Lead the design, development, and deployment of ML/AI/GenAI models that power core Foodics products. Collaborate with Data Engineers, Product Managers, and Platform teams to deliver production-grade models with real impact.
Requirements
- 5+ years' experience in applied ML, AI, or data science.
- Strong proficiency in Python and ML/AI libraries (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, HuggingFace Transformers).
- Experience with MLOps tools (e.g., MLflow, SageMaker) and managing versioning, testing, and observability.
- Deep understanding of model development workflows including feature engineering, hyperparameter tuning, model evaluation, and A/B testing.
- Deep understanding of statistical modeling, statistical inference, and the appropriate application of statistical tests (e.g., t-test, chi-square, ANOVA, regression analysis); ability to interpret results and communicate implications to both technical and non-technical audiences.
- Proven track record of deploying ML models in production at scale.
- Knowledge of ML best practices including bias mitigation, explainability (e.g., SHAP, LIME), and model monitoring for drift and fairness.
- Strong understanding of data pipelines, experimentation, and model evaluation.
- Familiarity working in a cloud-native environment (AWS preferred) with CI/CD, GitOps, and IaC tools (e.g., Terraform, CDK).
- Hands-on experience with GenAI / LLM integration (e.g., RAG, fine-tuning, embeddings, prompt engineering) and tools such as LangChain, LangGraph, or LlamaIndex.
Benefits
- Highly competitive compensation packages, including bonuses and the potential for shares.
- Prioritized personal development and regular training.
- Annual learning stipend to tackle new challenges and grow your career in a hyper-growth environment.
- Autonomy, mentoring, and challenging goals that create incredible opportunities for both you and the company.