City of London, London, United Kingdom Hybrid/Remote Options
Experis UK
Required Skills & Experience Proven experience (3–5+ years) as a Machine Learning Engineer , Data Scientist , or similar role. Strong programming skills in Python (experience with libraries such as TensorFlow, PyTorch, scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker More ❯
Required Skills & Experience Proven experience (3–5+ years) as a Machine Learning Engineer , Data Scientist , or similar role. Strong programming skills in Python (experience with libraries such as TensorFlow, PyTorch, scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker More ❯
field. 7+ years of professional software development experience, with at least 3 years in AI/ML. Strong proficiency in Python , including libraries like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch . Solid understanding of ML algorithms , NLP , deep learning , and statistical methods. Experience with Docker, Kubernetes , and cloud platforms like AWS/Azure/GCP . Hands-on experience with More ❯
the language) and in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data pipelines for analytics and modeling workflows. ML Ops & deployment More ❯
the language) and in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data pipelines for analytics and modeling workflows. ML Ops & deployment More ❯
City of London, London, United Kingdom Hybrid/Remote Options
Intellect Group
Science, Engineering, Mathematics, or a related discipline Demonstrated project experience (academic research, dissertation work, or personal projects) applying machine learning or AI techniques Strong programming skills in Python (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Familiarity with cloud platforms (AWS, Azure, or GCP) and basic distributed systems concepts Strong problem-solving mindset with a passion for building practical, scalable AI More ❯
Science, Engineering, Mathematics, or a related discipline Demonstrated project experience (academic research, dissertation work, or personal projects) applying machine learning or AI techniques Strong programming skills in Python (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Familiarity with cloud platforms (AWS, Azure, or GCP) and basic distributed systems concepts Strong problem-solving mindset with a passion for building practical, scalable AI More ❯
for sensitive environments. Collaborate across engineering, security, and product teams to deliver at pace and scale. The toolkit you’ll 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 ❯
City of London, London, United Kingdom Hybrid/Remote Options
Areti Group | B Corp™
for sensitive environments. Collaborate across engineering, security, and product teams to deliver at pace and scale. The toolkit you’ll 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 ❯
Excellent customer-facing communication across scientific and engineering audiences. Experience in pharma, biotech, medtech, or healthcare environments (ideal). MSc in Computer Science or equivalent experience. Bonus Familiarity with PyTorch, JAX, Hugging Face, and AWS ML services. Experience optimizing models for low-latency inference. Open-source contributions and/or startup experience. Why This Is Unique Globally competitive salary + More ❯
Excellent customer-facing communication across scientific and engineering audiences. Experience in pharma, biotech, medtech, or healthcare environments (ideal). MSc in Computer Science or equivalent experience. Bonus Familiarity with PyTorch, JAX, Hugging Face, and AWS ML services. Experience optimizing models for low-latency inference. Open-source contributions and/or startup experience. Why This Is Unique Globally competitive salary + More ❯
RFP responses, bid documentation, and client presentations. Hands-on experience with data science platforms such as Databricks , Dataiku , AzureML , or SageMaker , and machine learning frameworks such as TensorFlow , Keras , PyTorch , and scikit-learn . Expertise in cloud platforms ( AWS , Azure , Google Cloud ) and experience deploying solutions using cloud provisioning tools such as Terraform . Strong background in technology deployment, including More ❯
City of London, London, United Kingdom Hybrid/Remote Options
LHH
RFP responses, bid documentation, and client presentations. Hands-on experience with data science platforms such as Databricks , Dataiku , AzureML , or SageMaker , and machine learning frameworks such as TensorFlow , Keras , PyTorch , and scikit-learn . Expertise in cloud platforms ( AWS , Azure , Google Cloud ) and experience deploying solutions using cloud provisioning tools such as Terraform . Strong background in technology deployment, including More ❯
/LLM/NLP/CV models. - Strong understanding of machine learning fundamentals, statistical inference, and model evaluation. - Advanced proficiency in SQL (e.g., PostgreSQL, ELT/ETL) and Python (PyTorch, LightGBM, Scikit-learn). - Experience with modern AI concepts: prompt engineering, embeddings, vector search, etc. - Skilled in managing complex codebases (Git) and working with cloud platforms (GCP, AWS). - Excellent More ❯
/LLM/NLP/CV models. - Strong understanding of machine learning fundamentals, statistical inference, and model evaluation. - Advanced proficiency in SQL (e.g., PostgreSQL, ELT/ETL) and Python (PyTorch, LightGBM, Scikit-learn). - Experience with modern AI concepts: prompt engineering, embeddings, vector search, etc. - Skilled in managing complex codebases (Git) and working with cloud platforms (GCP, AWS). - Excellent More ❯
internships, or personal projects) applying machine learning or AI techniques Strong programming skills in Python and TypeScript (this is essential) Experience with common Python data/ML libraries (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Experience building or contributing to TypeScript codebases (e.g. Node.js backends, React frontends, or internal tools) Hands-on exposure to AWS (e.g. EC2, S3, IAM; bonus More ❯
City of London, London, United Kingdom Hybrid/Remote Options
Intellect Group
internships, or personal projects) applying machine learning or AI techniques Strong programming skills in Python and TypeScript (this is essential) Experience with common Python data/ML libraries (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Experience building or contributing to TypeScript codebases (e.g. Node.js backends, React frontends, or internal tools) Hands-on exposure to AWS (e.g. EC2, S3, IAM; bonus More ❯
Python expertise: Skilled in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data pipelines for analytics and modelling workflows. Model development & deployment More ❯
Python expertise: Skilled in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data pipelines for analytics and modelling workflows. Model development & deployment More ❯
natural language processing or other relevant AI fields. Proven track record of designing, developing, and deploying AI systems in production environments. Proficient in Python and key ML libraries (e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers). Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks, MLflow, LangChain, LangGraph. Proven experience with modern engineering More ❯
City of London, London, United Kingdom Hybrid/Remote Options
KPMG UK
natural language processing or other relevant AI fields. Proven track record of designing, developing, and deploying AI systems in production environments. Proficient in Python and key ML libraries (e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers). Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks, MLflow, LangChain, LangGraph. Proven experience with modern engineering More ❯
on-prem setup Requirements: 25 years experience in ML engineering/MLOps roles Strong proficiency in Python and experience with relevant ML libraries/frameworks (pandas, numpy, sklearn, TensorFlow, PyTorch) Strong understanding and experience in implementing end-to-end ML pipelines (data, training, validation, serving) Experience with ML workflow orchestration tools (e.g., Airflow, Prefect, Kubeflow) and ML feature or data More ❯
Skills: Proficiency in Python, with a deep understanding of machine learning algorithms, deep learning, and generative models. Advanced AI Skills and Testing: Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch), hands-on experience in deploying AI/ML solutions as a service/REST API on Cloud or Kubernetes, and proficiency in testing of developed AI components. Responsibilities also include More ❯
Skills: Proficiency in Python, with a deep understanding of machine learning algorithms, deep learning, and generative models. Advanced AI Skills and Testing: Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch), hands-on experience in deploying AI/ML solutions as a service/REST API on Cloud or Kubernetes, and proficiency in testing of developed AI components. Responsibilities also include More ❯
