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Responsibilities
- Understand business objectives and develop models to achieve them
- Use computer science fundamentals, including data structures and algorithms
- Analyze ML algorithms and rank them by success probability
- Build algorithms and maintain scalable machine learning solutions
- Apply machine learning algorithms and libraries
- Explore and visualize data to understand it and identify distribution differences
- Verify data quality and ensure it via data cleaning
- Supervise the data acquisition process for additional data needs
- Find available datasets online for training
- Train models and tune their hyperparameters
- Analyze model errors and design strategies to overcome them
- Manage infrastructure and data pipelines for production deployment
- Support engineers and product managers in implementing machine learning
- Collaborate with data engineers to build data and model pipelines
- Liaise with stakeholders to analyze business problems and define requirements
- Develop machine learning applications according to requirements
Requirements
- Proven experience as a Machine Learning Engineer or similar role
- Understanding of data structures, data modeling, and software architecture
- Deep knowledge of math, probability, statistics, and algorithms
- Technical expertise in AI, ML, deep learning, and related technologies
- Experience in developing AI/ML models in real-world environments
- In-depth experience with AWS and/or Microsoft Azure AI/ML services
- Effective data exploration and visualization experience (e.g. Excel, Power BI)
- Familiarity with machine learning frameworks and libraries
- Excellent communication skills and teamwork ability
- Outstanding analytical and problem-solving skills
- Ability to explain complex processes to non-experts
- Experience with Amazon Cloud and AWS AI services
- Upper-Intermediate English proficiency or higher
- Previous client communication experience with a technical consulting ability
- Pharma domain background
Benefits
- Competitive compensation with performance-based reviews
- Join a passionate, experienced team in a friendly atmosphere
- Opportunities for professional and career advancement
- Paid Time Off: 18 business days per year (20 after 2 years)
- Sick Leave: Non-documented 4 days/year, documented 20 days/year
- Family Leave: 3 paid days for marriage, childbirth, or bereavement
- Comprehensive medical insurance coverage
- English courses for language improvement
- Participation in forums and conferences for professional development
- Regular team-building activities and corporate events
- Comfortable, fully equipped office with work-from-home options
