ML Engineer
- Level
- Mid
Not stated in the posting: salary, work type, visa.
Open. First seen 3 October 2026.
About the role
We are toogeza, a Ukrainian recruiting company that is focused on hiring talents and building teams for tech startups worldwide. People make a difference in the big game, and we may help to find the right ones.
Currently, we are looking for an experienced Senior ML Engineer to join one of toogeza’s clients.
Professional qualifications
- 7+ years’ experience in Machine Learning / Data Science, with 3+ years in credit-lending organisations.
- Demonstrated delivery and productionisation of Probability-of-Default (PD) models, credit-limit strategies, fraud-detection, conversion-uplift, and collections-optimisation models.
- Advanced Python proficiency and solid grasp of modern ML algorithms, feature engineering, and model-evaluation best practices.
- Ability to write, structure, and optimise complex SQL queries.
- Deep understanding of the credit lifecycle, especially online lending workflows.
- Proven skill in sourcing, cleansing, and generating features from data sets.
- Comfortable setting up and maintaining modelling environments (local, cloud, or on-prem).
- Detail-oriented, accountable, and committed to both team and individual targets.
- English: Intermediate (B1) or higher.
Preferred / bonus qualifications
- Practical experience with LLM solutions:
- Using commercial APIs (e.g., OpenAI, Anthropic, etc.).
- Self-hosting of open-source models
- Fine-tuning of open-source models.
- Building voice chatbots.
- Building RAG chatbots.
- Experience with Computer Vision models for document or image processing.
- Building ML pipelines and deploying models to production.
- Creating executive dashboards and model reports in Power BI.
Main responsibilities
- Design, train, and deploy probability of default models.
- Build credit-limit strategies.
- Discover and scope AI/ML opportunities that boost efficiency and revenue of the company, including collections optimisation, fraud control, conversion lift, etc.
- Analyse data sources and engineer features for modelling.
- Produce and update internal model documentation.
- Implement model monitoring.
- Plan and execute A/B tests.
- Build Computer Vision pipelines to automate lending workflows.
- Develop LLM-based solutions that streamline internal processes or enhance customer experience.
Expected results
- Implemented probability of default models and credit-limit strategies.
- Launched A/B tests for models that potentially can boost the efficiency and/or revenue of the company.
- Thorough, audit-ready documentation for models.
What We Offer
- Join a fast-scaling FinTech company where your decisions shape the business and your contributions truly matter.
- Enjoy 20 paid days off annually, flexible scheduling, and a supportive, people-first culture.
- Partial compensation for medical insurance, sports activities, and foreign language.
- Work in an international, agile team with ambitious goals, modern tools, and a strong sense of purpose.
Professional qualifications
- 7+ years’ experience in Machine Learning / Data Science, with 3+ years in credit-lending organisations.
- Demonstrated delivery and productionisation of Probability-of-Default (PD) models, credit-limit strategies, fraud-detection, conversion-uplift, and collections-optimisation models.
- Advanced Python proficiency and solid grasp of modern ML algorithms, feature engineering, and model-evaluation best practices.
- Ability to write, structure, and optimise complex SQL queries.
- Deep understanding of the credit lifecycle, especially online lending workflows.
- Proven skill in sourcing, cleansing, and generating features from data sets.
- Comfortable setting up and maintaining modelling environments (local, cloud, or on-prem).
- Detail-oriented, accountable, and committed to both team and individual targets.
- English: Intermediate (B1) or higher.
Preferred / bonus qualifications
- Practical experience with LLM solutions:
- Using commercial APIs (e.g., OpenAI, Anthropic, etc.).
- Self-hosting of open-source models
- Fine-tuning of open-source models.
- Building voice chatbots.
- Building RAG chatbots.
- Experience with Computer Vision models for document or image processing.
- Building ML pipelines and deploying models to production.
- Creating executive dashboards and model reports in Power BI.
Main responsibilities
- Design, train, and deploy probability of default models.
- Build credit-limit strategies.
- Discover and scope AI/ML opportunities that boost efficiency and revenue of the company, including collections optimisation, fraud control, conversion lift, etc.
- Analyse data sources and engineer features for modelling.
- Produce and update internal model documentation.
- Implement model monitoring.
- Plan and execute A/B tests.
- Build Computer Vision pipelines to automate lending workflows.
- Develop LLM-based solutions that streamline internal processes or enhance customer experience.
Expected results
- Implemented probability of default models and credit-limit strategies.
- Launched A/B tests for models that potentially can boost the efficiency and/or revenue of the company.
- Thorough, audit-ready documentation for models.
What We Offer
- Join a fast-scaling FinTech company where your decisions shape the business and your contributions truly matter.
- Enjoy 20 paid days off annually, flexible scheduling, and a supportive, people-first culture.
- Partial compensation for medical insurance, sports activities, and foreign language.
- Work in an international, agile team with ambitious goals, modern tools, and a strong sense of purpose.
What this role asks for
Particular to this role
Computer Vision · RAG
Rare in Toogeza's other 14 open postings.
Standard for data science / ML roles
LLM · Machine Learning · Python · SQL
Common in data science / ML postings at any company.
Read against Toogeza's other open postings on this site.
The team: Engineering HIRES STEADILY
This role is one of 7 open in Engineering. 2 were posted in the last 30 days and the oldest in February: a team that hires all year rather than one being built.
WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS
Python (5 of 7), Machine Learning (3 of 7), Active Directory (2 of 7), Azure (2 of 7), Bash (2 of 7), Docker (2 of 7), Jira (2 of 7)
OTHER ROLES ON THIS TEAM
- IT Support Engineer posted Oct 14
- IT Infrastructure & Operations Engineer (SysOps) posted Oct 14
- Machine Learning Engineer — Physics AI posted Sep 8
- Senior Backend Engineer posted Aug 21
- AI Video Agent Engineer posted Jun 2
- Senior Machine Learning Engineer posted Feb 18
From the team and dates on Toogeza's own job board.
Salary context
5 other open postings titled ML Engineer state a salary: median USD 183,000 to USD 246,000 a year.
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