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Tech Stack
About the role
- Research, prototype, and productionize LLM solutions for tasks such as product classification, enrichment, and workflow automation.
- Fine-tune and optimize foundation models for domain-specific performance.
- Build scalable inference pipelines and APIs to deliver AI features in production.
- Partner with backend, data, and product teams to define requirements and deliver impactful AI solutions.
- Benchmark model performance and optimize across accuracy, latency, and cost.
- Stay current on advances in LLMs, multimodal models, and tooling, bringing relevant improvements into production.
- (L4) Take technical ownership of major AI features, mentor junior engineers, and influence architecture and design decisions.
Requirements
- L3: 3–5 years of software engineering or applied ML experience, with direct exposure to LLMs.
- L4: 5–8 years of engineering experience, with a proven track record of building and deploying LLM systems in production.
- Experience in agentic systems is a major plus.
- Strong coding skills in Python and familiarity with ML frameworks (PyTorch, TensorFlow).
- Hands-on experience with fine-tuning, prompting, or integrating LLMs (OpenAI, Anthropic, Hugging Face, Qwen, etc.).
- Knowledge of data pipelines, embeddings, vector databases (e.g., Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG).
- Experience deploying ML models as APIs or services in a cloud environment (AWS preferred).
- Bonus: familiarity with multimodal models, RLHF, or evaluation frameworks for generative AI.
Benefits
- A chance to build AI-native tools that change how commerce works globally.
- Diverse, international team of engineers, product managers, and AI specialists.
- Competitive compensation and career growth, with opportunities to level up into leadership.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
LLM solutionsfine-tuningoptimizing foundation modelsscalable inference pipelinesAPIsbenchmarking model performancePythonML frameworksdata pipelinesretrieval-augmented generation
Soft skills
technical ownershipmentoringinfluencing architecturecollaboration