

Maxinsights; Santa Clara (CA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Health insurance

Vision care

Dental coverage

401(k)

Paid holidays

PTO (Paid Time Off)

Sick leave

Job summary

Maxinsights is seeking a Machine Learning Engineer to advance video understanding and segmentation at scale. You will prototype embedding pipelines, build LLM-based indexing, and architect end-to-end workflows that translate raw video into structured, searchable data.

The role requires hands-on experience in computer vision, multi-modal learning, and large-scale systems, with a focus on embedding models, vector search, and orchestration frameworks.

Qualifications

• MS or PhD in Computer Science, Electrical Engineering, or related field, or equivalent practical experience.
• 3+ years of hands-on experience in computer vision or multi-modal machine learning.
• Strong proficiency in Python and PyTorch, with solid software engineering fundamentals.
• Hands-on experience with CLIP or similar vision-language/video embedding models for retrieval or representation learning.
• Experience building or fine-tuning LLM-based systems for video/image understanding (captioning, QA, summarization).
• Familiarity with agentic system design — tool use, multi-step reasoning, and orchestration frameworks.

Responsibilities

• Build and optimize video/image embedding pipelines using CLIP-style and other vision-language embedding models for large-scale search/retrieval.
• Develop LLM-based video understanding systems for indexing, summarization, and QA over long-form video.
• Design and implement video chunking/segmentation algorithms to create temporally-aligned clips.
• Build automated captioning systems combining vision-language models and LLMs for fine-grained descriptions.
• Architect agentic systems and pipelines chaining embedding, captioning, retrieval, and reasoning steps.
• Scale video search infrastructure (vector indexing, retrieval, ranking) for millions of clips.
• Collaborate with annotation and data teams to integrate outputs into training pipelines for embodied AI.
• Evaluate and benchmark models and frameworks; track frontier research for platform improvements.

Skills

Python

PyTorch

Multi-modal ML

Computer Vision

Embedding models

Software engineering

Vector search

Model orchestration

Education

MS or PhD in CS/EE or related

Tools

CLIP-style embeddings

FAISS

Milvus

LangChain / LlamaIndex

Job description

Maxinsights is seeking a Machine Learning Engineer to advance video understanding and segmentation at scale. You will prototype embedding pipelines, build LLM-based indexing, and architect end-to-end workflows that translate raw video into structured, searchable data.

The role requires hands-on experience in computer vision, multi-modal learning, and large-scale systems, with a focus on embedding models, vector search, and orchestration frameworks.