AIML Engineer
Join our AI-first team shaping next-gen intelligent systems. Work on cutting-edge models, agentic workflows, and real-world ML deployments.
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Role Summary
We are looking for a driven and detail-oriented AI/ML Engineer to join our growing applied AI team. In this role, you will design, build, and ship intelligent systems that directly impact our product and millions of users. You will work across the full ML lifecycle — from data ingestion and experimentation to model deployment and monitoring — collaborating closely with product managers, platform engineers, and data scientists to bring AI-powered capabilities to production at scale.
About the Team
Our AI Platform team builds the intelligence layer that powers every product decision — from personalized recommendations and real-time fraud signals to generative AI features used by millions daily. We operate with a startup mindset inside a scaled organisation: fast cycles, high ownership, and a direct path from research prototype to production impact. You'll be embedded alongside senior engineers and researchers, with mentorship, access to compute, and a genuine culture of learning.
Required Skills & Qualifications
- Python proficiency Must Have — production-quality code, OOP, async programming, and familiarity with testing frameworks (pytest).
- Machine learning fundamentals Must Have — solid grasp of supervised/unsupervised learning, model evaluation, bias-variance tradeoff, and regularisation.
- LLM & NLP experience Must Have — hands-on work with transformer architectures, prompt engineering, fine-tuning (LoRA / QLoRA), and tokenisation.
- RAG pipeline development Must Have — experience building retrieval-augmented systems with vector databases (Pinecone, Weaviate, or pgvector).
- LLM frameworks Must Have — practical knowledge of LangChain, LlamaIndex, or equivalent orchestration tools.
- Cloud & MLOps basics Must Have — experience with at least one major cloud (AWS / GCP / Azure), containerisation (Docker), and CI/CD for ML workflows.
- Version control & collaboration Must Have — Git, code review culture, and documentation practices.
Preferred Qualifications
- B.Tech / B.S. / M.S. in Computer Science, Data Science, Mathematics, or a related field — or equivalent industry experience. Nice to Have
- Experience with PyTorch or TensorFlow for custom model training and fine-tuning on domain datasets. Nice to Have
- Familiarity with Hugging Face ecosystem — Transformers, PEFT, Datasets, Evaluate libraries. Nice to Have
- Exposure to multi-modal models (vision-language, speech, or document understanding). Nice to Have
- Knowledge of model serving frameworks — TorchServe, BentoML, vLLM, or Triton Inference Server. Nice to Have
- Published work, open-source contributions, Kaggle Top placements, or demonstrable personal AI projects on GitHub. Nice to Have
- Understanding of data privacy, responsible AI principles, and model interpretability (SHAP, LIME). Nice to Have
What We Offer
- Competitive salary benchmarked against top-quartile market data, reviewed bi-annually.
- Performance bonus (up to 20% of base) tied to individual and team milestones.
- Equity participation through stock options vesting over a 4-year schedule.
- Health, dental, and vision insurance fully covered for employee + dependants.
- $3,000 annual learning & development budget — conferences, courses, certifications.
- Access to premium compute (A100 / H100 clusters) for research and experimentation.
- Flexible working hours with a core collaboration window; 25 days annual leave.