Sigma Software Group is hiring a
Machine Learning Internship

Summary

Join our team as an intern and get a chance to deepen your knowledge, develop your experience with real projects & work with top engineers from the first weeks of internship. You'll receive mentorship, education program overview, project tasks overview, hardware, educational courses, certification programs, free access to cloud infrastructure, friendly working environment, possibilities to work from our comfortable offices or from home.

Requirements

• Studies in University or finishes a BSc or MSc diploma from the IT or math fields or proven/presentable self-study with online courses and pet-projects
• Has proven experience with Python
• Knows the fundamentals of algorithms and data structures, SQL databases, fundamentals of Machine Learning
• Basics of Pandas, NumPy or similar libraries
• Nice to have basic knowledge in NLP / text processing domain
• Experience with the following tools: Git, nice to have experience with task tracking systems like Jira
• Has clear and effective written and verbal communication skills
• At least Intermediate level of English

Responsibilities

• Working on internal project on ML and software development tasks mainly in NLP area
• Picking up hard skills following 2-6 months training program, created together with the mentor’s supervision
• Brushing up on your soft skills, including communication, listening, self-organization, problem-solving, searching abilities, presentation skills, emotional intelligence & motivation
• Improving your English language skills
• Obtaining the hard & soft skills, that are necessary to get the Junior ML Engineer position (according to our internal Skills Grade Matrix)
• Follow company policies regarding to time schedules, regulations, and security
• Participate in your team activities, such as knowledge sharing, brainstorm sessions, team buildings, helping others, etc
• Analyze functional and non-functional requirements, clarify with stakeholders if required
• Complete your first internal project with the mentor’s supervision