Job description
We're looking for a curious and motivated engineer to join our AI team.
You'll help design, build, and ship intelligent systems — from LLM-powered features to ML pipelines — while learning from senior engineers in a fast-moving environment.
Responsibilities: Build and integrate AI/ML features into production applications using large language models and other ML techniques.
Design and maintain data pipelines for training, fine-tuning, and evaluating machine learning models.
Collaborate with product and design teams to translate requirements into AI-powered features.
Write clean, well-tested Python code and contribute to shared ML libraries and tooling.
Monitor and evaluate model performance in production; iterate on prompts, parameters, and architectures.
Document experiments, findings, and system designs clearly for the team Requirements: Bachelor's degree in Computer Science, Engineering, Math, or a related field (or equivalent practical experience).
Proficiency in Python and familiarity with ML libraries such as PyTorch, TensorFlow, or scikit-learn.
Basic understanding of machine learning concepts: supervised learning, embeddings, transformers.
Experience working with APIs, REST services, and cloud platforms (AWS, GCP, or Azure).
Strong communication skills and a growth mindset.
Nice to Have: Hands-on experience with LLM APIs (OpenAI, Anthropic, Cohere) or open-source models (LLaMA, Mistral).
Familiarity with RAG architectures, vector databases (Pinecone, Weaviate, Chroma).
Knowledge of MLOps tools: MLflow, Weights & Biases, or similar.
Contributions to open-source AI/ML projects or personal AI side projects.
Experience with prompt engineering and fine-tuning workflows
This job post has been translated by AI and may contain minor differences or errors.
