Whether you're a Data Scientist, App Engineer, Tester or Developer — your ideas matter here. At Indium, growth is continuous, curiosity is celebrated, and innovation never stops. You'll build with people who question everything, prototype fast, and see beyond what exists.
Full Time (On Site)
Uk
Exp: Entry-level Department: It
Description
We are looking for a Senior AI Engineer — a true cheetah in the AI world — fast, innovative, and deeply skilled. The ideal candidate must have strong experience in Generative AI and Image Processing/Recognition, along with a proven track record in leading AI teams. You’ll be working on cutting-edge AI products, building, deploying, and scaling real-world AI solutions.
Requirements
- Key Responsibilities:
- Design, build, and deploy advanced AI/ML models, with a major focus on Generative AI (LLMs, diffusion models, GANs, etc.) and Computer Vision (image recognition, object detection, image segmentation).
- Architect and scale AI solutions for production environments.
- Lead technical design discussions and project planning for AI initiatives.
- Collaborate closely with cross-functional teams including product managers, data scientists, and engineers.
- Mentor and support junior engineers, helping to grow the team’s AI capabilities.
- Stay updated on the latest AI/ML research and innovations and bring new ideas to the table.
- Ensure best practices in model training, evaluation, deployment, and monitoring.
- Required Skills & Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or related fields.
- 4+ years of experience in AI/ML development and deployment.
- Mandatory hands-on experience with Generative AI (e.g., LLMs, GANs, Diffusion Models).
- Strong expertise in Image Processing and Image Recognition techniques.
- Expertise with machine learning frameworks such as TensorFlow, PyTorch, or JAX.
- Solid Python programming skills (knowledge of C++/Java is a plus).
- Strong understanding of deep learning, computer vision, NLP, and reinforcement learning.
- Experience deploying models to cloud environments (AWS, Azure, or GCP).
- Prior experience leading and mentoring engineering teams.
- Excellent analytical, problem-solving, and communication skills.
- Preferred:
- Experience with MLOps tools (MLflow, Kubeflow, SageMaker, Vertex AI, etc.).
- Research background or publications in top AI/ML conferences (NeurIPS, CVPR, ICML, etc.).
- Familiarity with prompt engineering, fine-tuning LLMs, and synthetic data generation.
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