Deep Learning Engineer

Job Summary

Our distributed team develops motion detection features, ensuring high performance through cloud-based solutions. We are responsible for calibrating Edge and Cloud collaboration to achieve the best results.

You will join as a Deep Learning Engineer and be responsible for day-to-day research tasks, such as setting up hypotheses, gathering data for experiments, training and validating ML models, validating results, and writing a paper on your results.

Duties and Responsibilities

Develop innovative machine learning algorithms. Implement advanced methods and technologies in model development
Analyze large datasets to identify correlations and patterns. Visualize research results for clearer interpretation
Tune hyperparameters and optimize algorithms. Improve models to enhance their performance and accuracy
Provide consultations and collaborate with colleagues from other departments
Report progress and project achievements to management
Explore and evaluate new technologies in the field of machine learning. Implement cutting-edge ideas and techniques into production processes
Engage in continuous self-improvement and technical skill development. Train and mentor junior colleagues to enhance the overall competence level within the team

Qualifications and Skills

3+ years in machine learning (computer vision domain)
Practical experience in at least one of the following problems: classification, detection, segmentation
Python3, NumPy, scikit-learn, pandas, SciPy
Deep learning frameworks: PyTorch
Experience in deploying machine learning models to production
Good understanding of machine learning and deep learning concepts
Good written and spoken English

Nice to have

Practical experience with GANs, VAEs
Probabilistic programming and bayesian framework
Model optimization: pruning, quantization, knowledge distillation
Basic understanding of web and client-server architecture
asyncio, aiohttp, and other async libraries for back-end
Basic understanding of Big Data, understanding of difference between MapReduce and in-memory processing
Algorithms, data structures
SQL, NoSQL
Docker, Kubernetes, Kubeflow
Bash

We offer multiple benefits that include

The environment of equal opportunities, transparent and value-based corporate culture and an individual approach to each team member
Competitive compensation and perks. Annual performance review
Gig-contract
21 paid vacation days per year, paid public holidays according to the Ukrainian legislation
Development opportunities like corporate courses, knowledge hubs, and free English classes as well as educational leaves
Medical insurance is provided from day one. Sick leaves and medical leaves are available
Remote working mode is available within Ukraine only
Free meals, fruits, and snacks when working in the office.

Deep Learning Engineer

Key Skills

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