Machine Learning Engineer

Our partner, a company headquartered in New York, creates an AP solution combining smart automation with spending intelligence to drive material savings and empower finance teams to make smarter spending decisions. 

*Your background: 

• Higher technical education; 

• 2-4 years of practical experience experience with Python; 

• at least 1 year of commercial experience with machine learning 

*Skills, competencies: 

• Capacity to work independently 

• Good communication skills 

• Willingness and readiness to develop professionally 

*Technical knowledge: 

• In-depth knowledge of Python  

• Fast API framework 

• Intermediate machine learning knowledge (pandas, numpy, scikit learn, light gum, xg boost)  

• Experience in LLM deployment (Lang chain, Open AI, Vertex AI) 

• Experience with ML inference 

*It will be a plus:  

• Kubeflow/Kserve framework for ML 

• Ray framework 

• Kubernetes knowledge 

• Terraform knowledge 

Your responsibilities:

• Maintain and deploy
• Machine learning infrastructure
• Support Existing Data Pipeline of the project
• Should be trained and deployed multiple models.

*What we offer:  

• Flexible work schedule;  

• Ability to work remotely from Ukraine;  

• Possible formats of cooperation: 3rd form Individual entrepreneur or cooperation under GiG contract (preferably);  

• Offices in the centre of Lviv or Kyiv (if you prefer to work from the office);  

• 20 days of vacation and the opportunity to take a paid day off on Ukrainian public holidays;   

• Unlimited paid sick leave;  

• Maternity leaveprograms;  

• Paid sabbatical after five years of work in the company;  

• Compensation for English lessons, professional courses, books, and participation in local and foreign conferences;  

• Physical and mental health support program (gym, swimming pool, psychologist, etc.);  

• Legal and accounting support;  

*Interview steps: 

• TA — 1 hour (introduction, discussion of your practical experience etc); 

• Technical interview — 1.5 hours/2 team members 

• 30 minutes call introduction with our partner 

• Technicall assessment — 3 hours 

• 1 hour interview with the team lead, engineering lead and CEO