Lead Machine Learning Engineer (ML)

Location: Sofia, Bulgaria; hybrid remote/in-office role with flexible working hours and home office.

Company

hirify.global is a global data and technology company operating across financial services, healthcare, automotive, insurance and other markets, with 25,200 employees in 32 countries.

What you will do

• Lead the design, development, testing, governance, deployment and operation of reusable data attributes and ML capabilities at scale.
• Design technical architectures and integration patterns connecting analytical environments, data platforms and production services across markets.
• Evaluate data sources and methodologies, quantify predictive value, and explore synthetic data for experimentation and product development.
• Design data ingestion, transformation and ETL approaches, data-quality controls, and migration paths for legacy attributes and workloads.
• Lead complex implementations and proof-of-concepts, conduct architecture and code reviews, troubleshoot production issues, and establish engineering standards.
• Mentor engineers and data scientists and enable local Analytics and Engineering teams to operate new capabilities independently.

Requirements

• Strong software engineering fundamentals covering object-oriented programming, data structures, algorithms, design patterns, testing and maintainable design.
• Hands-on Python experience with data and analytical libraries such as Pandas and NumPy, plus experience developing production-grade data or ML applications rather than only prototypes or notebooks.
• Experience with applied machine learning and statistics, including model evaluation, feature engineering, overfitting, cross-validation and train/validation/test methodologies.
• Experience with large-scale data processing technologies such as Apache Spark, PySpark and Spark SQL; Databricks or a comparable modern data/ML platform; Delta Lake, distributed processing and data-quality controls.
• Experience developing reusable features or attributes, designing APIs and services, and applying software development lifecycle, Agile, code review and version-control practices.
• Practical experience with AWS or Azure and knowledge of compute, storage, networking, identity and access management, security and managed data services.
• Experience with CI/CD pipelines, Infrastructure as Code such as Terraform, Docker, Kubernetes, Linux environments, production troubleshooting, monitoring, logging and operational practices.
• Ability to translate requirements into technical designs, evaluate architectural trade-offs, create reusable solutions, lead architecture reviews, improve code quality and manage technical and delivery risks.
• Ability to communicate complex technical concepts to technical and non-technical audiences and collaborate across engineering, analytics, product and geographically distributed teams.

Nice to have

• FastAPI or similar API frameworks, ML lifecycle and MLOps practices, and Jenkins.
• Azure services including Blob Storage, Virtual Machines, Microsoft Entra ID, Databricks and Azure Data Factory, or relevant AWS services such as S3, EC2, Lambda, EKS, SageMaker, OpenSearch and managed Kafka.
• Apigee, SSO or identity integrations such as Okta, and experience migrating legacy analytical or data workloads to modern cloud platforms.
• Experience building platforms, frameworks or tooling for Data Science or Analytics teams.
• Experience in regulated, data-intensive environments such as financial services.

Culture & Benefits

• Permanent, full-time employment in a hybrid role with flexible working hours and home-office opportunities.
• Professional development programs, career pathways and unlimited access to online training, learning materials and books.
• Social benefits including life insurance, food vouchers, additional health and dental insurance, a monthly flex allowance, corporate discounts, Multisport, Sharesave and employee assistance programs.
• 25 days of paid vacation, one additional birthday day off and three extra paid days for participation in social-responsibility events.
• Inclusive, purpose-driven workplace with a recognized team culture and equal-opportunity and accommodation support.

Hiring process

• Applications and recruitment communications are handled through authorised hirify.global channels and official hirify.global.com email addresses.
• hirify.global never asks candidates to make payments during application, interview, assessment, onboarding or recruitment.