Senior Machine Learning Engineer

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.

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

3 to 8 years of expereince, pytorch, tensorflow, aws, langchain, 4-8 years building and deploying production machine learning systems

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

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

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

Neural architectures, transformers, convolutional networks, training optimization

Audio classification, automatic speech recognition, audio transcription

Semantic search, embedding models, vector similarity, multimodal retrieval

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