Applied AI Engineer — Healthcare AI

Clinvvo; Bengaluru; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Clinvvo in Bangalore is seeking an experienced AI/ML engineer to join a fast-growing health-tech startup. You will own end-to-end systems for medical AI, from data pipelines to production-grade models, with real-time constraints.

The role emphasizes applied AI, LLMs, fine-tuning, speech-to-text, and NER, with strong focus on reliability and low latency in clinical settings. You will collaborate with clinicians and engineers to ship impactful solutions.

Qualifications

• Bachelor's in Computer Science, Engineering, or related field.
• 3+ years in AI/ML with focus on applied and Generative AI systems.
• Strong hands-on experience with LLMs, prompt engineering, and structured outputs.

Responsibilities

• Real-time clinical document generation with sub-second latency and no hallucinations.
• Fine-tune special-purpose models (LoRA, PEFT, SFT) for high-throughput serving.
• Develop speech-to-text and audio pipelines for clinical use with multi-speaker accents.
• Implement medical NER to extract medications, dosages, diagnoses, and procedures.
• Build evaluation pipelines with golden datasets and clinician-in-the-loop reviews.
• Develop automated booking and scheduling systems for patient interactions.
• Curate clinical datasets and deploy production-grade services at scale.

Skills

Applied AI

LLMs

Prompt engineering

Python

SQL

AWS

MLOps

Production systems

Education

Bachelor's in CS

Tools

HuggingFace

PEFT

LoRA

TRL

Axolotl

Unsloth

Job description

Clinvvo is a fast-growing, profitable Swedish health-tech company built by clinicians and technologists, trusted by 200+ hospitals and clinics across Sweden and Germany, and newly backed by a $1.5M USD seed round from European institutional investors as we expand across Europe and beyond. Joining now means shaping the product, the technical roadmap, and the future of the company as we scale.

The Role

Work at the forefront of medical AI — not by wiring together off-the-shelf services, but by owning the systems and the models behind them. Clinical work is messy, spoken, time-critical, and unforgiving of errors, which makes it one of the most interesting applied AI problem spaces there is.

The headline opportunity: pushing the frontier on special-purpose models of our own — fine-tuning experience is not required; we want strong applied AI engineers with solid fundamentals and the motivation to grow into this, and we'll support you in doing so.

What you'll do

• Real-time clinical document generation — turn a live consultation into a structured, clinically accurate document while the clinician is still in the room. Sub-second latency, zero tolerance for hallucination.


• Fine-tuning special-purpose models — LoRA, PEFT, SFT and preference alignment, optimized for high-throughput serving. Dataset design through to production. This is where we invest in going deep.


• Speech-to-text and audio pipelines — real clinical audio: multiple speakers, accents, noise, and Swedish and German medical vocabulary no off-the-shelf model has seen.


• Medical NER and structured extraction — medications, dosages, diagnoses, procedures and temporal relationships pulled out of free text, reliable enough to write into a patient record.


• Evaluation pipelines — in healthcare, "it looks good" is not a metric. Golden datasets, automated judges, clinician-in-the-loop review, and the monitoring that catches regressions before a clinic does.


• Automated booking and scheduling — agentic systems that handle real patient interactions end to end, with real-world consequences when they go wrong.


• Data and deployment — curate clinical datasets to a training-ready standard, and take systems from experiment to monitored, production-grade services clinicians rely on at scale.

You won't do all of this at once, but over time you'll touch most of it.

What we're looking for

• Bachelor's in Computer Science, Engineering, or a related field.


• 3+ years in AI/ML, with a focus on applied and Generative AI systems.


• Strong hands-on experience with LLMs, prompt engineering, and structured outputs.


• Hands-on with speech-to-text and audio-processing pipelines.


• Proficient in Python (pandas, NumPy, ML/AI libraries) and SQL.


• Familiar with cloud AI services, preferably AWS (S3, SageMaker, Bedrock).


• Understanding of LLMOps / MLOps: evaluation, monitoring, deployment, and iteration.


• Proven experience shipping production-grade AI systems at scale.


• Strong ownership, clear communication, and independence in a fast-paced environment.

Good to have

• Parameter-efficient fine-tuning (LoRA, PEFT, SFT) and tools such as Hugging Face Transformers, PEFT, TRL, Axolotl, or Unsloth.


• RLHF, DPO, or other preference-alignment methods.


• Information extraction / NER, and experience with clinical or biomedical ontologies.


• End-to-end GenAI workflows (LangChain, LlamaIndex, RAG), embeddings, vector databases, and retrieval.


• Agentic systems, tool use, and function calling in production.


• Real-time / streaming inference and low-latency serving.


• Healthcare, clinical, or other regulated-data experience.

Why this role

• Frontier work with real impact — models and systems deployed in real clinical settings, used every day.


• Breadth and depth — hard problems across speech, generation, extraction, evaluation and agents, with room to go deep on fine-tuning special-purpose models.


• End-to-end ownership — from data and experimentation through deployment and continuous improvement.


• A profitable, funded company (a fresh $1.5M seed) and a meaningful mission.

This is a full-time, in-office role at our Bangalore office in HSR Layout.