Senior Data Science Engineer

Hybrid, Office, Remote

Ukraine

Our client is the leading property portal in the Middle East and North Africa (MENA) region, dedicated to shaping an inclusive future for real estate while spearheading the region's growing tech ecosystem. At its core is a clear and powerful purpose: To change living for good in the region.

Requirements:

• Education: Master's or PhD in Computer Science, Machine Learning, Data Science, or a related field.
• Experience: 5+ years of experience in applied data science or machine learning engineering roles.
• Proven track record of deploying models in production environments with measurable business impact.
• Experience guiding junior data scientists or leading end-to-end ML projects independently.

Technical Skills:

• Expertise in supervised/unsupervised learning, deep learning (CNNs, RNNs, transformers), and statistical modeling.
• Strong foundation in scenario modeling, optimization, and evaluation metrics for performance and fairness.
• Proficiency in Python (pandas, NumPy, scikit-learn) and deep learning libraries (PyTorch or TensorFlow).
• Hands-on experience with LLMs, prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) pipelines.
• Experience integrating ML models via APIs and embedding AI in enterprise systems.
• Deep knowledge of cloud platforms (AWS/GCP/Azure) and containerized deployments (Docker, Kubernetes).
• Familiarity with ML pipelines, model registries, CI/CD, Git-based version control, and production monitoring.

Soft Skills:

• Exceptional communication and stakeholder management skills across technical and non-technical audiences.
• Strategic thinking with the ability to connect AI/ML capabilities to core business goals.
• Demonstrated ability to thrive in a fast-paced, collaborative, and dynamic environment.
• Strategic mindset with the ability to translate business goals into data-driven initiatives.

Responsibilities

• Lead the design and implementation of complex predictive and optimization models using classical ML/statistical methods, deep learning architectures, and generative techniques.
• Drive innovation in Large Language Models (LLMs), Generative AI, and Agentic AI—pioneering new applications such as enhanced personalization, lead qualification, content generation, and workflow automation.
• Own the end-to-end ML lifecycle: from hypothesis generation, experimentation, evaluation, and explainability, to scalable deployment in production systems.
• Develop and enforce rigorous evaluation and monitoring pipelines, including A/B testing, drift detection, and model fairness/robustness.
• Guide the development of advanced analytics and visualization solutions to support strategic business decisions at scale. – Collaborate closely with engineering teams to ensure resilient, low-latency, and production-grade deployment of AI systems.
• Embed trust, transparency, and auditability in all models—ensuring alignment with ethical AI and governance frameworks.
• Stay abreast of the latest in AI research and industry trends to keep our technology stack at the forefront.
• Implement MLOps and deployment best practices (CI/CD, automated workflows, model registry, versioning, and lifecycle management). –
• Cross-Team Collaboration: Act as a technical leader and mentor for junior team members, fostering a culture of excellence, innovation, and continuous learning.
• Collaborate with Data Platform and Engineering teams to optimize model deployment pipelines and infrastructure.
• Partner with Product, Strategy, Commercial, and Executive stakeholders to define AI roadmaps, align on business priorities, and communicate insights effectively.

What we offer:

• Annual paid vacation of 18 working days.
• Extra vacation days for long-lasting cooperation.
• Annual paid sick leave of 10 days.
• Maternity/Paternity leave.
• The opportunity for sabbatical leave.
• Marriage and Parenthood Package.
• Compensation for sports activities (up to 250$ per year) or health insurance covering (70%) — after the trial period.
• Internal education(corporate library).
• Career development plan.
• English and Spanish classes.
• Paying taxes and managing PE (Private Entrepreneur).
• Technical equipment.
• Internal Referral program.
• Opportunity to take part in company volunteering activities.
• Sombra is a "Friendly to Veterans" award-holder.