Position: Computer Vision Tech Lead
Company: SELECT*
Category: Data Science
Experience required: 5y
English level: upper
Published: 2022-07-01T00:00:00+03:00

**SELECT*** is a professional team of recruiting specialists who are searching for talents in Ukraine, Europe, and the USA. Currently, we are looking for a **Computer Vision Tech Lead** for **Brainly**.

**Brainly** is the online learning platform where over 350 million students and parents go from questioning to understanding. With their smartphones, users can snap a photo to instantly solve any problem or homework question and be matched with a Brainly product such as Community Q&A, Brainly Tutor, Math Solver or Textbook Detective. 

**Brainly** is built to provide students, parents, experts, and teachers with a collaborative platform and tools needed to succeed in any educational environment.

The AI Services department represents a major investment toward the vision of implementing an AI-powered Predictive Intervention platform. The platform will enable every student to receive tailored recommendations satisfying their current and future educational needs, and provide successful and specific learning paths.

In order to get there, they are building the fundamental pillars of their AI strategy by having dedicated teams owning different systems of their  technology portfolio and in particular they are heavily investing in visual search technologies.

The Visual Search Systems team supports other search and production teams by providing computer vision capabilities to:

Improve and introduce new functionalities to classify images and extract visual information to improve retrieval precision and personalize the answering results
Leverage real-time mobile devices capabilities to provide a better answering experience
This is a Tech Lead role where you will act as the technical partner to the team manager. You will lead a team of world-class scientists and engineers driving the data science capabilities of their knowledge base and state-of-the-art Computer Vision algorithms both server-side and client-side (mobile devices) on top of the PyData stack, PyTorch, Tensorflow, Sagemaker, and other AWS cloud services.

The ideal candidate is an enthusiast of educational technologies with a product-oriented data science background and a blend of leadership, machine learning, and statistics skillset.

**Responsibilities:**

**Team Leadership**

- Be responsible for making technical decisions in the scope of the team work.
- Guide the team in technical decisions and be accountable for them.
- Coordinate the work breakdown, sprint-level planning, and day-to-day team operations.
- Lead by example, showing how to get things done and being among the top contributors of the team.
- Technical mentoring and reviews (code and analysis).

**Research & Development**

- Research and implement novel techniques of computer vision algorithms – such as objects detection and image classification – on both back-end and resource-constrained edge devices (e.g. mobile phones).
- Explore and analyze multi-dimensional and unstructured data in order to find patterns and relationships.
- Effectively communicate results and storytelling with the data.
- Ensure statistical and scientific rigor among the whole team.

**Delivery Management**

- Design systems, architectures, methodologies, and define technical and research specifications.
- Contribute to the definition of the team roadmap and deliverables.
- Plan and estimate technical capacity and efforts required.
- Responsible for the technical success and quality of the team deliverables.

**Relationship development**

- Support the project manager on collecting requirements and feedbacks as well as aligning multiple technology and product teams, business and management stakeholders on the ML systems owned by the team.
- Collaborates with team, other tech leads, and the management to develop process, policy, protocols, and solutions related to best practices or common issues.
- Educate Brainly employees on the topics related to Data Science & Machine Learning and the importance of high-quality contents.
 

**Requirements:**

- Bachelor’s degree or above in STEM fields (science, technology, engineering, or mathematics) or a similarly quantitative field.
- Deep knowledge and understanding of theoretical foundations of classical Machine Learning (Bayesian statistics, Linear regression, Logistic Regression, Dimensionality Reduction, Clustering), strong theoretical background in classic Computer Vision (Image Processing, Feature Detection, Structure from motion) and Deep Learning architectures.
- 6+ years experience, or a comparable industry career, with machine learning, data mining, or statistical modeling.
- 4+ years experience with Deep Learning models for Computer Vision in production (ability to prototype and test suboptimal solutions quickly and iterate up to a final product that can be deployed).
- Working knowledge of Python and the PyData stack or other numerical programming languages.
- Machine Learning technologies such as: Tensorflow or PyTorch, AWS Sagemaker, scikit-learn, cuML, NVIDIA DALI, OpenCV.
- Distributed computing systems such as Spark, dash, Ray.
- Data analysis and visualization tools such as pandas, cudf, matplotlib or streamlit, plotly, dash, bokeh and ability to convey complex analyses with the most efficient and intuitive visual interactions and data storytelling.
- Proficiency with Docker containers, experience with SQL and relational databases.
- Ability to understand and code from the latest state-of-the-art research papers.
- A scientific mentality with the ability to ask the right questions, as well as answer them, ability to break research down into clearly defined tasks and quick iterations.
- Proven technical leadership of complex data science teams or machine learning projects involving multiple roles and/or teams (hands-on tech leader attitude and clear communications skills, familiar with agile development and lean principles).
- A track record of attracting and retaining world-class AI talents – you can demonstrate that you are someone with whom engineers want to work with, who has a deep appreciation for understanding team growth and you can share this passion to motivate the team and the wider organization.
 

**Nice to have:**

- PhD with publications in Statistics, Data Science, Computer Science, Machine Learning, Mathematics or similar.
- Experience with Machine Learning at the Edge (TinyML – technologies such as TensorflowLite, CoreML, TensorRT, DeepStream, Google ML Kit) either on Android, iOS, custom hardware, or other devices.
- Experience with analyzing massive datasets and training machine learning algorithms on distributed clusters.
 

**Benefits:**

- They want to see you grow along with them -  you will have 800$ per year for personal development, extra time for attending conferences and workshops, and unlimited access to an online learning platform (courses from Coursera, Udacity, Udemy, Harvard ManageMentor, and many others).
- Health is important, which is why at Brainly, they fully cover private health & dental care packages for you and your family and provide you with a sport card (Multisport Plus in Poland, Andjoy in Spain). 
- You will also get an access to online individual psychological consultations with professionals in English & Polish via the Mental Health Helpline.
- Flexible working hours – working requires communication, so they work within the European business hours, but they also know that life may be unpredictable, so if you need to jump out of work (doctor’s appointment, emergency, anything) – no problem!
- Your personal concierge AskHenry will support you in your daily duties, eg. planning your dream vacation.
- They will provide you with all the necessary equipment & tools, including an additional budget for accessories which will make your remote setup even more comfortable.
- You can join internal communities and contribute to charity, diversity and inclusion initiatives, take part in great internal events or represent Brainly at conferences or meet-ups.