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.
About the Role
We are looking for an experienced AI/ML Engineer with deep expertise in feature engineering and model engineering to join our team
Key Responsibilities
Be Technical:
- Design and implement AI pipelines for automating royalty calculation and relation processes etc.
- Integrate foundation models (LLMs, vision models, etc.) into products using APIs and custom fine-tuning.
- Develop and maintain retrieval systems that operate efficiently at scale
- Explore frontier software engineering in AI/ML for media, and related opportunities for UMG.
- Build on state-of-the-art cloud infrastructure
- Collaborate with the team and stakeholders to deliver, operate and maintain products.
- Be part of an innovative and dynamic team
Must have
- Background in Computer Science, Software Engineering, ML Ops, Artificial Intelligence or related technical field.
- 5+ years of hands-on professional experience in software/ML engineering
- Proven ability to come up with designs for AI/ML systems, pipelines and/or applications, and to implement them successfully.
- Expertise in quantitative evaluation and benchmarking of state-of-the-art AI models.
- Up to date knowledge of state of the art for ML Ops, ML infrastructure, including related tools, design patterns, best practices etc.
- Experience with vector databases (e.g., Pinecone, FAISS, Milvus, Weaviate) and information retrieval systems and methods.
- Familiarity with media content (video, audio) ML pipelines.
- Proficiency in Python and common AI/ML libraries (e.g., PyTorch, Hugging Face Transformers, LangChain) and cloud frameworks (VertexAI, Bedrock, Sagemaker)
- Strong proficiency in Git, CI/CD workflows, and containerization (Docker/Kubernetes).
- Proficiency with Linux environments and cloud platforms (e.g. AWS, Google Cloud Platform)
- Ability to write clean, efficient, well documented, and reusable code
- Good communication skills, both oral and written
- Curious, self-motivated, and proactive.
- Experience training and/or fine-tuning AI models