Staff ML Engineer

About the Role

We are seeking an experienced Staff ML / Prompt Engineer to lead the design, development, and optimization AI solutions. You will collaborate cross-functionally with software engineers and product managers to architect prompt engineering strategies, fine-tune models for maximum effectiveness, and ensure the delivery of innovative products. This is a key technical role, blending expertise in machine learning, prompt engineering to push the boundaries of what’s possible with AI-driven applications.

This is a full-time position based out of our Novi-Sad office.

Technologies You’ll Use

• Python, Java, GPT-like models, Cloud, Data scraping

What You’ll Do

• Design, test, and refine prompt structures to optimize the performance of advanced language models (e.g., GPT-like models).
• Experiment with different prompt engineering techniques (e.g., chain-of-thought, few-shot, zero-shot) to improve accuracy and reduce model biases.
• Conduct research on state-of-the-art NLP and embedding approaches to enhance model capabilities and performance.
• Collaborate with product and engineering teams to integrate ML solutions seamlessly into existing platforms and pipelines.
• Mentor junior members of the ML team, sharing knowledge on advanced modeling techniques and best coding practices.
• Provide technical guidance and leadership in code reviews, system design meetings, and documentation.
• Stay up-to-date with the latest advancements in NLP, deep learning, and generative AI.
• Establish performance benchmarks, develop ML metrics, and monitor system performance in production.

Skills We’re Looking For

• 5+ years of experience in machine learning, natural language processing, or a related field.
• Expertise in Python.
• Deep understanding of state-of-the-art NLP techniques (transformer-based architectures, large language models, embeddings, etc.).
• Solid experience in prompt engineering, including knowledge of zero-shot, few-shot, and chain-of-thought prompting.
• Familiarity with ML Ops tools and practices (Docker, Kubernetes, CI/CD pipelines, model versioning, etc.).
• Strong analytical skills with the ability to design experiments and interpret complex data sets.
• Effective communication skills with both technical and non-technical stakeholders.
• Ability to lead cross-functional initiatives and guide others in adopting best practices.
• Passion for research, experimentation, and staying current with emerging ML trends.
• Problem-solving mindset, with a strong focus on delivering practical, scalable solutions.

Bonus Skills​

• Java backend knowledge

#LI-HYBRID

#LI-NR1