Position: Senior Machine Learning Engineer
Company: AltexSoft
Category: Data Science
Experience required: 3y
English level: upper
Published: 2022-08-01T00:00:00+03:00

The company applies machine learning to make optimal use of electronic health data for the most vulnerable healthcare population. Its mission is to improve patient outcomes by augmenting clinical decision-making with the power of AI. Based in Silicon Valley, our team is a group of passionate healthcare technology veterans, engineers, and data scientists leveraging cutting-edge technology to predict patient risk and provide tools that drive timely intervention.

As a Machine Learning Engineer, you will work with an exceptional team including data scientists and strong MLops engineers to design, prototype, engineer, test, deploy and maintain ML platforms and applications for real-world production use. As part of this team, you will primarily lead the rapid prototyping of new models and model features. You will also be working with and learning from leading machine learning and data science faculty from Stanford University. Working with them may also open the door to later advancing your education with a graduate-level degree.

Requirements:

- BS in Computer Science or related technical field
- 1.5 years of proven machine learning experience in academia or industry
- Strong class-based understanding of the foundational concepts of machine learning
- Proven familiarity with one or more Machine Learning libraries and SQL
- Strong proficiency in Python (preferred), Java or C/C++
- Attention to detail and ability to work independently
- Excellent communication skills and ability to work well in a team
- Passion for problem-solving

Would be a plus:

- Master's degree in a relevant technical field Familiarity with cloud-based infrastructure (AWS preferred)
- Experience in niche machine learning areas (Healthcare models, NLP, Recommender Systems, Explainability)
- Active profile in Kaggle, GitHub, Stack Overflow, or similar

Responsibilities:

- Design, code, and test machine learning model prototypes
- Translate novel ideas and use new packages to make testable prototypes
- Improve the classification performance of existing machine learning models
- Collaborate with data scientists to perform error analysis and derive actionable insights into improving your prototypes
- Guide ML ops engineers in converting your prototypes into production models

What we offer:

- Close collaboration with the client and the ability to influence the result and the process;
- Being a part of a proactive and friendly team;
- Supportive environment and tech communities;
- Development of Individual Development Plans to build a transparent career within the company;
- Social benefits (incl. vacation, sick leaves, education, etc)