We are seeking a skilled Machine Learning Engineer to develop and maintain scalable ML systems that support advanced data analysis and AI-driven insights. In this role, you will collaborate closely with data scientists and engineers to design pipelines, tools, and production-grade solutions that turn complex datasets into actionable intelligence. You will ensure smooth transitions from prototypes to operational systems, working in a cloud-based environment that emphasizes reliability, efficiency, and experimentation. Ideal candidates are proactive, collaborative, and passionate about building robust ML infrastructure that enables innovation at scale. This role offers exposure to cutting-edge technologies and the opportunity to contribute to impactful AI applications in a fast-paced environment.

Accountabilities

Design, develop, and maintain machine learning pipelines for data ingestion, feature processing, model training, deployment, and monitoring
Adapt and extend ML tools and frameworks to meet the specific needs of data science teams
Integrate internal and external APIs to connect datasets, models, and services efficiently
Ensure infrastructure and processes support fast experimentation while maintaining reliability, security, and scalability
Act as a technical partner to data scientists, enabling smooth execution of modeling projects and production deployment
Bridge the gap between research prototypes and production-grade ML systems

Requirements

2+ years of experience as a Machine Learning Engineer, ML-focused Software Engineer, or equivalent, delivering production-grade ML systems
Bachelor's degree in Computer Science, Mathematics, or a related technical field
Strong Python skills for ML pipeline development, including experience with packages such as pandas, scikit-learn, and PyTorch
Proficiency in software development best practices: writing clean, maintainable, and well-tested code
Experience with SQL and building scalable data processing workflows (e.g., Apache Spark, Airflow, dbt)
Strong communication skills and the ability to translate technical solutions for non-engineers
Highly desirable: experience with cloud environments (AWS), containerization (Docker), REST API integration, MLOps frameworks, geospatial/imagery data processing, and familiarity with insurance or property/casualty domains

Benefits

Quarterly wellbeing days off (4 additional "YOU" days per year)
Company-sponsored volunteering days
Generous parental leave policies
Access to LinkedIn Learning for continuous development
Discounted health insurance plans
Monthly technology allowance
Subscription to company products for personal use

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.

🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.

📊 It compares your profile to the job's core requirements and past success factors to determine your match score.

🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.

🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role.

Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

Thank you for your interest!