Engineering · AI / ML
AI / ML Lead
You run the AI / ML function: the models we fine-tune, the retrieval pipelines behind them, the evaluation harness that says whether a change helped, and the cost and latency of everything we serve.
Experience
5–8 years
Location
Bengaluru
Level
Experienced
About the Role
MiFiX.ai is our AI platform for financial institutions — a set of engines and agents that read documents, answer questions over bank data, run rule-driven decisioning and hold a conversation with an end customer. It is in production with real banks. This role owns the model side of it.
You run the AI / ML function: the models we fine-tune, the retrieval pipelines behind them, the evaluation harness that says whether a change helped, and the cost and latency of everything we serve. You have one AI / ML Engineer and a fellowship bench of ten fellows to bring up — a large part of this job is turning that bench into people who ship.
You report to the Head of Engineering and sit alongside the platform, security and DevOps functions. This is a hands-on leadership role: you are expected to be in the code and in the eval numbers, not only in the review.
Key Responsibilities
Models & Retrieval
Own the model roadmap
Decide what is fine-tuned, what is prompted, what is bought and what is not worth doing at all — and be able to defend each call on cost, latency and measured accuracy.
Fine-tuning in production
LoRA / QLoRA adapters on open-weight models, dataset curation, versioned checkpoints, rollback on regression.
Production RAG
Chunking, embedding, reranking and grounding on real client corpora — including the unglamorous part, which is when the corpus is bad.
Agents and tool use
Multi-step agents with guardrails, retries and hard bounds on what a model is permitted to do against client data.
Evaluation & Governance
Build the evaluation harness
Labelled sets per capability, regression gates in CI, and a number we can quote to a bank. No release goes out on a demo and a feeling.
Own hallucination and safety controls
Output filtering, citation enforcement, refusal behaviour, prompt-injection resistance on anything touching client documents.
ISO 42001 model governance
Model cards, data lineage, change records and the evidence an auditor will ask for. Work with Information Security on the control set.
Cost and latency discipline
Token budgets per workflow, caching, quantisation and batching. Know what each production call costs and what it should cost.
Team
Lead the AI bench
Ten AI fellows and one AI / ML Engineer. Set the work, review it properly, and be honest early about who is converting and who is not.
Mentoring structure, not ad-hoc help
A defined ramp per fellow, a real project each, and a written assessment at the mid-point — the fellowship is six months and drift is expensive.
Represent AI to clients
Explain to a bank's technology and risk teams what the model does, where it is uncertain and what the controls are. In plain language.
What You Bring
- 5–8 years in machine learning, with at least 2 years on systems that served live traffic — not research-only.
- Strong Python and PyTorch. You have run a fine-tune end to end and can explain which metric moved and why.
- Production RAG built by you: chunking strategy, embedding choice, reranking, and the evaluation that proved it worked.
- An evaluation harness you designed — labelled data, regression gates, a number you were willing to be held to.
- Demonstrated control of inference cost and latency, with before-and-after figures.
- Experience mentoring early-career engineers, and the willingness to give direct feedback.
- BE / BTech / MS in Computer Science, Mathematics, Statistics or a related quantitative field.
What Would Be Great to Have
- OCR and document-extraction pipelines on poor-quality scans.
- Speech — ASR, diarisation or TTS in production.
- ISO 42001, NIST AI RMF or equivalent model-governance exposure.
- On-premise or air-gapped model deployment for a regulated client.
- Financial-services domain: lending, collections, trade finance or onboarding.
- Open-source contribution, publication or a public model/dataset release.
Why Join Us
MiFiX.ai is already in production with banks — you are not building a demo. The AI function is yours to define, with a ten-person fellowship bench and a direct line to the Head of Engineering. Decisions here reach real customers within a release cycle.
Sound like you?
Send your CV to careers@newstreettech.com. The subject line is filled in with the role code (NS-AIL-001) for you.
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