16 of 16 Part-Time PyTorch Jobs in the City of London

platforms for sensitive environments. Collaborate across engineering, security, and product teams to deliver at pace and scale. The toolkit youll use Data Science & Engineering: Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow), SQL, NoSQL, Spark, big data ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js DevOps & Cloud: CI/CD, Docker, AWS (S3 More ❯

performance inference. Requirements 5+ years in AI/ML engineering or applied research, with deep experience in LLMs, generative AI, or autonomous AI agents. Strong programming skills in Python, PyTorch, TensorFlow, or JAX. Hands-on experience with agentic AI, multi-step reasoning, and decision-making pipelines. Knowledge of RAG, vector databases, embeddings, and autonomous task orchestration. Experience deploying AI models More ❯

involvement in LLM projects including training, fine-tuning, or production deployment Strong track record in scalable AI system development Technical Expertise Expert-level Python programming with deep knowledge of PyTorch, TensorFlow, or JAX Proven experience with distributed computing environments and modern MLOps workflows Practical knowledge of LLM toolkits (Hugging Face ecosystem, training frameworks) Strong problem-solving abilities for complex model More ❯

in AI/ML, with at least 1 year focused on Generative AI and NLP. Strong programming skills in Python; proficient in libraries such as NumPy, Pandas, scikit-learn, PyTorch, TensorFlow. Proven experience building and scaling GenAI applications in production. Expertise in LLM architectures (OpenAI, LLaMA, Mistral, etc.) and RAG implementation. Familiarity with frameworks like LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen More ❯

structured and unstructured data. Build data pipelines, models, and AI applications using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with stakeholders and More ❯

with message brokers (Kafka, SQS/SNS, RabbitMQ). Knowledge of real-time streaming (Kafka Streams, Apache Flink, etc.). Exposure to big-data or machine-learning frameworks (TensorFlow, PyTorch, Hugging Face, LangChain). Understanding of infrastructure and DevOps (Terraform, Ansible, AWS, Kubernetes). Exposure to fintech or start-up environments. Mindset & Attributes: Positive, objective-focused, and collaborative. Willingness to More ❯

a similar role, preferably within the finance industry or at a leading technology company. Strong expertise in algorithms, data structures, multivariate calculus, and linear algebra. Proficient in Python, TensorFlow, PyTorch, or similar languages and frameworks, with experience writing CUDA kernels and profiling GPU code a plus. Excellent communication skills, with the ability to work effectively in cross-functional teams and More ❯

Deep knowledge of ML/statistical methods (e.g. supervised/unsupervised, Bayesian, time-series). Strong Python skills with core libraries (NumPy, Pandas, Scikit-Learn) plus deep learning frameworks (PyTorch, TensorFlow). Strong leadership in project delivery, architecture, and technical decision-making. Excellent communicator, able to simplify complex ideas for any audience. Strategic thinker with awareness of FS sector trends. More ❯

experience as a Data Scientist or Data Engineer Strong command of Python (including libraries such as scikit-learn, NumPy, matplotlib) Experience in deep learning frameworks such as TensorFlow or PyTorch Knowledge of SQL and relational databases; experience with Big Data environments Familiarity with API development and NoSQL databases Understanding of CI/CD practices , AWS , and GIT Background in working More ❯

Experience building and deploying ML models into production (e.g., in forecasting, optimisation, or computer vision) Proficiency in Python and familiarity with key ML libraries like Scikit-learn, TensorFlow, or PyTorch Solid foundation in statistical modelling and machine learning techniques Exposure to cloud technologies such as AWS, especially services like SageMaker or Lambda, is a bonus Comfortable collaborating with software teams More ❯

and integrating third party generative AI models. Ideal background: 3+ years of experience in machine learning, deep learning or AI engineering Advanced proficiency in Python and ML frameworks like PyTorch Experience deploying and maintaining scalable production-grade AI systems Strong understanding of data pipelines, MLOps and cloud platforms (AWS and Azure) Experience working in small or mid-sized tech/ More ❯

preferred Demonstrated ability to deploy production-level ML modelsparticularly in optimisation, demand forecasting, or computer vision Advanced proficiency in Python and ML frameworks such as Scikit-learn, TensorFlow, or PyTorch Solid understanding of supervised and unsupervised learning, statistical modelling, and mathematical optimisation Hands-on experience with AWS services, especially SageMaker, Lambda, and related infrastructure Willingness to contribute to backend development More ❯

engineers, product and commercial teams to bring ideas to life What theyre looking for: 13 years experience in applied ML/AI (or equivalent projects) Strong Python skills with PyTorch, Hugging Face or scikit-learn Experience experimenting with LLMs (fine-tuning, embeddings, prompt chaining etc.) A passion for turning messy real-world data into something powerful and production-ready Excitement More ❯

years experience in machine learning engineering (some research is fine but this should be coupled with strong and referencable applied work in production.) Strong Python plus frameworks such as PyTorch - production experience with Docker/AWS Proven track record of taking models from concept to production with measurable impact - ROI/Gains/Drops/Reducations Experience with time-series More ❯

for real-time deployment. What Were Looking For 3+ years experience building and deploying deep learning systems, with shipped models or published research. Strong Python skills and proficiency in PyTorch or JAX. Hands-on with at least one of: LLMs, VLMs, or image/video generative models. Experience with deep learning infrastructure (datasets, distributed training, checkpointing, etc.). Clear, structured More ❯

delivering ML projects from idea production with measurable impact. Deep hands-on expertise with LLMs (fine-tuning, prompt engineering, evaluation, and deployment at scale). Hands-on experience with PyTorch/TensorFlow, LangChain, vector databases , or similar tools. Excellent communicator; comfortable working with non-technical stakeholders. Thrive in chaos and love building zero-to-one . This isnt just another More ❯