What are the responsibilities of a Senior Machine Learning Engineer?

In this role, you will get to:

• Collaborate with cross-functional teams to understand business requirements and design ML solutions to meet those needs

• Implement, and maintain machine learning models for edge devices such as cameras, drones, or IoT sensors.

• Develop and maintain scalable infrastructure for model training and deployment on either edge devices or cloud based solutions

• Conduct experiments and analysis to evaluate model performance and identify areas for improvement in edge computing and object tracking applications.

• Gather customer requirements during pre-sales interactions, determining project scope, creating technical diagrams, and making estimations for man-days and cloud costs

• Develop and maintain technical documentation

• Participate in recruitment in order to evaluate and interview candidates, as well as improving our recruitment processes

• Share your expertise across the team and mentor the junior/mid-level via code reviews, 1:1, workshops or knowledge sharing sessions, to enhance their technical skills and understanding of best practices

Requirements for this role are:

• 5+ years of experience in developing and deploying machine learning models for edge devices and/or cloud based solutions in a production environment

• Strong programming skills in Python, C++, or other programming languages commonly used for machine learning and computer vision applications

• Proficiency in computer vision algorithms for object detection, recognition, and tracking

• Experience with hardware and software integration of camera systems and edge devices, including knowledge of image sensors, optics, and processing units

• Ability to optimize and deploy models for real-time processing and low-latency applications on edge devices

• Experience using Docker for containerization and deployment of applications in a production environment

• Excellent problem-solving skills and the ability to work well in a fast-paced, collaborative environment

• Ability to scope projects, define architectures, and choose technologies based on project requirements

• Leadership skills and ability to mentor junior and mid-level Machine Learning Engineers

• Experience with a deep learning framework (e.g. TF, Pytorch, MXNet, CAFFE, ONNX)

It’s nice if you have experience with:

• Experience working with IoT and edge devices (e.g. Android, Nvidia Jetson)

• Experience with deep learning compilers (e.g TVM, XLA, Glow)

• Experience with deep learning accelerators (e.g. TPU, NPU, DLA)

• Experience with deep learning optimization frameworks (e.g. TRT, TFLITE, MACE)

• Experience with CI/CD, Cloud Platforms (e.g. GCP, AWS, Azure)

• Understanding of low-level code performance optimization

• Knowledge and experience with GPU programming e.g. CUDA

Who excels in this role? 

• Someone who loves getting things done!

• Open-minded - eager to ask for comments/suggestions for improvement

• Passionate for anything and everything data

• Able to share and suggest ideas

• Love doing tons of research

• Have a can-do and will-do attitude!

• Ready to tackle any challenges

What are some of the benefits of working at Sertis? 

• Hybrid working environment

• Up early or slow starter in the morning? We have flexible office hours

• Mentorship programs for every level; from executive-level coaching to fresh grad

• Learning support- to help you build your skillset and grow your career

• Get to work and learn from the best in the industry, and share your ideas with like-minded individuals

• ​We cultivate intelligence and learning so that our experts can become community leaders in their respected fields in the tech industry

• Amazing colleagues to enjoy company social outings, parties, and events

• Result-oriented workplace; We provide direction, not orders and give you the autonomy to deliver your best work

• We work at the frontier of innovation in the AI industry

• Work on meaningful solutions that solve and improve real-life problems and challenges

• We run like a startup, and embrace the adventure; we focus on getting things done, while still having a down-to-earth and informal culture

• ​This is your chance to build your career in a growing data-driven industry.