Senior Smart Sensing & Algorithms Engineer – Philips Avent (Smart Parenting)

Help shape the next generation of smart baby care products. At Philips Avent (Smart Parenting), we create meaningful innovations that support parents and babies worldwide. As a Senior Smart Sensing & Algorithms Engineer, you will develop data-driven reassurance features for our Smart Parenting portfolio (e.g., baby video monitors) and adjacent connected propositions.

We’re looking for a hands-on, end-to-end engineer who can bridge consumer needs, sensing/vision, data analytics, and algorithm development. This is not about building a “perfect” algorithm in isolation. It’s about delivering a function that works reliably in the real world, builds trust with parents, and can be scaled into a product.

Your role

You will be part of Philips Avent’s Research & Advanced Development (R&AD) team, driving early-stage innovation with a focus on smart sensing, data pipelines, and algorithm development.

You will:

• Lead front-end exploration projects for reassurance features, from problem framing to validated prototype.
• Translate consumer and technical insights into measurable signals, performance metrics, and system requirements (what to measure, how to measure it, what “good” looks like).
• Build and iterate on data pipelines and algorithm prototypes in Python, and evaluate them pragmatically using the right metrics and trade-offs (reliability, false alarms, edge cases).
• Work closely with cross-functional teams (R&D, UX, marketing, physiology/clinical partners) to ensure features are meaningful, explainable, and deliver real reassurance to parents.
• Collaborate with global stakeholders and suppliers to ensure sensing/vision performance holds up under real-world conditions.
• Communicate progress clearly: structure learnings, propose options/trade-offs, and drive decisions with evidence.

Typical problems you’ll solve

• Turn consumer functions into measurable signals and a robust detection pipeline with clear KPIs.
• Reduce false alarms while preserving sensitivity, and explain trade-offs in a product context.
• Design data collection and labeling strategies that improve performance over time.
• Validate algorithms under real-world variability (lighting, motion, occlusion, noise) and define guardrails for reliable behavior.

Why you’ll love this role

You’ll work on “real life” product intelligence: noisy signals, imperfect data, and real constraints. You’ll have the opportunity to own the end-to-end chain from sensing/data to algorithm to prototype validation, and see your work shape features used by families globally. Success is not the most advanced model on paper, but a feature that is trusted, robust, and ready for productization.

You’re the right fit if

• You have a Master’s or PhD in Engineering or Applied Sciences, such as Mechanical, Mechatronics, Electrical, Biomedical, Applied Physics, Robotics, or Computer Science (or equivalent experience), with a clear end-to-end product/systems track record.
• You bring 5+ years of experience developing data-driven functions in real products or real-world systems (consumer, medical, IoT, automotive, robotics, etc.).
• You are strong in Python and comfortable with data analysis, statistics, and rapid algorithm prototyping (signal processing, ML baselines, evaluation).
• You have experience or strong affinity with computer vision and/or sensing systems, and you understand the chain from sensor → data → algorithm → user function.
• You think end-to-end: you can define what data is needed, how to collect it, how to validate it, and how to make it robust and reliable in practice.
• You are pragmatic and fast-learning, with a bias for testing and iteration rather than endless research.
• You can align stakeholders and present structured, data-driven recommendations to management.
• Experience with international teams/suppliers and exposure to Asian manufacturing ecosystems is a plus.

Important: this is not a role for someone who only trains models on prepared datasets, nor for someone who wants to stay purely in hardware. We need an engineer who can bridge sensing, data, algorithms, and validation and drive learning cycles end-to-end.

Signals of fit

1. You’ve taken a vague user problem and turned it into a measurable system with clear KPIs.
2. You’re comfortable defining what data to collect and building the pipeline yourself (not just training on provided datasets).
3. You start with simple baselines, iterate fast, and can explain trade-offs clearly.
4. You think in failure modes: edge cases, false alarms, robustness, and real-world variability.
5. You can prototype end-to-end (from sensor/vision input to an output that could become a product feature).
6. You communicate crisply and can make decision-ready recommendations, not just analysis.
7. You enjoy improving efficiency (automation, tooling, faster experimentation).

Signals of mismatch

1. You mainly build models on curated datasets and don’t engage with sensing, data collection, or validation strategy.
2. You prefer long research cycles and perfect accuracy over pragmatic product trade-offs and fast iteration.
3. You want a purely software role (or purely mechanical role) without owning the full end-to-end chain.

How we work together

We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week.

About Philips

We are a health technology company.