Browse Jobs
Explore open roles across India.Explore active software roles. Sign up to apply and get AI match scores.
Top MatchesTop Job Matches
Loading jobs…
Back to Browse Jobs
Philips
Data & AI Engineer
Philips
Bengaluru•Remote•3-6 Yrs•1 day ago
Job description
RemoteAIMachine LearningHealthcare
Overview
Data & AI Engineer role focused on building AI solutions for MRI systems to minimize downtime.
Responsibilities
- Design, develop, and deploy production-grade Data and AI solutions across the MR service AI portfolio — including predictive failure and remote-resolution models, AI-driven parts recommendation, root-cause analytics for rework reduction, and GenAI applications for contract and entitlement analytics.
- Build and maintain robust data pipelines and data models over service datasets (ITSM cases, remote diagnostics/machine logs, parts and contract data), ensuring reliable, secure, high-quality inputs for AI applications.
- Develop, integrate, and operationalise ML models, LLMs, Retrieval-Augmented Generation (RAG) pipelines, and agentic AI workflows into service tools used by field service engineers and remote service engineers worldwide.
- Take POCs to MVP & productization: harden prototypes (including those built with external AI partners) into validated, monitored, supportable enterprise solutions.
- Implement AI engineering best practices — MLOps/LLMOps, CI/CD, automated testing, monitoring, model versioning, and governance — appropriate to a regulated healthcare environment.
- Develop APIs, microservices, and cloud-native AI services for scalable deployment across enterprise and service platforms.
- Monitor model performance in the field; retrain and continuously optimise for accuracy, latency, cost, and reliability against measurable service outcomes (system uptime, time-to-resolution, first-time-right).
- Embed Responsible AI by design: data privacy, security, explainability, auditability, and compliance requirements consistent with MedTech and Philips AI governance standards.
- Collaborate closely with Data Scientists, System Architects, Service Information Architects, Product Owners, and external delivery partners to translate service business problems into engineered solutions.
- Evaluate emerging AI technologies and frameworks; contribute to code reviews, documentation, knowledge sharing, and the engineering standards of a growing team.
- Mission with a heartbeat: your models directly reduce MRI downtime — that means faster diagnosis for patients, not just dashboards.
- Full lifecycle exposure: upstream commercial analytics (contracts, entitlements, pricing) and downstream operational AI (prediction, resolution, parts) in one portfolio.
- Real data, real scale: validated service case data across a global installed base — you build on evidence, not toy datasets.
- Builder's seat: a newly carved-out team where engineering standards, tooling choices, and ways of working are still being shaped — by you.
- Bachelor's Degree: 3-6 years of experience in Data Engineering, AI Engineering, Machine Learning Engineering, Software Engineering, or related fields.
- OR Vocational/Equivalent Qualification: Minimum 4 years of relevant experience in Data Engineering, AI Engineering, Analytics, Machine Learning, or Software Development.
- Minimum Education
- Bachelor's or Master's Degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, Software Engineering, Statistics, Mathematics, or a related discipline.
- Minimum Experience
Qualifications
- Exposure to healthcare, MedTech, or other regulated industries; familiarity with medical device service operations, IoT/remote diagnostics data, or field service workflows is a strong plus.
- Knowledge of Responsible AI, AI governance, cybersecurity, and data privacy practices (e.g., GDPR, healthcare data handling).
- Comfort working in a globally distributed, remote-first team across time zones (India, Europe, North America).
- Strong problem-solving skills with excellent collaboration and communication abilities — able to work directly with service domain experts and translate their knowledge into AI solutions.
- Programming: Python (preferred), SQL
- Data Engineering: ETL/ELT, data pipelines, data modelling for structured and unstructured service data (logs, case notes, documents)
- Machine Learning: Scikit-learn, TensorFlow or PyTorch; experience with time-series, classification, and NLP on operational data is a plus
- Generative AI: LLMs, prompt engineering, RAG, vector databases, agentic AI frameworks; experience with managed GenAI platforms such as Azure OpenAI Service or Amazon Bedrock
- Cloud Platforms: Azure (preferred), AWS or GCP
- MLOps/LLMOps: MLflow, Docker, Kubernetes, GitHub Actions/Azure DevOps, CI/CD
- Databases: SQL, NoSQL, vector databases
- API Development: REST APIs, FastAPI or similar frameworks
- Version Control: Git
- Onsite roles require full-time presence in the company’s facilities.
- Field roles are most effectively done outside of the company’s main facilities, generally at the customers’ or suppliers’ locations.
- This role is an office-based role.
- Learn more about our business.
- Discover our rich and exciting history.
- Learn more about our purpose.
Nice to have
- Experience with Azure AI Services.
- Healthcare industry experience.
Education
- Bachelor's or Master's Degree in Computer Science, AI, Data Science, etc.