Staff Engineer, Software

Stryker; Gurugram District; On-site; INR 3,500,000 - 6,000,000; Full time

Job summary

Stryker is seeking an experienced engineer who combines AI/ML for computer vision with native Android development. You will train and fine-tune vision models for live camera feeds, while shipping a production Android app that connects to our cloud.

Collaboration with deployment and maintenance teams ensures models run within scaling and runtime constraints. The role requires 5+ years in software engineering, strong Python and ML framework skills, and proven Android app delivery.

Qualifications

• Experience in vision-based model training and production deployment.
• Strong Python and ML framework proficiency (PyTorch/TensorFlow).
• Hands-on experience with cloud AI training infrastructure.
• Production Android app shipping and cloud integration capability.
• Ability to work with MLOps and deployment teams.

Responsibilities

• Design, train, evaluate, and tune CV models for live video.
• Optimize models to meet deployment constraints and scale.
• Maintain and upgrade models in production with data drift handling.
• Build native Android app (Kotlin) communicating with cloud backend.
• Establish Android CI, testing, crash reporting, and Play Store pipelines.

Skills

AI/ML (CV)

Python

Kotlin

Android dev

PyTorch/TensorFlow

MLOps

REST/gRPC

Cloud AI infra

CNNs & detectors

Education

BS/MS CS/AI

Tools

AWS SageMaker

GCP Vertex AI

Azure ML

ONNX

Android Studio

Job description

Job Description

We are seeking an experienced engineer who brings two distinct skill sets: AI/ML (Computer Vision) – owning the training, testing, and tuning of vision‑based models for live camera‑feed monitoring; and Native Android Development – developing and shipping a production Android app that talks to our cloud. You will partner with the deployment team to align models with their scaling/runtime constraints and work with the maintenance team to maintain and upgrade models.

Key Responsibilities

• Design, train, evaluate, and tune computer vision models (detection, classification, segmentation, tracking) for live video and multi‑camera use cases, including dataset curation, training/validation/testing pipelines, and rigorous benchmarking on accuracy, latency, and throughput.
• Optimize models (architecture, quantization, pruning, distillation) to meet deployment and scaling constraints provided by the deployment team; re‑tune or re‑architect when those constraints change.
• Partner with the operations team to maintain and upgrade models in production – triage regressions, refresh on new data, address drift, and ship improved versions.
• Design, build, and ship a native Android application (Kotlin, Jetpack Compose, MVVM/Clean Architecture, Hilt, Coroutines/Flow, Room, WorkManager) that interacts with our cloud backend.
• Build secure cloud integration: REST/gRPC, OAuth2/JWT, TLS, FCM push, and offline‑first sync; handle Android runtime permissions and background execution correctly.
• Set up Android CI, testing (unit + instrumentation), crash reporting, and Play Store release pipelines.

Required Qualifications

• 5+ years of total professional software engineering experience.
• Proven experience in vision‑based model training and testing, with models shipped to production.
• Hands‑on experience with cloud‑based AI training/experimentation infrastructure (AWS SageMaker, GCP Vertex AI, Azure ML, or equivalent).
• Experience building models for continuous monitoring via live video input from cameras and tuning them for efficient inference across multiple concurrent camera streams.
• Track record of collaborating with deployment/MLOps/operations teams – translating runtime constraints into model decisions and supporting models post‑launch.
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow, TensorFlow Lite, ONNX); strong grasp of CNNs and modern detection/tracking architectures (YOLO, DETR, ByteTrack, etc.).
• Strong proficiency in Kotlin and the modern Android stack (Jetpack, Compose, Coroutines/Flow, Hilt, Room, WorkManager); demonstrated experience shipping production Android apps to the Play Store.
• Deep working knowledge of Android Wi‑Fi and BLE APIs.
• Experience with cloud connectivity on Android (REST, gRPC, WebSockets, or MQTT; OAuth2/JWT; TLS; FCM) and Android’s security/permissions model (runtime permissions, foreground services, background execution limits).
• Comfort interfacing with embedded/IoT hardware over BLE and Wi‑Fi under real‑world conditions (intermittent connectivity, retries, power constraints).

Preferred Qualifications

• On‑device inference acceleration (Android NNAPI, Qualcomm SNPE, MediaPipe, GPU delegates).
• Streaming protocols (RTSP, WebRTC, HLS) and video codecs; edge / IoT camera deployments.
• Model monitoring, drift detection, and active learning loops.
• Contributions to open‑source ML or Android projects.

Education

• Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field — or equivalent practical experience.

Measurement Bias

• Strong product mindset and bias for measurement – you instrument, benchmark, and optimize.
• Excellent collaboration skills with deployment and operations teams, and a maintenance mindset toward models in production.
• Ability to switch effectively between two distinct domains (ML model development and Android app development) and deliver in both.