Senior Machine Learning Engineer
San Francisco, California, USA
170000-225000
Job Description
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 systemsStrong Python expertise with solid ML fundamentals and production-quality code practicesEnd-to-end ML model development experience : data engineering, training, deployment, monitoringProficiency 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 audioProduct-oriented mindset identifying ML opportunities that enhance user experience and business outcomesFamiliarity with MLOps tooling and cloud infrastructure (AWS or GCP)Self-directed and effective in ambiguous situationsTechnical Expertise We're Seeking
Supervised / unsupervised learning, feature engineering, model evaluation, A / B testingNeural architectures, transformers, convolutional networks, training optimizationRAG implementations, prompt engineering, vector databases, model fine-tuning, LangChainImage classification, object detection, OCR, visual content analysis, image embeddingsAudio classification, automatic speech recognition, audio transcriptionSemantic search, embedding models, vector similarity, multimodal retrievalModel deployment, monitoring, experiment tracking (MLflow, Weights & Biases), data pipelinesCloud ML services : AWS (SageMaker, Bedrock) or GCP (Vertex AI), scalable inferenceWhy is This a Great Opportunity
Revenue-generating company addressing genuine market needsDefine ML strategy and infrastructure during growth phaseHigh autonomy with meaningful work, no trivial tasksRapid deployment cycle, models reach production in daysEngineering-first cultureInfluence both product and company directionTackle varied ML challenges across video, language, and audio domainsDirect input on product strategy, your ML concepts become shipped features#J-18808-Ljbffr