Senior GenAI / Machine Learning Engineer

Description

Why Ness

We know that people are our greatest asset. Our staff’s professionalism, innovation, teamwork, and dedication to excellence have helped us become one of the world’s leading technology companies. It is these qualities that are vital to our continued success. As a Ness employee, you will be working on products and platforms for some of the most innovative software companies in the world.
You’ll gain knowledge working alongside other highly skilled professionals that will help accelerate your career progression. 
You’ll also benefit from an array of advantages like access to trainings and certifications, bonuses, and aids, socializing activities and attractive compensation.
 
Requirements and responsibilities

We are looking for a Senior GenAI / Machine Learning Engineer to join our team.
In this role, you will design, build, and deploy LLM‑powered and ML‑driven systems that operate at production scale. You will work on advanced data engineering pipelines, develop intelligent models for large‑scale data processing, and contribute to next‑generation AI capabilities that enhance client’s global location and mapping products.
This is an opportunity to work with cutting‑edge AI technologies, solve complex engineering challenges, and shape production‑grade ML systems used by millions of end users worldwide.
 
What you’ll do

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Machine Learning, or related field;
• 5+ years of experience in ML engineering, data engineering, or software engineering with a strong ML focus;
• Ability to write clean, efficient, and maintainable code;
• Strong analytical mindset, problem solving skills, and attention to detail;
• Comfortable working in fast paced, agile environments;
• Strong expertise in GenAI / LLM engineering including hands on experience with modern LLM frameworks and tooling;
• Proven experience in applied machine learning, including model development, evaluation, and optimization;
• Advanced Python programming skills and deep familiarity with ML libraries and ecosystem tools;
• Solid understanding of data engineering foundations, including ETL pipelines, distributed processing, and data quality;
• Demonstrated experience deploying production ML systems (batch or real time);
• Experience with cloud platforms (AWS preferred) for scalable ML and data workloads;
• Strong understanding of software engineering best practices, version control, CI/CD, and testing.

• Experience working with geospatial or maps related datasets;
• Knowledge of cost optimization strategies for ML workloads and cloud infrastructure;
• Familiarity with the Places ecosystem or similar location based data domains;
• Exposure to workflow orchestration tools (Airflow, Prefect, Luigi);
• Experience with containerization and orchestration (Docker, Kubernetes).

If this role sounds good to you, even if you don’t meet every single bullet point in the job description, we encourage you to apply anyway. For most of the candidates that applied, we found a role that was a very good fit with their skills.
Let’s meet and you may just be the right candidate for one of our roles.
At Ness Digital Engineering we are willing to build a work culture that is based on diversification, inclusion, and authenticity.