At the moment our recruitment process for Senior Machine Learning Engineer is held entirely online.
We are looking for engineers who are passionate to stay at the forefront of machine learning technology, building state-of-the-art AI solutions for Fortune 500 businesses, and launching these solutions into production.
Responsibilities
- Research, develop, and productionize AI-enabled enterprise solutions using various software engineering tools and technologies
- Build systems that use machine learning techniques (including deep learning) to solve real-life business problems
- Choose the most suitable methods and algorithms to apply to a particular use case
- Create automation pipelines for data processing, machine learning modeling flows, and application deployments
- Work with various data sources to prepare datasets for training, validation, and optimization of models
Requirements
- MS or Ph.D. in Computer Science or a related technical field involving Artificial Intelligence & Machine Learning
- Capability of translating business use cases into a concrete model development strategy
- Strong programming skills in Python
- Experience in using Python for data analysis and modeling
- Experience with machine learning frameworks and libraries (e.g. PyTorch, TensorFlow, scikit-learn)
- Knowledge of software engineering principles and best practices
- Experience with cloud services and infrastructure (AWS, Azure)
- Knowledge of statistical techniques and understanding of their advantages and drawbacks
- Strong problem-solving skills
- Very good communication skills
- Very good command of English
Nice to have
- Experience with other programming languages and software engineering technologies (Java SQL, R, C++, Julia)
- Experience with ML automation tools (Metaflow, MLflow)
- Experience with end-to-end machine learning platforms (Dataiku, DataRobot, Azure ML, AWS Sagemaker)
Your benefits on this position
- Cafeteria MyBenefit
- Comfortable workstation
- Integration activities & trips
- Language lessons
- Learning opportunities
- Lunch&Learn
- Private medical care
- Sport activities