Applied AI ML Lead- AI Research Engineer

hackajob

Bengaluru NM Years Exp Posted 8d ago

Leads applied research into open-source LLM evaluation and deployment for cost, sovereignty, and data-residency optionality
Runs fine-tuning work for tone, lexicon, and domain-specific tasks that are currently brittle in prompts
Investigates inference efficiency and tokenomics: cost-per-output, model routing, and optimisation of production inference
Prototypes voice and image/multimodal capabilities (speech-to-text, text-to-speech, voice agents, document and image understanding) to underwrite future user-facing experiences
Designs rigorous evaluation methodologies and benchmarks so research findings are measurable and reproducible
Partners with AI and platform engineers to productionise research outputs, each tied to a real platform or product need
Publishes internal findings and raises the team's collective capability through knowledge-sharing; acts as a recruiting and thought-leadership magnet

Formal training or certification on artificial intelligence and machine learning concepts and 5+ years applied experience
Advanced proficiency in Python and the modern ML/DL stack (e.g., PyTorch, Hugging Face)
Hands-on experience evaluating, fine-tuning, and deploying Large Language Models
Strong grounding in experimental design, evaluation, and benchmarking of ML systems
Ability to bridge research and engineering: prototypes that become production-ready capabilities
Awareness of inference cost, performance, and optimisation techniques
Strong communication skills, including translating research into business and engineering terms
Published in a top-tier AIML venue (e.g. NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR), or equivalent open-source / applied-research contributions in LLMs, fine-tuning, or efficient inference
MSc or PhD in Machine Learning, Computer Science, or a related quantitative field, or equivalent applied experience