AI/ML Engineer
Job Summary
Job Description
As an AI/ML Engineer at Ness Digital Engineering, you will collaborate on designing, developing, and implementing cutting-edge Generative AI solutions. Responsibilities include researching advancements in Generative AI, optimizing models, working on end-to-end development (ideation to deployment), and staying current with industry trends. You'll be involved with AI Agents, RAG, and tools like CrewAI, LangChain, LlamaIndex, and HuggingFace. Experience with AWS (Bedrock, SageMaker), LLMOps, Docker, Kubernetes, and strong Python/ML framework skills (PyTorch/TensorFlow) are essential. The role requires an advanced degree and 6+ years of experience in AI/ML.
Must have:
- Generative AI solutions development
- Deep learning & neural networks
- Large Language Models expertise
- AI Agents & RAG experience
- AWS (Bedrock, SageMaker) expertise
- Python & ML frameworks proficiency
- Data pre-processing experience
- Model fine-tuning experience
Good to have:
- CrewAI, LangChain, LlamaIndex, HuggingFace experience
- LLMOps expertise
- Docker and Kubernetes familiarity
Perks:
- Access to trainings and certifications
- Bonuses
- Socializing activities
- Attractive compensation
13 skills required
Job Details
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
What you’ll do:
- Collaborate with cross-functional teams to design, develop, and implement cutting-edge Generative AI solutions.
- Research and experiment with the latest advancements in Generative AI, ensuring our solutions remain on the leading edge of technology.
- Optimize and fine-tune models for performance, scalability, and efficiency.
- Work on end-to-end development, from ideation to deployment, ensuring a seamless integration of Generative AI into various software ecosystems.
- Stay abreast of industry trends, emerging technologies, and best practices, contributing to a culture of continuous learning and improvement.
What you’ll bring:
- Advanced degree in Computer Science, Machine Learning, or a related field;
- 6+ years of experience as an AI/ML engineer/data scientist;
- Proven experience in developing Generative AI solutions;
- Solid understanding of deep learning concepts, neural networks, and reinforcement learning;
- Solid understanding of Large Language Models, Transformers architecture, self-attention, mixture of experts, and embedding models;
- Proven experience with AI Agents and advanced Retrieval Augmented Generation;
- Experience with CrewAI, LangChain / LangSmith / LangGraph, LlamaIndex and HuggingFace;
- Experience with model fine-tuning;
- Hands-on data pre-processing experience;
- Strong Python expertise;
- Proficiency in ML frameworks such as PyTorch, TensorFlow, or similar
- Experience with AWS development and deployment (ECS, Lambda, S3);
- Expertise with AWS Bedrock and SageMaker;
- Expertise with LLMOps;
- Familiarity with Docker and Kubernetes;
- Strong problem-solving skills and a passion for tackling complex challenges.
Not checking every single requirement?
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.
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