Senior ML Engineer Offline

Our mission at Geniusee is to help businesses thrive through tech partnership and strengthen the engineering community by sharing knowledge and creating opportunities 🌿Our values are Continuous Growth, Team Synergy, Taking Responsibility, Conscious Openness and Result Driven. We offer a safe, inclusive and productive environment for all team members, and we’re always open to feedback💜 If you want to work from home or work in the city center of Kyiv, great — apply right now.

Requirements.
● 4+ years of hands-on experience in computer vision, with a strong focus on embedded/edge device optimization;
● Deep knowledge of CNN-based object detection and face detection techniques;
● Expertise in model compression, quantization, and acceleration for embedded inference;
● Strong Python and C++ development skills;
● Experience with deployment tools: TensorRT, ONNX Runtime, TFLite, OpenVINO, or CoreML;
● Familiarity with embedded platforms (e.g., NVIDIA Jetson, Qualcomm Snapdragon, Raspberry Pi with Coral Edge TPU);
● Experience in profiling and optimizing models for latency, throughput, and memory efficiency.

What you will do.
● Communication: Lead as part of a scrum team focused on delivering production-ready, optimized computer vision models. Promote clear, respectful, and constructive communication;
● Collaboration: Work closely with machine learning engineers, software developers, and hardware teams to ensure seamless integration of vision models into products;
● Documentation: Maintain high standards for documenting model training processes, optimization techniques, deployment pipelines, and performance benchmarks;
● Continuous improvement: Stay updated on state-of-the-art research in embedded computer vision and edge AI, bringing new ideas and technologies into the development process;
● Planning: Actively participate in sprint planning and provide accurate estimations, particularly for model optimization and deployment tasks.

Model Development and Optimization:
● Design and optimize CNN-based object detection and face detection models;
● Implement advanced model optimization techniques, including pruning, quantization, and knowledge distillation;
● Develop models with a focus on efficient deployment on embedded or edge devices.

 Embedded Deployment:
● Use tools like TensorRT, ONNX Runtime, TFLite, OpenVINO, or CoreML for deployment;
● Work with embedded hardware platforms such as NVIDIA Jetson, Qualcomm Snapdragon,
and Raspberry Pi with Coral Edge TPU.

Performance Profiling:
● Profile models for latency, throughput, and memory efficiency;
● Optimize the inference performance to meet strict resource and timing constraints on target devices.

Development Skills:
● Develop and maintain codebases in Python and C++ to support model integration and deployment pipelines.

What you will get.
● Competitive salary and good compensation package;
● Exciting, challenging and stable startup projects with a modern stack;
● Corporate English course;
● Ability to practice English and communication skills through permanent interaction with clients from all over the world;
● Professional study compensation, online courses and certifications;
● Career development opportunity, semi-annual and annual salary review process;
● Necessary equipment to perform work tasks;
● VIP medical insurance or sports coverage;
● Informal and friendly atmosphere;
● The ability to focus on your work: a lack of bureaucracy and micromanagement;
● Flexible working hours (start your day between 8:00 and 11:30);
● Team buildings, corporate events;
● Paid vacation (18 working days) and sick leaves;
● Cozy offices in 2 cities ( Kyiv & Lviv ) with electricity and Wi-Fi (Generator & Starlink);
● Compensation for coworking (except for employees from Kyiv and Lviv);
● Corporate lunch + soft skills clubs;
●Unlimited work from home from anywhere in the world (remote);
● Geniusee has its own charity fund.