Similar Jobs
Artificial Intelligence • Hardware • Information Technology • Security • Software • Cybersecurity • Big Data Analytics
As an AI/ML Engineer Co-Op, you will assist in developing AI tools, work with data engineers, understand data patterns, and ensure tools align with business needs.
Top Skills:
DjangoFlaskLlm PromptingPandasPythonSeabornSnowflakeSQL
Big Data • Fintech • Mobile • Payments • Financial Services
The Senior Staff Machine Learning Engineer will lead the design and scaling of advanced ML systems, mentor engineers, and define technical strategy across Affirm.
Top Skills:
KubeflowMlflowPythonPyTorchRaySparkXgboost
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
As a Staff Machine Learning Engineer, you'll lead AI initiatives using large-scale data, optimize ML models for edge devices, and collaborate with cross-functional teams.
Top Skills:
C++PythonRayRustSpark
At Numrah, we build intelligent, modern applications that combine cutting-edge engineering with practical machine learning. We're looking for a Machine Learning Engineer who is deeply grounded in ML theory and excited to design, train, fine-tune, and deploy Large Language Models (LLMs) and other ML systems in real-world production environments.
You’ll work closely with backend and product individuals/teams to deliver smart, scalable features—from rapid experimentation to full-scale deployment. If you’re passionate about ML theory, hands-on with LLMs, and know how to ship high-impact AI features, this role is for you.
What You’ll Do
- Design and implement ML solutions from ideation to production
- Fine-tune and integrate LLMs
- Deploy and monitor LLM-powered features at scale in real-world products
- Collaborate with engineers and product teams to build intelligent, user-facing features
- Write clean, scalable code and detailed technical documentation
- Stay current with the latest in ML research, LLM capabilities, and MLOps best practices
Must-Haves
- Be an Arabic speaker
- Have at least 1 year of non-internship experience in Machine Learning.
- Strong ML and DL theory background, you don't just use things, you know how they are working under the hood.
- Experience training and fine-tuning LLMs, with practical knowledge of transformer architectures
- Solid production-level Python experience and strong software engineering fundamentals (OOP, OOD, DSA)
- Familiarity with LLM integration frameworks like HuggingFace Transformers, OpenAI, or LangChain
- Familiarity with ML data pipelines and manipulation tools (e.g., Pandas, NumPy)
- Strong research, writing, and documentation skills
- Collaborative mindset and ability to communicate technical ideas clearly
Nice-to-Have
- Experience deploying LLM-based features to production
- Knowledge of parameter-efficient fine-tuning (LoRA, QLoRA, PEFT)
- Familiarity with RAG pipelines and vector databases (e.g., Pinecone, Weaviate)
- Understanding of model serving and inference optimization (quantization, batching)
- Exposure to MLOps practices (monitoring, versioning, CI/CD for ML)
- Experience with RESTful APIs, Docker, and cloud platforms (GCP, AWS, or Azure)
- Interest in NLP applications, smart assistants, or chatbot systems
What you need to know about the London Tech Scene
London isn't just a hub for established businesses; it's also a nursery for innovation. Boasting one of the most recognized fintech ecosystems in Europe, attracting billions in investments each year, London's success has made it a go-to destination for startups looking to make their mark. Top U.K. companies like Hoptin, Moneybox and Marshmallow have already made the city their base — yet fintech is just the beginning. From healthtech to renewable energy to cybersecurity and beyond, the city's startups are breaking new ground across a range of industries.
