Senior Data Scientist (AI/ML)

TL;DR

Senior Data Scientist (AI/ML): Designing, training, and evaluating machine learning models using Python and ML frameworks, with an accent on exploring large datasets, feature engineering, and experimentation methods. Focus on integrating models into production workflows, applying model validation, and collaborating with cross-functional teams to define problem statements.

Location: Remote from Bulgaria or Poland, or hybrid/onsite in these countries.

Company

hirify.global is an AI-first global tech company with 25+ years of engineering leadership, specializing in digital transformation and AI platforms for Fortune 500 clients.

What you will do

• Design, train, and evaluate ML models using Python and established ML frameworks.
• Explore large datasets in BigQuery, create well-structured feature sets, and write advanced SQL.
• Implement experimentation methods such as A/B testing, uplift modeling, or time-series validation.
• Collaborate with ML/data engineers to integrate models into production workflows using GCP tools like Vertex AI.
• Participate in deployment planning, performance monitoring, model validation, drift detection, and retraining processes.
• Partner with product, analytics, and engineering teams, communicate findings, and mentor junior team members.

Requirements

• Strong experience with Python and libraries such as pandas, numpy, scikit-learn, TensorFlow, JAX, or PyTorch.
• Advanced SQL proficiency with comfort working inside BigQuery.
• Experience designing and evaluating ML models across structured datasets.
• Understanding of feature engineering principles and familiarity with model deployment patterns.
• Experience designing experiments and interpreting results using sound statistical methods.
• Advanced English proficiency (B2+).

Nice to have

• Experience with Vertex AI model training, model registry, or Feature Store.
• Familiarity with orchestration contexts such as Composer or Airflow.
• Experience using BigQuery ML for rapid prototyping.
• Understanding of modern MLOps approaches.
• Exposure to event-driven feature pipelines using Pub/Sub.

Culture & Benefits

• International projects and flexible work options (in-office, hybrid, or remote).
• Medical healthcare and well-being program.
• Recognition program, referral bonuses, and top-tier equipment provision.
• Ongoing learning and reimbursement opportunities.
• Culture that leads with trust, respect, open dialogue, creative freedom, and mentorship.
• Team events and local benefits.