Senior AI Engineer

RhythmX AI; Bengaluru; On-site; INR 1,500,000 - 2,000,000; Full time

Job summary

RhythmX AI is looking for a Senior AI Engineer in Bengaluru to lead the development of AI solutions within a healthcare environment. You’ll be responsible for building and deploying advanced AI systems, collaborating with product and engineering teams to ensure impactful applications.

The ideal candidate has at least 6 years of experience in AI, including work in healthcare, with strong skills in machine learning, LLMs, and cloud technologies.

Qualifications

• Minimum 6+ years of experience in AI/ML, with at least 2 years in GenAI.
• Experience in healthcare company, particularly with EHRs.
• Proven development of AI algorithms using healthcare datasets.

Responsibilities

• Fine-tune LLMs and develop ML models for healthcare applications.
• Lead model deployment with cloud-native tools.
• Evaluate speech models for conversational interfaces.

Skills

Python

Machine Learning

Deep Learning frameworks (PyTorch, TensorFlow)

Natural Language Processing (NLP)

Speech-to-Text (STT)

Text-to-Speech (TTS)

Education

Bachelor's or Master's degree in Computer Science or related field

Tools

Azure ML

MLOps

Git

Job description

GW RhythmX is seeking a talented and innovative Senior AI Engineer to lead the development and deployment of advanced AI solutions within a mission-driven healthcare environment. This role is ideal for a seasoned professional with hands‑on experience in machine learning (ML), large language models (LLMs), and generative AI (GenAI), with a strong focus on productionizing scalable and reliable models.

As a Senior AI Engineer, you will drive end‑to‑end AI development—from ideation and training data pipelines to model deployment and continuous improvement—while addressing unique healthcare data challenges. You’ll collaborate across functions including product, engineering, data science, and clinical experts to deliver high‑impact AI applications, including voice assistants and multimodal systems tailored to real‑world care settings.

Responsibilities

• Fine‑tune SLMs / LLMs and develop ML models for healthcare‑specific use cases.
• Build multimodal AI systems that integrate text, structured medical data, and images.
• Optimize models for accuracy, latency, and resource efficiency in production settings.
• Evaluate and integrate speech‑to‑text (STT) and text‑to‑speech (TTS) models into conversational interfaces.
• Customize foundation models using domain adaptation and prompt engineering techniques (e.g., PEFT, LoRA).
• Develop AI algorithms from healthcare data and guide them through a full production lifecycle into deployed solutions.
• Lead model deployment end‑to‑end with cloud‑native tools and infrastructure (Azure ML).
• Implement model performance monitoring, drift detection, and auto‑retraining pipelines.
• Ensure AI solutions are scalable, reliable, and aligned with security and compliance requirements in healthcare environments.

Technical Leadership

• Provide technical guidance to junior AI engineers.
• Conduct design reviews and drive the adoption of best practices in model reproducibility, validation, and explainability.
• Lead the evaluation and integration of cutting‑edge ML research and open‑source frameworks.
• Contribute to architectural decisions aligned with clinical, business, and regulatory goals.
• Process and curate large‑scale, structured and unstructured healthcare datasets.
• Design synthetic data generation strategies where needed to augment training.
• Handle noisy, imbalanced, or incomplete data through robust preprocessing and enrichment.
• Ensure HIPAA and GDPR compliance in data handling, encryption, and access management.
• Leverage EHR and clinical data from the provider side to engineer healthcare data pipelines and training corpora.
• Lead the creation of robust evaluation strategies combining domain‑specific KPIs (e.g., AUC, accuracy) with clinical relevance.
• Proactively identify, measure, and mitigate algorithmic bias, especially in patient‑facing models.
• Conduct adversarial stress testing and ensure models meet safety, fairness, and ethical standards.
• Define model KPIs aligned with measurable impacts on clinical outcomes, patient safety, and workflow efficiency.

Cross‑Functional Collaboration

• Translate stakeholder and product needs into robust, scalable AI solutions.
• Collaborate with clinical experts to vet model behavior and expected impact in patient and caregiver workflows.
• Participate in Agile processes including sprint planning, demos, and technical retrospectives.
• Manage documentation of model architectures, version changes, testing strategies, and key design decisions.

Learning, Innovation & Thought Leadership

• Stay up‑to‑date on the latest LLM advancements, STT/TTS developments, voice interaction technologies, and GenAI frameworks.
• Evaluate new models and methods (e.g., RAG, LangChain, Whisper, Tacotron) for their potential impact and feasibility.
• Advocate for responsible AI and lead initiatives in privacy‑preserving and explainable ML.
• Contribute to a culture of continuous learning, internal knowledge sharing, and open technical dialogue.

Qualifications

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or related technical field.
• Minimum 6+ years of industry experience in AI/ML including at least 2 years with GenAI, NLP/NLU, and LLMs.
• Must have software development experience at a healthcare company, particularly in the provider space (e.g., hospitals, clinical systems) with exposure to EHRs or related healthcare data domains.
• Proven experience developing AI algorithms using healthcare datasets and integrating them into production products or services.
• Experience building voice‑enabled products or assistants is highly advantageous.

Technical Skills

• Expert in Python and deep learning frameworks such as PyTorch or TensorFlow.
• Hands‑on experience with training/fine‑tuning LLMs and modern NLP/NLU techniques.
• Hands‑on expertise with STT (e.g., Whisper) and TTS (e.g. Elevenlabs) models.
• Proficient in MLOps, including model serving, experiment tracking, container orchestration, and CI/CD pipelines.
• Strong understanding of production‑grade solutions using Azure.
• Familiarity with version control (e.g., Git), collaboration tools, and responsible AI practices.
• Familiar with vector databases, retrieval‑augmented generation (RAG), and API deployment.
• Comfortable with healthcare regulatory frameworks (e.g., HIPAA, GDPR) and ethical data use policies.

Professional Attributes

• Curious and self‑motivated, with a passion for impactful healthcare innovation.
• Effective communicator who can tailor technical concepts to non‑technical stakeholders.
• Exceptional problem‑solving and quantitative reasoning abilities.
• Team‑oriented, growth‑minded, and proactive in driving projects forward.
• Highly organized and focused on quality, reproducibility, and compliance.
• Passionate about applying AI to improve outcomes in real‑world healthcare systems.

GW RhythmX is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.