We're a leading partner in social commerce, collaborating with major athletic wear, footwear, and electronics brands to expand their influencer-driven sales channels. Having achieved significant revenue milestones, we're rapidly expanding our technical team. Our mission is to create the ultimate platform connecting content creators with brands across major e-commerce ecosystems including video shopping platforms, social media marketplaces, and online retail channels.

We're developing critical infrastructure for the digital creator landscape and integrating artificial intelligence with enterprise-level brands and influencers. Your contributions will have immediate user impact—our customer base relies on our platform for their daily operations.

Responsibilities

Architect and maintain machine learning systems across the full lifecycle: research, prototyping, training, deployment, and continuous improvement

Develop multimodal ML solutions processing video content, textual data, imagery, and audio at enterprise scale

Engineer and implement large language model applications utilizing retrieval-augmented generation and AI service integrations

Create content analysis and categorization models for written and visual media

Build discovery and search capabilities using vector embeddings and semantic matching

Develop audio processing and analysis workflows

Establish ML operations infrastructure including data engineering pipelines, model deployment services, performance monitoring, and experimentation frameworks

Collaborate on ML/AI product innovation with product teams and clients

Utilize cutting-edge AI tooling to enhance development velocity

Partner directly with clients to transform ambiguous needs into production ML solutions

Deliver rapidly in a fast-paced, high-priority environment

Qualifications

Ideal Candidate Profile

4–8 years building and deploying production machine learning systems

Strong Python expertise with solid ML fundamentals and production-quality code practices

End-to-end ML model development experience: data engineering, training, deployment, monitoring

Proficiency with contemporary ML frameworks (PyTorch, TensorFlow, scikit-learn)

Production experience with large language models and AI service APIs (OpenAI, Anthropic, Hugging Face)

Cross-domain ML capabilities spanning natural language processing, computer vision, and audio

Product-oriented mindset identifying ML opportunities that enhance user experience and business outcomes

Familiarity with MLOps tooling and cloud infrastructure (AWS or GCP)

Self-directed and effective in ambiguous situations

Technical Expertise We're Seeking

Core Capabilities:

Supervised/unsupervised learning, feature engineering, model evaluation, A/B testing

Neural architectures, transformers, convolutional networks, training optimization

RAG implementations, prompt engineering, vector databases, model fine-tuning, LangChain

Image classification, object detection, OCR, visual content analysis, image embeddings

Audio classification, automatic speech recognition, audio transcription

Semantic search, embedding models, vector similarity, multimodal retrieval

Model deployment, monitoring, experiment tracking (MLflow, Weights & Biases), data pipelines

Cloud ML services: AWS (SageMaker, Bedrock) or GCP (Vertex AI), scalable inference

Why is This a Great Opportunity

Revenue-generating company addressing genuine market needs

Define ML strategy and infrastructure during growth phase

High autonomy with meaningful work, no trivial tasks

Rapid deployment cycle, models reach production in days

Engineering-first culture

Influence both product and company direction

Tackle varied ML challenges across video, language, and audio domains

Direct input on product strategy, your ML concepts become shipped features

Comments

This is an urgent role

Responsive client 

Open to H1B Visa transfer 

No OPT candidates