🌎 Akvelon is a known USA company, with offices in places like Seattle, Mexico, Ukraine, Poland, and Serbia. Our company is an official vendor of Microsoft and Google. Our clients also include Amazon, Evernote, Intel, HP, Reddit, Pinterest, AT&T, T-Mobile, Starbucks, and LinkedIn. To work with Akvelon means to be connected with the best and brightest engineering teams from around the globe and working with an actual technology stack building Enterprise, CRM, LOB, Cloud, AI and Machine Learning, Cross-Platform, Mobile, and other types of applications customized to the client’s needs and processes.
We are looking for a Machine Learning Engineer to design and implement advanced models for ranking, personalization, and recommendation systems. This role involves developing innovative machine learning solutions to tackle complex, greenfield business challenges with real-world impact.
The ideal candidate combines strong technical skills in ML and recommendation systems, practical experience deploying ML models, and a collaborative mindset. The candidate should be comfortable designing systems from scratch, testing and improving them, and working with others to turn insights into real business value.
Responsibilities:
- Drive research ideas from first-principles conceptualization to practical realization.
- Collaborate with engineers to design and implement solutions that balance theoretical elegance with practical constraints.
- Develop innovative strategies for creating, collecting, and assessing high-quality datasets, including synthetic data generation.
- Design robust evaluation techniques and benchmarks for assessing diverse product properties.
- Conduct experiments to evaluate new methodologies and their impact on product outcomes.
- Stay up-to-date with the latest machine learning research to inform and guide model development.
- Research, train, evaluate, and improve machine learning models for ranking and personalization.
- Analyze data to uncover patterns, correlations, and opportunities for improvement.
- Conduct applied research to develop and launch models that enhance strategic products.
- Work cross-functionally with engineers, business stakeholders, and subject matter experts to align solutions with business goals.
- Address complex technical challenges in a fast-paced, ambiguous environment, designing innovative solutions to meet evolving needs.
- Communicate complex findings and research results through clear, concise, and compelling explanations, tailored to both technical and non-technical audiences, to drive understanding and collaboration.
Requirements:
- 4+ years of industry experience building production ML systems.
- Deep expertise in designing and implementing end-to-end ML systems, particularly in ranking or recommendation.
- Expert knowledge of ML fundamentals including feature engineering, model selection, evaluation metrics, and monitoring.
- Proven ability to design and evaluate machine learning models, benchmarks, and experiments.
- Strong coding skills in Python and experience with NLP and ML frameworks (e.g. PyTorch, TensorFlow).
- Experience with feature stores, model serving infrastructure, and ML pipelines.
- Strong communication and independence skills.
- Working with daily overlap till 8 pm CET (2 pm EST).
Nice to have:
- Experience or interest in finance/investing domain.
- Experience with ML platforms (Google Vertex AI).
Working conditions and benefits:
- Paid vacation, sick leave (without sickness list)
- Official state holidays — 11 days considered public holidays
- Professional growth while attending challenging projects and the possibility to switch your role, master new technologies and skills with company support
- Flexible working schedule: 8 hours per day, 40 hours per week
- Personal Career Development Plan (CDP)
- Employee support program (Discount, Care, Health, Legal compensation)
- Paid external training, conferences, and professional certification that meets the company’s business goals
- Internal workshops & seminars
- Corporate library (Paper/E-books) and internal English classes
Don’t miss out on this opportunity! Submit your application today.
